Whatever the weather in Europe, come rain, storms, snow, sleet or sun, the meteorological satellite, Meteosat-9, will be observing it. Meteosat-9 (Figure 1) is in orbit 36,000 km above the equator from where it gets a space-eye view of weather systems as they develop. The images it transmits down to ground stations every 15 minutes – in the visible light and infrared wavelengths – are used by meteorologists to help produce weather forecasts. While Meteosat-9 stays in one place in relation to the Earth – i.e. it is geostationary – it is complemented by another meteorological satellite, Metop-A, which circles closer to the Earth in a polar orbit at 817 km and collects images and more detailed vertical profiles of atmospheric conditions.

Both satellites provide images and atmospheric data that are used by meteorologists to make weather forecasts, and over the longer term they help to monitor changes in the Earth’s climate. The good news for researchers, climate modelers, amateur meteorologists, and anyone else wanting to see what Meteosat-9 and Metop-A are observing, is that the data they produce are freely available for non-commercial or research purposes. One option is to access the data via the Internet or, for a relatively small cost, you can even set up your own satellite dish and beam the data collected from Meteosat-9 and other satellites onto the PC in your office or home in near-real time.

Accessing EUMETSAT Satellite Data

The data produced by Meteosat-9 and Metop-A are available from EUMETSAT, Europe’s meteorological satellite agency. EUMETSAT operates Meteosat-9, and its in-orbit backup Meteosat-8 (Figure 2), over Africa to provide weather images for Europe and Africa. The main payload on both of these satellites is the Spinning Enhanced Visible and Infrared Imager (SEVIRI) which builds up images of the Earth’s surface and atmosphere in 12 different wavelengths once every 15 minutes. Regional images, covering smaller areas, can be obtained as frequently as every 5 minutes.

The satellites also carry the Geostationary Earth Radiation Budget (GERB) instrument which provides valuable data on reflected solar radiation and thermal radiation emitted by the Earth and atmosphere.

In addition, EUMETSAT operates two more geostationary satellites – Meteosat-6 and -7 – which are located over the Indian Ocean.

Tropical storm Bill moving westward through the Hurricane Alley – August 2009 Meteosat-8 RGB composite.

Metop-A, the polar-orbiting satellite, carries a host of instruments – some of the key ones are as follows:

• The AVHRR (Advanced Very High Resolution Radiometer) scans the Earth’s surface in six spectral bands to provide day and night imaging of land, water and clouds. It also measures sea-surface temperature, ice, snow and vegetation cover.

• The High Resolution Infrared Radiation Sounder (HIRS) and newer state-of-the-art Infrared Atmospheric Sounding Interferometer (IASI) measure infrared radiation emitted from the surface of the Earth to obtain highly accurate temperature and humidity profiles.

• The Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) provide global information on atmospheric temperature and humidity profiles as well as precipitation, even in cloudy areas.

• GOME-2, (Global Ozone Monitoring Experiment), a spectrometer that is used to derive detailed profiles of the atmospheric content and profile of ozone, nitrogen dioxide, water vapor, oxygen, bromine oxide and other gases.

• GRAS (Global Navigation Satellite System Receiver for Atmospheric Sounding) – a Global Positioning Satellite (GPS) receiver that provides atmospheric soundings of the temperature and humidity of the Earth’s atmosphere.

• An Advanced Scatterometer (ASCAT) which measures wind speed and direction over the ocean.

EUMETSAT also processes and distributes data from the Jason-2 ocean altimetry satellite which measures ocean surface height and is playing a key role in monitoring sea level rise – a major concern relating to climate change. It also yields valuable information on ocean circulation, surface wind speeds and wave heights.

All EUMETSAT satellites transmit their measurement and telemetry data to receiving stations on the ground. From there, data are relayed to EUMETSAT’s Control Centre in Darmstadt, Germany, where they are processed, archived in the EUMETSAT Data Centre, and retransmitted in near-real time to the user community, mainly via a system called EUMETCast.

Accessing Data via Eumetcast?

EUMETCast is a data distribution system for high-speed, high-volume data delivery of the EUMETSAT products. It is based on standard Digital Video Broadcast (DVB) technology and uses commercial telecommunication satellites to transmit files (data and products) to a wide user community. There are three broadcasts: Europe in the Ku-band via the Eurobird-9 satellite, Africa in the C-band via the AtlanticBird-3 satellite and North and South America in the C-band via the NewSkies-806 satellite.

The data streams and products delivered via EUMETCast include observations from EUMETSAT’s Meteosat and Metop satellites, the US National Oceanic and Atmospheric Administration’s (NOAA’s) Geostationary Operational Environmental Satellites (GOES), the Japan Meteorological Agency’s Multifunctional Satellite (MTSAT) and Chinese Fengyun-2 satellites. At their most frequent, these data are delivered to users within five minutes of processing.

Also available via EUMETCast are Moderate Resolution Imaging Spectroradiometer (MODIS) products covering selective geographical regions, numerical weather forecasts, in-situ observational data, land application products covering Europe, Africa and South America, global and regional marine meteorological and ocean surface products, and atmospheric chemistry products.

Set Up Your Own EUMETCast Reception Station?

If you would like to set up your own reception station to receive a EUMETCast data stream, a simple system would need to comprise a standard PC with DVB card inserted and a satellite dish (off-set antenna) fitted with a digital universal V/H LNB.

All components of a EUMETCast reception station are commercially available and as an example, the hardware costs for a single PC station for EUMETCast Europe (Ku-band) reception start at around €1,500. In addition, a EUMETCast client software package is required for handling the incoming DVB and storing it as data files. This package is available directly from EUMETSAT at a one-off cost of €100 per station installation. More information is available on the process of setting up and registering a EUMETCast reception station at: http://www.eumetcast.com

Access to EUMETCast is open to any user within the footprint of one or more of the EUMETCast beams. Once users have equipped themselves with the necessary hardware components, they are invited to register with EUMETSAT in order to gain access to the various EUMETCast data streams. The online registration form is available at https://eoportal.eumetsat.int/Registration/.

Getting Data from the EUMETSAT Data Centre

Another way of accessing meteorological satellite data is via the EUMETSAT Data Centre, which was first established in 1995 and holds an archive of over 25 years of meteorological satellite data and products – one of Europe’s largest and most comprehensive collections in this field.

The range of available EUMETSAT satellite data and products can be searched using the online Product Navigator – a central data discovery service which also includes third-party products disseminated via EUMETCast. Users can search for data, subscribe to EUMETCast-disseminated services and, in future, order data via the EUMETSAT Data Centre.

According to Harald Rothfuss, manager of the Data Centre; “User access to and orders of EUMETSAT data from the Data Centre are increasing all the time. An average of 50 new users are registering every month to be able to order data from the Data Centre and over 2,500 users are currently registered. As many researchers are now interested in longer time series, for example for climate-related studies, orders in the range of 1 Terabyte (1 TB) are not unusual.”

“In the near future, the process of searching and ordering from the Data Centre will be integrated into the new EUMETSAT Earth Observation (EO) Portal, a project planned to be available during 2010. Interoperability standards implemented in the EO Portal will give users not just a central point where they can manage subscriptions to data, products and services provided by EUMETSAT, it will also allow even more users easy access to EUMETSAT data. The EO Portal with its interoperability standards is an important contribution to various organizations and programs – like the World Meteorological Organization, the Global Earth Observation System of Systems (GEOSS) and the Global Monitoring for Environment and Security (GMES) initiative.”

When it is finalized, the EO Portal will offer the user community ’single sign-on’ access to all data services offered by EUMETSAT. In particular, subsequent developments will give users the ability to register and manage their accounts for access to the Data Centre and User Notification Service through the EO Portal user management service. The EO portal can be accessed at https://eoportal.eumetsat.int/

Sea fog over the North Sea – April 2009 Meteosat-8 HRV image.

Real-Time Satellite Product Display

A third alternative to accessing the data collected by EUMETSAT weather satellites is to visit the real-time image display section on the EUMETSAT website. There you will find a comprehensive compilation of EUMETSAT satellite products reproduced in graphical form. The service is provided on a 24/7 basis and the image files displayed are automatically refreshed with the latest, openly available data from EUMETSAT satellites. In addition, a limited archive of 100 files per product is provided. The real-time images service incorporates satellite image-data loops, visualized products derived from satellite data and a selection of RGB composite images.

Many Ways to Access EUMETSAT Satellite Data

So to summarize, if you are interested in seeing what meteorological satellites are observing high above the Earth, then there are a number of options: you can visit the EUMETSAT website and see the real-time imagery, you can access archived satellite products at the Data Centre, and you can even set up your own EUMETCast receiving station for weather satellite data, giving you a unique view of what the weather has in store.

Useful links

http://www.eumetsat.int/Home/Main/Image_Gallery/Real_Time_Imagery/index.htm

http://www.eumetsat.int/Home/Main/Access_to_Data/ProductNavigator/index.htm

http://www.eumetsat.int/Home/Main/Access_to_Data/Delivery_Mechanisms/SP_1117714355151

News Analysis by Peter Fairley

The Congo River has the potential to power a continent. In power and ecological wealth, Africa’s Congo River and the rainforests it drains stand second only to the Amazon. In regularity, the Congo is unrivalled. Because its tributaries straddle the equator, the Congo is inundated with rain water in all seasons. At its July/August low point the river eases to a still raging 30,000 cubic meters per second on average. In 1905, the ‘driest’ year in recorded history, the Congo bottomed out at a mighty 21,400 m³/sec, nearly double the Mississippi’s average flow. This consistent power translates into a hydropower potential that knows no equal in scale and sustainability, concentrating at a natural pinch point 225 kilometers upstream from Kinshasa, the capital of the Democratic Republic of Congo (DRC). There above a 15-kilometer stretch of cascading falls and rapids lies the site of the Inga Dams and, in the view of power engineers, the energetic promise of more than one continent. Until now, however, this promise has been unrealized.

An estimated 370,000 gigawatt-hours of energy flow through the Inga Dams every year, exceeding the hydropower generation of Canada (where hydro engineers flooded tens of thousands of square kilometers in British Columbia, Quebec and Newfoundland to make Canada the world’s hydropower leader). The question is whether Inga’s potential can be harnessed amidst the flood of violence and corruption that surrounds and infuses the DRC. Inga’s installations currently capture only a fraction of its potential. Just 1,775 megawatts of power generating capacity has been installed at Inga—about three percent of Canada’s installed capacity—and the DRC government acknowledges that only a fraction of Inga’s turbines currently operate.

The DRC desperately needs energy to grow. This mineral-rich expanse the size of Western Europe is Africa’s fourth most populous country but also one of its poorest. The International Monetary Fund estimates the DRC’s gross domestic product per capita at $171 – placing it last among the 180 countries studied last year. That’s lower in real terms than when the DRC threw off colonial rule by Belgium in 1960. In addition to myriad social and political challenges, economic growth is thwarted by a dearth of reliable electricity. The DRC’s mining-rich eastern Katanga province and Kinshasa province already suffer a net shortfall of 1,400 megawatts that holds back growth.

Inadequate access to energy is the single largest impediment to economic growth across Africa according to a World Bank study released in November (2009), Africa’s Infrastructure: A Time for Transformation. As the report notes, the generation capacity of the 48 countries of sub-Saharan Africa is equivalent to that of Spain, which has one-twentieth the population. In all, inadequate electricity, water, roads and communications systems cut economic growth every year by 2 percentage points across sub-Saharan Africa. Of the $93 billion investment in infrastructure needed annually over the next decade, almost half is needed to address the continent’s power supply crisis. And the DRC’s investment shortfall is particularly severe. The state power utility, the Société Nationale d’Électricité (SNEL), delivers electricity to just 7% of the DRC’s 68 million people.

Revitalizing and extending the hydropower works at Inga is the centerpiece of plans by the government in Kinshasa, SNEL and numerous international partners who aim to re-energize the DRC, underpin its economic future and secure its tenuous democracy. Yet, after a decade of struggle amidst ongoing violence, political divisions and mismanagement, dividends are elusive and frustration is rising.

By Africa, For Africa

International cooperation to squeeze more power from Inga got underway in 2002. The DRC was just emerging from five years of turmoil that began with the 1997 overthrow of Mobutu Sese Seko, the corrupt Western-installed dictator that dominated the country for three decades. Congolese rebel leader Laurent Kabila unseated Mobutu with help from Rwanda and Uganda, but these neighbors invaded the following year. Forces from Angola, Namibia and Zimbabwe came to Kabila’s defence, turning the DRC into an international battleground until 2002 when Joseph Kabila, appointed president in 2001 following his father’s assassination, secured a peace deal that brought some stability and spurred an international effort to rebuild the DRC’s infrastructure.

The DRC government identified restoration of its war-ravaged electrical system as an early priority for national recovery. The World Bank stepped up to support the rehabilitation of the power stations installed under Mobutu to generate electricity from the water flowing into the Inga Dams. The original 1972 station known as Inga 1 was completely dysfunctional and Inga 2, added in 1982, was badly neglected. So too were the transmission lines to distribute their power within the DRC and export customers as far away as South Africa. Power output was barely a third of Inga 1 and 2’s original capacity according to the World Bank.

Meanwhile a made-in-Africa program took shape to realize Inga’s further potential under the encouragement of the African Union and its New Partnership for Africa’s Development. A key goal was to interconnect Africa’s power systems as a means to expand access to electricity and reduce its cost. Inga quickly emerged as a spotlight project for NEPAD.

Adding a third set of turbines to draw another 3,500 MW of power from Inga, tripling its generating capacity, and to build new transmission lines within DRC and southern Africa was the ambitious goal. Fellow members of the Southern African Development Community – South Africa, Angola, Botswana and Namibia – partnered with the DRC to share the cost and the power. By 2004 the five country’s national utilities had partnered to establish a Botswana-based operation called the Western Power Corridor Company (Westcor). They signed up Pat Naidoo, the top transmission expert for South African utility Eskom to be CEO, with a mandate to establish the feasibility and then build ‘Inga 3’ and its accompanying transmission lines.

Power experts have long argued Africa needs to support large capital-intensive energy projects and, as a result, bringing in Westcor was a move toward regional interdevelopment. It was also a move that was likely to profit not only Westcor’s members but African consumers as well. The river’s steady flow would guarantee Westcor’s power generation at a cost of just 5 cents per kilowatt-hour (cts/kWh). That is a fraction of Africa’s 18 cts/kWh average for grid-supplied power and the 40 cts/kWh firms pay for backup generators during all-too-frequent blackouts. It also beats the cost of other large-scale renewable power generating options according to recent cost estimates used by South Africa’s energy regulator. For example, wind and solar power are pegged at 12 cts/kWh and 21 cts/kWh respectively.

Power demand from South Africa, the region’s economic giant, would underpin financing for the $8-billion scheme. Westcor promised the DRC $500 million per year in royalties for use of the Congo, and profits split equally among the partners—the DRC included. “We’re actually building a cash machine here,” is how Naidoo described Inga 3 in a July 2009 talk to the South African Institute of Electrical Engineers. “The cash flows are substantial and massive and there’s plenty of energy for all,” said Naidoo.

Best of all, it was a by-Africa, for-Africa model of development. Modular installation of the hydro turbines, one 220-250 MW turbine at a time, meant that African banks could finance the installation, avoiding delays that come with international financing.

Complex Currents

Westcor’s implementation has slid, however, as other forces at play threaten to wreck its vision of African unity through the sharing of Congolese hydropower. Joseph Kabila’s election in 2006 has yet to secure his universal legitimacy, particularly in the eastern regions bordering Rwanda and Uganda that are marked by persistent sexual violence and killings according to NGOs such as Human Rights Watch and Doctors Without Borders. The World Bank categorizes the DRC as a ‘fragile’ state. Mismanagement is rife. And international developers eager to exploit the DRC’s mineral wealth (and need electricity to do so) also feed political divisions and corruption.

Since the waning days of its latest war, DRC officials have cut a series of side deals with international suitors, starting with a 2001 deal with German industrial firm Siemens promising $960 million to restore power flows from Inga 1 & 2 in exchange for access to the DRC’s diamond resources. That deal had fallen by the wayside by 2005 when Canadian mining firm MagIndustries signed a deal with SNEL to rehabilitate turbines in exchange for power for present and future mining operations. One turbine was ultimately refurbished but SNEL dropped the broader deal after inquiries by DRC parliamentarians revealed that it represented a “stealth privatization” of Inga at unfavorable terms for the DRC (equivalent to paying 26.5% interest on financing for the Inga 1 & 2 upgrades).

Other players have encouraged the DRC to look beyond modular upgrades such as Inga 3 to a far larger opportunity, with far greater environmental impacts. Known as Grand Inga, the idea is to dam the Congo upstream of the existing dams, flooding the adjacent Bundi Valley with enough water to generate up to 39,000 MW of power. Such an installation would produce nearly double the output of China’s recently completed Three Gorges hydroelectric project, the world’s largest to date. In 2002 French utility Electricité de France calculated how to finance the $80-billion-plus effort: by traversing the Sahara with the world’s longest power line, thus harnessing Congo’s flow to supply Europeans hungry for power.

One Inga side deal ultimately grew into a direct challenge to Westcor: a 2007 agreement with multinational mining giant BHP Billiton to supply up to 2,000 MW from Inga 3 for an aluminum smelter that Billiton proposes to build on DRC’s Atlantic coast. The company confirms that a “pre-feasibility study” for the hydropower project, funded by Billiton, has been completed. “The future of the aluminium smelter project hinges on progress being made on the Inga 3 project and it is still very early days,” said Illtud Harri, a London-based spokesperson for BHP Billiton, in an email exchange with Earthzine.

Billiton’s offer gave the DRC an alternate anchor client for Inga 3’s power, emboldening the DRC government to consider building Inga 3 on its own. Last summer the tensions within the Westcor’s partnership blew open after two years of speculation and confusion. Naidoo, during his talk with South Africa’s electrical engineers in Johannesburg last July, vented his frustration in comments reported by South African engineering and energy publications.

“We are in mid-flight now – and our partner, the DRC government, is starting to change the mandate on Inga 3. They are basically taking the foundation from under our feet,” said Naidoo, according to Johannesburg-based magazine WATTnow. Naidoo did not respond to requests for comment, but news reports since last summer suggest that the DRC is trying to restructure Westcor.

Progress on Inga 1 & 2, meanwhile, is almost as slow. Since the World Bank approved $167 million in emergency support for the DRC’s electricity system in 2002, further funding has materialized from the World Bank itself and other lenders, such as the European Investment Bank and the African Development Bank, with the aim to rebuild Inga 1 & 2, strengthen or add power lines, and extend power distribution to 250,000 additional people in Kinshasa (for a 0.4% increase in the DRCs electrification rate). But real change on the ground is thin. To date only two of Inga’s turbines have been refurbished, and power output remains at barely 40% of the original capacity—little improved over 2002.

According to the World Bank that stasis represents an achievement of sorts, because post-war economic growth has boosted demand for power and placed more strain on the DRC’s “already-overloaded network.” But stasis is of little solace to the rural communities throughout the DRC – including those which surround Inga itself – that are deforesting their lands in search of energy as buzzing power lines overhead carry the Congo’s power away from their region.

Governance Unrealized

Explanations for the electrical short-circuit in the DRC’s recovery share blame between external forces—including development lenders such as the World Bank—and the DRC elite who wield political power and manage its institutions. With regards to the latter, slow progress on Inga is seen as a symptom of management that is at best incompetent and short-sighted and, at worst, self-interested and corrupt.

Consider WATTnow editor Paddy Hartdegen’s September 2009 editorial, accusing the DRC of spurning its African partners. Hartdegen writes that the DRC, “has chosen to grab whatever money is on offer now and who cares about relationships, regional development or a long term future.” The magazine’s article on the reversal was illustrated by a fanciful piece of art showing the DRC’s Westcor partner countries literally hung out to dry.

A commission of the DRC Senate issued a report last September on mining sector revenues that shows how wide of the mark government administration can be. They found that the government received just $92 million of the $450 million it was due from this key industry, thanks to under-invoicing, tax evasion, smuggling, fraudulent contracts and poor accounting. Of nearly $75 million in taxes due, for example, officials booked just $814,042. Kinshasa-based newspaper Le Potentiel quoted Senator Henri-Thomas Lokondo, a commission member, calling the report evidence of “systematic fraud.”

Some observers see mismanagement as secondary, challenging the export-driven Inga expansion proposals as an extension of the European imperialism that has left such deep scars in Africa. Anders Lustgarten with the Brussels-based NGO Counter Balance, which critiques investments by the European Investment Bank, criticizes the power export plans in his November 2009 report, Conrad’s Nightmare: The World’s Biggest Dam and Development’s Heart of Darkness.

Map courtesy of African Energy.

Lustgarten tells Earthzine that any hydropower project on the Congo that delivered electrification and poverty reduction would be an “immeasurable service both to human beings and to the ecosystem.” In fact, according to the World Energy Council, an international group of governments and energy producers from 90 nations, Grand Inga could transform Africa’s power supply, providing “access to affordable and clean electricity to more than 500 millions of Africans who today have none.” But that cannot happen if the power is exported to Europe instead.

Lustgarten offers a practical solution to ensure that Inga’s development offers local benefit: Require the contractors selected to execute Inga projects to build domestic power connections and provide cheap energy to Congolese businesses and schools before they initiate energy exports as “a kind of loss-leader”.

Hydropower critic International Rivers suggests that the DRC look instead to small-scale renewable power technologies, as an antidote to the risk of energy diversion and corruption that comes with energy megaprojects. “Decentralized energy systems based on wind, solar power and micro hydro projects have a better chance of empowering Africa’s rural populations,” writes International Rivers’ policy director Peter Bosshard in a blog post this fall.

The World Bank, in email responses to Earthzine, defends its financing of power-exporting transmission lines linked to the Inga upgrades. The development bank says that increasing local energy supplies is a key criterion for its projects, and argues that Inga upgrades will add about 250,000 residents of Kinshasa to the grid as well as some communities around Inga. But it also acknowledges that the impact will be “relatively minor compared to the enormous needs,” nudging up the DRC’s electrification rate by less than 1%.

African Unity Stretched

On first blush Westcor’s Inga 3 project, with its by-Africans-for-Africans model, might seem to escape Lustgarten’s harsh critique. The first 1,000 MW was to stay in the DRC, and the rest would stay in Africa – primarily South Africa.

Even plans to export to South Africa, however, expose domestic political fault lines in the DRC. Naidoo said as much last summer, according to coverage of his July 2009 talk by South African engineering news outlet EE Publishers. DRC president Kabila strongly supports the South African Development Community (SADC) and Westcor’s Inga project, but others are wary. Naidoo says he recognized the divisions while meeting with DRC officials in Kinshasa last summer. “It came home when one said to me: ‘Who is Kabila? He belongs to you – SADC – you are propping him up here’. It’s virtually an anti-SADC type position that is developing in the region.”

What these arguments miss is the very practical benefits of shared power grids. L. Jac Messerschmidt, a former executive at South Africa’s Eskom, wrote in response to Naidoo’s revelations on Westcor that, whoever is to blame for wrecking Westcor’s vision, all players should remember that the region needs a shared southern African power grid to succeed economically. “Without it, the dreams of the region remain in peril,” writes Messerschmidt in a letter to EE Publishers.

That is as true for South Africa and the DRC as it is for the multinational mining companies currently dividing them such as BHP Billiton. “One day the putative smelters will find themselves without backup power when they need it most,” writes Messerschmidt. “The benefits of integrated power grids are obvious to those with long memories.”

By Karen M. St. Germain Senior Member, IEEE
Reprinted from IEEE Geoscience and Remote Sensing Society Newsletter (September 2009)

Introduction

The NPOESS program will launch its second risk reduction mission, the NPOESS Preparatory Project (NPP) in 2011. NPP is a collaboration between the NPOESS program (for risk reduction) and the NASA Earth Science program (for continuity of earth science measurements). The NPP platform will carry five remote sensing instruments, covering the electromagnetic spectrum from microwaves to visible waves. Each of these instruments will be flying for the first time on NPP, although some have substantially more legacy than others.

The Cross-track Infrared Sounder (CrIS) is a hyperspectral instrument that will provide measurements in the infrared over the long to short wave range, from 650 to 2550 cm21 (15.4 to 3.92 μm) In the US, the legacy experience for CrIS comes from the Atmospheric Infrared Sounder (AIRS), currently flying on the NASA EOS missions. In sensor operation, CrIS bears greater resemblance to the Infrared Atmospheric Sounding Interferometer (IASI), flying aboard the EUMETSAT METOP series. The CrIS instrument will work with its microwave counterpart, the Advanced Technology Microwave Sounder (ATMS), to produce atmospheric temperature, moisture, and pressure profiles under most weather conditions. The ATMS traces its legacy to the successful series of Advanced Microwave Sounding Units (AMSUs) currently flying as part of the National Oceanic and Atmospheric Administration (NOAA) Polar Operational Environmental Satellite (POES) system.

The Ozone Mapping and Profiler Suite (OMPS) will monitor atmospheric ozone in three ways: total column ozone, vertical ozone profile, and limb ozone profile. The nadir instruments trace their heritage to the Solar Backscatter Ultraviolet radiometer (SBUV)/2 and the Total Ozone Mapping Spectrometer (TOMS). The Limb profiler is being flown as an experimental sensor aboard NPP, and will provide a higher spatial resolution vertical profile than the nadir instrument. The OMPS sensor measurements are made between 250 and 380 nm.

The Visible/Infrared Imager/Radiometer Suite (VIIRS) collects visible and infrared imagery and radiometric data over the wavelength range 412 nm to 12.01 μm. Although there are differences in sensor operation, the closest VIIRS predecessor is the Earth Observing System (EOS) Moderate-resolution Imaging Spectroradiometer (MODIS) instrument (with additional enhanced capability for imagery across the terminator). Data products from VIIRS range from ocean surface products to cloud properties and land surface characterization. In planning the Calibration and Validation (Cal/Val) campaign for this first launch, we first consider lessons learned from previous Cal/Val campaigns, from both operational and science missions.

Cal/Val Overview
The highest objective of any Cal/Val program must be the accomplishment of the mission for which the program was chartered. In the case of NPOESS, the required National Mission Capabilities are captured in a requirements document (the Integrated Operational Requirements Document, IORD II), which outlines the performance attributes needed for each environmental data product. Fully accomplishing this goal means establishing that the data products meet required performance and are operationally viable. The term “operational viability” means that the products are suitable for inclusion in civilian and defense mission support, with robust performance, minimum down time, and low data latency. Elements of this include a full understanding of data product performance (e.g. error statistics), and rapid resolution of performance issues. For the NPOESS program, the Cal/Val program also plays a role in establishing contractual compliance of the work of the prime contractor.

The Calibration and Validation Program for the National Polar -Orbiting Operational Environmental Satellite System Preparatory Project (NPP)

Lessons Learned from Heritage Programs System View
An earth remote sensing system is a physical system, composed of the phenomena to be sensed, the space borne system making the measurements, and the processing system that packages, transmits, and processes the data. A simple depiction of such a system is shown in Figure 1. The ground processing system executes a series of operations that essentially “walk backward” through the physical system (black arrows in Figure 1), eventually yielding a representation of the environmental phenomena of the earth and atmosphere. These operations fall in to three major categories. The first stage involves unpacking and organizing the data, creating the Level 0 products, or Raw Data Records (RDRs) in NPOESS parlance. Then, the raw data are geolocated and calibrated using information from the spacecraft, the internal calibration targets, and knowledge of sensor performance attained during the prelaunch testing. This process produces radiance measurements and creates the Level 1 products (Sensor Data Records, or SDRs). Finally, the radiances are processed through algorithms to infer properties of the environment from which the emission originated. The outputs of these processes are the Environmental Data Records (EDRs), which are commonly known as Level 2 products. For a microwave sensor there is often one additional intermediate step between the SDR and EDR, where additional antenna pattern corrections are applied. This output of this step is called a Temperature Data Record, or TDR. The algorithms to produce the RDRs, SDRs, and EDRs require input data from the spacecraft (e.g. timing, navigation and pointing information) and the sensors (e.g. temperatures, voltages, sensor state and position). They may also require definable databases such as sensor characterization tables, environmental models and field of view models. Ultimately, the success of the algorithms in accurately reversing the measurement process depends upon a correct interface between the algorithm and each component of the system. A quick survey of past programs gives us insight on what drives the pace and success of the post-launch Cal/Val effort.

Over three generations of first-launch microwave sensors, the length of the Cal/Val program has been dominated by sensor performance and sensor interface issues. Some examples are: 1) Timing and position (dominated by spacecraft flight software, hardware, and spacecraft to sensor alignment), 2) Channel Polarization (inaccurately determined prior to launch), 3) Calibration target errors (dominated by calibration target materials and uniformity of target temperature, 4) Antenna Properties or Field of View Intrusions (dominated by completeness of pre-launch pattern measurements and knowledge of the complete system geometry). System Engineering and management challenges pre-launch have also caused considerable delay in post-launch Cal/Val, particularly with issues of format and documentation errors or inconsistencies and unavailability of pre-launch data or analyses.

A similar analysis for MODIS on Terra (the first VIIRS-like instrument), yields similar lessons. Sensor performance and sensor interface issues once again dominated the Cal/Val program. For example: 1) Electronic and optical cross-talk (driven by focal plane and filter performance), 2) Optical path performance (dominated by A/B side mirror differences and polarization geometry), and 3) Calibration errors due to reflected solar energy contamination of the cold space calibration view. Most first-flight systems also suffer from incomplete sensor models, ultimately limited by the completeness of the pre-launch test program. The time required for the validation of the EDRs is dominated by the maturity of the science from a space platform for that product. When well-understood heritage algorithms are simply “tuned” for the new instrument characteristics and the sensor changes are minimal, the Cal/Val period is minimized. However, for cases where no heritage product exists and new science understanding must be developed post launch, the EDR validation is rarely complete in less than two years.

From these experiences we take the following lessons. First, prelaunch test and analysis focus is critical for building the foundation for eventual high-quality data products. This requires a strong pre-launch sensor data analysis team. Second, even with a strong pre-launch program, sensor engineering and expertise will be needed after launch, so team continuity from pre- to post-launch must be a key consideration. Third, during the initial stages of a post launch Cal/Val, sensor performance “features” will require compensation in the ground processing algorithm. In many cases large errors will have to be corrected before moderate or smaller errors can even be identified. This means that a rapid and affordable algorithm update process is needed to keep the Cal/Val team moving at top speed. Finally, extensive involvement from the user community in the early stages is of great benefit in assessing the operational viability of the products and prioritizing the implementation of corrections. This last point always carries some programmatic risk, but it is a risk well worth taking for the long term health of the program.

NPP Cal/Val Guiding Philosophy
As an outcome of studying the successes and challenges of heritage Cal/Val programs, we established the guiding philosophy for the NPP Cal/Val program. There are seven key points: 1) Sensor performance and characterization are the cornerstone of all data products. 2) Experience and resources from past operational and science missions should be fully exploited and incorporated into the NPP and NPOESS Cal/Val plans, 3) Customer and User satisfaction is achieved through their participation in the Cal/Val process, 4) Customer and User proficiency with the operational algorithms is essential to efficient Cal/Val and community buy-in of the data, 5) A quick, cost-effective, global view of performance can be achieved through early comparisons with data from other space-based sensors, global surface models, surface networks, and direct radiance assimilation comparisons, 6) Targeted campaigns and special studies should be planned and executed with knowledge of the global performance, and 7) Corrective actions must be handled with customer involvement and in accordance with established program priorities. These concepts form the foundation of the NPP Cal/Val program.

The NPP Cal/Val Program

Figure 1. Remote sensing mission data processing flow showing measurements and collection of data (RtoL) and the retrieval process (LtoR).

Phases of the Cal/Val Program
There are four primary phases of the NPP Cal/Val program. The pre-launch phase covers the period during which the sensors are in development, test, and integration, and the ground system is being built. The Early Orbit Check-out (EOC) covers the period of post-launch sensor activation, and typically lasts for 30 to 100 days. The Intensive Cal/Val (ICV) covers the period between activation and the declaration of operational readiness for each product. The duration of the ICV varies, but for a first-launch sensor it is typically an 18 month process, even in the absence of the need for new science development. Finally, the Long-Term Monitoring (LTM)
phase extends through the life of the sensors to ensure that data products continue to meet their performance requirements, anomalies are appropriately handled, and upgrades are implemented as needed. The specific activities during each of these phases are different for each data product type (RDR, SDR, and EDR). In the next section we present the NPP Cal/Val program overview for each phase of the program and for each product chain. The product chain threads may be understood as representing the basic sensor functionality (RDR), the calibratability of the sensor (SDR), and the functionality and performance of the retrieval algorithms (EDR).

The Pre-Launch Phase
For the RDR product chain, the pre-launch Cal/Val effort seeks to answer the question “What are the criteria that establish the sensor as a stable, configurable, and functioning instrument capable of meeting its performance requirements?” The activities include verifying operational modes and data formats, analyzing the ambient and thermal/vacuum performance measurements, tuning parameters such as gain and offsets, establishing air-to-vacuum and temperature sensitivities, and developing look-up-tables and sensor constants. Another important component during this phase is looking ahead and developing the post-launch sensor team. At the same time the SDR product chain team, in a closely related activity, seeks to answer the question “Do the SDR algorithms (in their operational implementation) capture how the sensor actually works as built? And is the product compliant with requirements?” The primary activities during this period focus on making pre-launch measurements to established standards (e.g. NIST), establishing the completeness of the sensor test program, developing sensor error budgets and populating them with as-built numbers, analyzing test data, developing look-up-tables and sensor constants and their documentation, participating in “fix-or-fly” decisions, and identifying any liens (due to as-built performance) that may alter the on-orbit operations concept of the sensor. Finally, there are important activities prior to launch for the EDR product chains. The EDR team works to establish the answer to the question “Are the algorithms (as implemented in the operational processing system) stable, tunable, well understood, and working with realistic sensor and system performance characteristics?” For the NPP system, proxy data are available from heritage instruments. These data are adjusted to reflect sensor differences and are used for assessing algorithm performance under both normal and stressing conditions. In addition, we run these data through the operational processing system to establish the robustness of the system. Synthetic data (data generated through modeling) are used to establish algorithm sensitivities. We also make, at this stage, an initial assessment of areas where more research, added on-orbit resources, post-launch campaigns, or other mitigation may be needed.

The Early Orbit Check-out Phase
The most fundamental question, answered in the early post-launch RDR verification, is “Is the sensor operating as it was tested on the ground?” This question is answered by analysis of engineering data (e.g. voltages, currents, and temperatures), telemetry data, and calibration data. Bringing about a positive response to this question may require instrument tuning or adjustment. This is also the activity that establishes instrument baseline performance and represents the beginning of on-orbit instrument trending. If the RDR verification does not verify that the sensor is operating as expected, then a sensor anomaly resolution activity is activated, drawing on the sensor development, systems engineering, and Cal/Val teams. RDR verification lays the foundation for a closely related activity: SDR verification and tuning.

The SDR verification during EOC answers the question “Taken together, are the RDR and SDR algorithms producing radiances that are reasonable (spectrally and radiometrically) and geolocated?” This initial assessment is intended to find large errors and systematic performance issues. The primary tools for this analysis are radiance comparisons with other space-borne sensors, model and analysis fields processed through radiative transfer models. This is also the prime opportunity for executing spacecraft maneuvers to position the sensors to observe more “pure” scenes such as deep space or well understood scenes such as the moon. After launch, radiance errors are most typically handled through modification of the SDR algorithm. In such a circumstance the SDR team will work very closely with the sensor anomaly team to establish a correction approach that is as faithful as possible to the established root cause of the unexpected behavior. Often the SDR verification activity is informed by the EDR verification activity, especially where the previously mentioned forms of radiance comparison are technically difficult or expensive.

The EDR verification activities in the EOC phase are designed to answer the question “Are the EDR algorithms functioning and valid over a subset of nominal conditions?” The first element of this activity is establishing that all inputs from the sensor are available and reasonable. In many cases the EDR algorithm must be activated or tuned using correlative analysis with independent data sets. The EDRs are compared with similar products from other space borne sensors or model/analysis fields to establish that the large scale patterns are reasonable. The Cal/Val team also looks at performance comparisons under selected conditions such as the sensor operating range (e.g. is the sensor performance varying with its orbital position/temperature?). Such an outcome will immediately be fed back to the SDR and RDR activities for investigation. The EDR verification activity also assesses the performance over a range of stressing environmental conditions(e.g. extreme surface temperature, temperature inversions, absorbing aerosols). This phase also marks the beginning of the generation of matchup data sets with other sources of correlative measurements such as ocean surface buoys, operational radiosondes, etc. For these matchup data sets, the associated RDR, SDR, EDR, calibration and engineering data will be captured so that the matchup dataset may be efficiently regenerated upon implementation of an SDR or EDR algorithm correction.

The Intensive Cal/Val Phase
Just as the EOC is intended to identify and correct or mitigate major sensor or system anomalies, the Intensive Cal/Val (ICV) phase is intended to identify and correct or mitigate moderate to minor sensor or system anomalies.

The primary focus of the RDR product chain is to establish the sensor stability by answering the question “Is the sensor and its calibration stable over the sensor’s range of operating conditions?” The answer to this question is established primarily through correlative analysis involving a host of system variables. These variables include position in orbit, seasonal variations, sensor operating state (and the operating states of neighboring sensors and transmitters), and the like. Performance is established through detailed analysis of telemetry and calibration data, correlation analysis, and early trend analysis. Unexpected findings during this activity may result in a modification of the sensor operations concept (e.g. table uploads, calibration frequencies, etc.)

Again, in a closely related activity, the SDR validation establishes the foundation for all future EDR work. The question to be answered by this activity is “Are the SDRs precisely geolocated, stable, and valid to expected levels (accuracy and precision) over conditions seen to date. There are a number of activities that support SDR validation, and only the primary ones are discussed here. First, the analyses that were begun during the EOC are continued and expanded. For example, analyses of accumulated comparisons with radiances and environmental products from other space based sensors and model fields will be continued. With the increasing comparison statistics, performance will be stratified, for example, in a zonal average global sense. Other statistical analysis techniques such as vicarious calibration approaches are viable at this stage, and will be used to provide a very reliable performance point for trending over the life of the sensor. Spacecraft maneuvers may continue into this phase as needed, although they may become difficult to schedule as some of the data begin to see operational use. Aircraft under-flights, with calibration targets independently calibrated to national standards may take place during this phase. Sensor error budgets established prior to launch are key to the success of the SDR validation, particularly as they may provide insight into unexpected sensor behaviors.

Finally, in recent years, a new approach to SDR validation has emerged through collaboration with the operational user community. Radiance assimilation into off-line instantiations of operational numerical weather prediction or analysis systems will be used to provide very sensitive indications of areas or conditions under which the sensor provided radiances deviate from expected values. An additional benefit of this interaction is that the operational users gain early familiarity with the new sensor data sets, their formats and performance attributes, allowing for earlier and more efficient operational use of the validated radiance data products.

Long-Term Monitoring Phase
At the conclusion of the ICV, all data products should be meeting performance expectations and should be viable for operational use. Product lines will likely reach this state at different times, depending on instrument performance and algorithm maturity at launch. We then will enter the Long-Term Monitoring (LTM) phase where the instrument and products are scrutinized for trends, finer adjustments may be made to the processing algorithms, and handling of sensor degradation becomes the primary focus.

During LTM, the RDRs (including telemetry, engineering, and calibration data) trending and analysis continue. The question of interest is “Is the sensor stable over seasons and is degradation as expected?” Mitigation approaches include tuning of the warning thresholds and recognizing changes in sensor operating state. As the sensors age, modification of their operations concepts may be required to maintain performance. These may include more frequent table uploads, and adjustments to operating set points.

For the SDR product chain, the question during LTM is “Are the SDR algorithms and supporting look-up tables and sensor constants optimized as the sensor ages?” Continuous tracking of radiance performance (in addition to the RDR trending) is central to answering this question. During this phase mitigation approaches will have to be developed to handle changes to redundant side (A/B side) subsystems as necessary. Typical issues also include degradation of sensor electronics, calibration targets, and optical surfaces. In some cases complete loss of a channel has occurred. Mitigation of these performance changes ranges from simple updates to Look-Up Tables (LUTs) to a reformulation of the SDR algorithm. These adjustments are most critical for the long term utility of the NPP data. Issues uncovered and mitigated in the SDR production are almost always accompanied by adjustments to EDR product chains as well.

The question “Are the EDR products valid over the full range of conditions and operationally viable?” dominates the EDR product chain team during the long term monitoring phase. Continued analysis of accumulated comparisons with both space borne sensor and correlative data sets will be used to validate the data products under stressing and important conditions, even if such conditions are not uncommon. In some cases special campaigns for poorly understood conditions may be needed, in accordance with program priorities. Of course the most fundamental activity will revolve around adapting EDR products to accommodate sensor channel loss or performance degradation.

The specifics of the activities during each Cal/Val phase, and for each product chain are captured in individual Calibration and Validation plans, but all follow the general structure captured here.

The NPP Cal/Val Teams
An examination of the activities described in the previous sections will reveal that the expertise required to execute a successful Cal/Val varies with product chain and phase of the program. Figure 2 is a graphical depiction of this concept.

In the upper left hand corner of this matrix the required expertise is focused on the sensor performance and engineering considerations. Activities in the lower right quadrant are more focused on the environmental data side, required expertise in the physics of the earth environment and an understanding of how the EDRs are to be used to support operational mission. In other words, the needed expertise shifts from sensor engineering (typically with a strong sensor developer presence) to Government customers over time and product chain. The NPP Cal/Val teams have been constructed to accommodate these varying expertise requirements.

The NPOESS program has two components; the Integrated Program Office (IPO), and the Prime Contractor. From the Cal/Val perspective there are several important considerations that flow from this structure. First, the prime contractor holds most of the sensor development contracts and the systems engineering responsibility. In addition, the prime contractor is responsible for the development of the ground processing system. The prime contractor’s performance requirements are captured in the contract they have signed with the Integrated Program Office.

The IPO, on the other hand, is the primary interface with the Government customer/user community, and as such is well positioned to work with the users to ensure program priorities are achieved. The program commitments to the customers are captured in the governing requirements document, the IORD. The IPO also has the ability to draw upon technical expertise from within the Government and academia far more readily than the prime contractor. With this construct in mind, Cal/Val teams were created to best draw upon the resources available to the IPO and the Prime Contractor.

Figure 2. Expertise required during Cal/Val as a function of time and data products.

The RDR & SDR Cal/Val Teams
The RDR and SDR Cal/Val efforts are led by the prime contractor. Their responsibilities include development of the RDR and SDR algorithms and LUTs, performance verification of the sensors, and post-launch calibration and validation of the SDR products. To support this activity, they will carry a core team for each sensor, consisting of members of the sensor development team, the algorithm developers and the calibration specialists. The IPO will augment this contractor team with experts from government and academia, especially when such experts bring strong heritage expertise. In the case of the VIIRS instrument, the IPO has worked closely with NASA to bring the lessons learned from the Moderate-resolution Imaging Spectroradiometer (MODIS) calibration team to the VIIRS SDR team. For each sensor, the Government team is lead by an identified sensor science lead. The sensor science lead is responsible for leading the Government SDR team and coordinating their activities with the prime contractor. The RDR and SDR validation programs are captured in sensor specific calibration and validation plans, with the detailed task descriptions and responsibilities further enumerated in an integrated task network. This task network is the management tool that the leads will use to coordinate the work of the team, adapting as necessary as understanding of sensor performance and issues evolves.

The EDR Cal/Val Teams
The EDR Cal/Val activities are led by the IPO team, which is organized by discipline area. The IPO has six environmental product teams: imagery and cloud mask products, ocean surface products, land surface products, atmosphere products (cloud and aerosol properties), ozone, and sounder products. For each product team, the IPO sought leadership from a center of expertise. Each of these team leads has put together a plan and a supporting team (from across the stakeholder agencies) to execute their Cal/Val program. The IPO provides the resources for these efforts and coordinates across the discipline area teams. Examples of coordination activities include optimizing any field campaigns for maximum benefit across teams and developing an infrastructure that supports all of the discipline teams.

The imagery and cloud mask team is led by the Air Force Weather Agency and The Aerospace Corporation because they are the most involved users of the imagery data products.

The ocean surface product (sea surface temperature and ocean color/chlorophyll) team is led by the Naval Research Laboratory and the Naval Oceanographic Office, both located at Stennis Space Center. They were asked to lead the oceans effort because of their resident technical expertise and because their operational missions are most sensitive to the quality of these ocean products.

The land surface products team leadership is provided by the NOAA National Climatic Data Center (NCDC) in Asheville, NC. NCDC was selected because of their in-house technical expertise, their working partnerships with other stakeholders, and their wealth of independent data sets.

The sounder product team is led by NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) Center for Satellite Applications and Research (STAR) because of the close connection between the NOAA operational weather mission and the sounder product quality.

The ozone products from the nadir instrument will be led by NOAA/NESDIS STAR, in close cooperation with the NASA team leading the validation of the ozone limb sensor products.

Finally, the atmospheric products, which include cloud properties and aerosol properties, will be led by NASA Goddard Space Flight Center. This is the only product team that does not have direct ties to operational missions. This is due to the fact that this subset of the EDRs does not have operational heritage, but does have strong heritage from within the NASA EOS program, and in particular, the MODIS science team.

The Clouds and the Earth’s Radiative Energy System (CERES) sensor is also flying on NPP, but the NASA Langley Research Center Science Directorate owns the Cal/Val responsibilities under the terms of the sensor manifest agreement Every effort will be made to coordinate with the Langley team avail them of the infrastructure that supports the rest of the Cal/Val teams.

Correlative Data Sets
The SDR and EDR Cal/Val teams have identified an extensive preliminary list of correlative data sets that are available in the post-launch Cal/Val effort. These data sets are generally of four types: space borne sensors, global fields & models, airborne sensors, networks and deployables and currently include over 32 space-based sensors, 6 individual global fields/models, 12 separate ground based networks and 13 separate deployable/airborne data sources.

The NPP Cal/Val Support Infrastructure

An important benefit of embracing a community based Cal/Val program is in bringing not just heritage experience, but also heritage tools to benefit the NPP program. This approach provides savings in both development cost and tool verification. However, there are some functions that are best done with centralized resources, to establish a common infrastructure for the benefit of all of the Cal/Val teams. That common infrastructure is described here. The infrastructure is called the Government Resource for Algorithm Verification, Integration, Test and Evaluation (GRAVITE). GRAVITE has four main components, the technical library, the central processing and distribution capability, the software repository, and a whole system triage tool.

The Technical Library
The NPP system produces 24 EDRs which are supported by 70 algorithms implemented in the ground system (not including CERES products, which are developed and maintained by NASA Langley). The documentation for this complex system is extensive and development/update cycles for the documentation are not, in most cases, synchronized. The technical reference library is intended to be the primary resource for the accurate information, available in a timely manner to support rapid post-launch Cal/Val activities. The goal is to use graphical representations of the system to allow the user to rapidly identify the detailed information needed – whether that is format information, algorithm flow diagrams, or sensor descriptions.

Ozone Mapping and Profiler Suite (OMPS) will measure the concentration of ozone, which keeps the sun’s ultraviolet radiation from striking the Earth, in the atmosphere and how its concentration varies with altitude. (Photo Courtesy of Ball Aerospace)

Tied in to the technical library is a repository of all prelaunch instrument test data and telemetry. This repository also includes instrument test procedures, test logs, and analysis reports. These items are the basis for pre-launch instrument performance assessments made by the SDR Cal/Val team that inform the sensor requirements sell-off process. A set of tools that allows querying of the test data by telemetry parameters (e.g. instrument state or optical bench temperature) is also included for convenience in searching the data.

The Central Processing and Data Distribution
The central processing and data distribution capability is located within the NOAA facility that will process NPP data operationally. These assets support the collection, storage distribution and reformatting of mission, ancillary, auxiliary and correlative data to support the geographically distributed Cal/Val teams. The central processing capability is intended to perform functions that either benefit multiple Cal/Val teams (e.g. SDR work) or where reduction in data flow results (e.g. matchup generation).

Software Repository
A shared access software repository is provided which contains algorithm processing modules from the IDPS operational code, tools to run these modules on a “scientist friendly” platform such as Linux, and a platform for sharing analysis software tools, all with configuration management and change tracking. This capability is especially important for managing, vetting, testing, and verifying any changes to the operational code that may be proposed by the Cal/Val team.

System Visualization Tools
Heritage Cal/Val programs have demonstrated that anomalies observed are often traceable to sensor geometry relative to the satellite, earth, sun or other satellites. The ability of the Cal/Val team to visualize these relationships, and correlate them to the mission data and telemetry is the key to rapid issue resolution. The infrastructure team is developing such a capability and expects to demonstrate this tool to the Cal/Val team 6-8 months prior to launch. The software will be freely distributed to the Cal/Val team, and will run in a desktop environment. In addition, these tools will be available to Cal/Val scientists visiting the IPO.

Conclusions

The NPP program is the pathfinder for the NPOESS program in many ways, including development and maturation of the Calibration and Validation Program. The Integrated Program Office has put together discipline teams, lead by internationally recognized experts, to plan and execute the Cal/Val. This planning takes as a basis the most effective heritage approaches and tools, but updates these in light of availability of data sources, known sensor performance and issues, recent scientific developments. The phases of the Cal/Val program have been identified and are designed to optimize the impact of the available resources. The details of these plans are captured in 11 volumes, which will be released to the broader community in 2010.

Karen M. St. Germain (SM‘02) received the BS degree in electrical engineering from Union College, Schenectady, NY in 1987, and the Ph.D. degree from the University of Massachusetts, Amherst, in 1993. She joined NOAA in 2004 and is currently Chief of the Data Products Division at the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Integrated Program Office. NPOESS is the next generation operational weather and environment satellite system supporting U.S. National civilian and defense weather prediction and environmental observation. Dr. St. Germain is responsible for demonstrating the scientific integrity of the data processing algorithms, pre- and post-launch sensor calibration and data product validation for the nine NPOESS sensors and the 38 operational earth, atmosphere and space environmental data products. Dr. St. Germain has been a member of the IEEE Geoscience and Remote Sensing Society since 1988. She served as an associate editor of the IEEE GRSS Newsletter from 1994 to 1996, and was elected to the AdCom in 1997. She served as the Membership Chairman from 1997 to 1998, as the Vice President for Meetings and Symposia from 1998 to 2001, and currently serves as the Vice President for Operations and Finance. Dr. St. Germain was Co-Chairman of the Technical Program for IGARSS 2000. She served on the U.S. National Academy of Sciences National Research Council Committee on Radio Frequencies (CORF) from 2000–2007 and served as the chairman from 2005–2007. Dr. St. Germain is the general co-chair of IGARSS 2010 and hopes to see you all in Hawaii.

Reprinted from NASA

NASA Jet Propulsion Laboratory research scientist Richard Gross has computed how Earth’s rotation should have changed as a result of the Feb. 27 quake. Using a complex model, he and fellow scientists came up with a preliminary calculation that the quake should have shortened the length of an Earth day by about 1.26 microseconds (a microsecond is one millionth of a second).

Perhaps more impressive is how much the quake shifted Earth’s axis. Gross calculates the quake should have moved Earth’s figure axis (the axis about which Earth’s mass is balanced) by 2.7 milliarcseconds (about 8 centimeters, or 3 inches). Earth’s figure axis is not the same as its north-south axis; they are offset by about 10 meters (about 33 feet).

By comparison, Gross said the same model estimated the 2004 magnitude 9.1 Sumatran earthquake should have shortened the length of day by 6.8 microseconds and shifted Earth’s axis by 2.32 milliarcseconds (about 7 centimeters, or 2.76 inches).

Gross said that even though the Chilean earthquake is much smaller than the Sumatran quake, it is predicted to have changed the position of the figure axis by a bit more for two reasons. First, unlike the 2004 Sumatran earthquake, which was located near the equator, the 2010 Chilean earthquake was located in Earth’s mid-latitudes, which makes it more effective in shifting Earth’s figure axis. Second, the fault responsible for the 2010 Chiliean earthquake dips into Earth at a slightly steeper angle than does the fault responsible for the 2004 Sumatran earthquake. This makes the Chile fault more effective in moving Earth’s mass vertically and hence more effective in shifting Earth’s figure axis.

Gross said the Chile predictions will likely change as data on the quake are further refined.

Alan Buis (818) 354-0474
Jet Propulsion Laboratory, Pasadena, Calif.

The 8.8 magnitude earthquake that wreaked havoc on Central Chile on February 27, 2010 also generated a tsunami which crossed the entire Pacific Ocean, reports the Intergovernmental Oceanographic Commission (IOC) of UNESCO.

The near-real time sea level monitoring system registered the tsunami on Galapagos (1.0 m in Santa Cruz) to Marquise Islands (1.8 m) and from Malibu (1.4 m) to Valparaiso (1.3 m), from Hiva oa Marquesas (1,29 m) to Hanasaki, Hokkaidao, Japan (0.82 m). Worst hit was the area around Talcahuano, Chile with a 2.34 m.

The Pacific Tsunami Warning System (PTWS) enabled emergency response agencies to warn locals about the risk of tsunami and order evacuations. This is the first real ocean-wide test of a system that was put in place nearly 50 years ago by UNESCO’s Member States through its Intergovernmental Oceanographic Commission (IOC).

Peter Koltermann, Head of IOC’s Tsunami Unit, said: “This tsunami is another distressing example of our vulnerability at the coasts to natural disasters. We need to further enhance greater vigilance and preparedness. High-risk coastal communities, where there is very little time, maybe minutes, for populations to receive any warning, have too be strengthened by urgently continuing to develop and implement evacuation measures.”

The Pacific Tsunami Warning Center in Hawaii, USA relayed and shared the following timeline: The major tsunami off Concepcion, Chile on Feb 27, 06:34 UTC had a magnitude of 8.8 Mw. It issued a regional warning at 06:46. The first sea level measurements at Valparaiso with 1.3 m and Talcahuano with 2.3 m confirmed a tsunami had been generated. PTWC revised and extended the affected region at 09:47. At 10:45 UTC the PTWC warned of a Pacific wide tsunami and subsequent hourly messages expanded the warning to several areas in the Pacific Ocean. Every hour the system coordinated by UNESCO/IOC and operated by national agencies kept updating the established tsunami warning focal points and media accessing the system.

The Pacific Tsunami Warning System (PTWS) was established when a 9.5 magnitude earthquake on May 22, 1960 off Chile on the Pacific Rim generated a tsunami heavily affecting populations from Hilo in Hawaii to the Sanriku coast of Japan. PTWS has operated since 1965 under the mandate of UNESCO/IOC. In the aftermath of the Indian Ocean tsunami on Dec 26, 2004, building on this Pacific experience, UNESCO/IOC established similar systems for the Indian Ocean, the Caribbean and the seas around Europe to ensure a global cover for tsunami hazards.

The President’s FY2011 budget contains a major restructuring of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) in order to put the critical program on a more sustainable pathway toward success. The satellite system is a national priority – essential to meeting both civil and military weather-forecasting, storm-tracking, and climate-monitoring requirements. However, the program is behind schedule, over budget, and under-performing. Independent reports and an administration task force have concluded that the current program cannot be successfully executed with the current management structure, and with the current budget structure. These challenges originate in large part because of a combination of management deficiencies that result from conflicting perspectives and priorities among the three agencies who manage the program. Serious lapses in capabilities loom as a result.

Background

NPOESS is a tri-agency program with the Department of Commerce (specifically the National Oceanic and Atmospheric Administration, or NOAA), the Department of Defense (DOD, specifically the Air Force), and the National Aeronautics and Space Administration (NASA) designed to merge the civil and defense weather satellite programs in order to reduce costs and to provide global weather and climate coverage with improved capabilities above the current system.

In 2002, the NPOESS program was estimated to cost approximately $6.5B (for development and operations through FY2018) and consisted of an initial NASA satellite to test the new sensors (the NPOESS Preparatory Project – NPP – to be launched in early 2006) and six NPOESS platforms in three orbits, the first of which (C-1) was to be launched in early 2009. The program encountered numerous technical and management challenges, which led to restructuring of the NPOESS program in 2006 due to cost over-runs that triggered Congressionally-mandated recertification. The restructured program reduced the scale of the program from six main satellites (in three orbits) to four satellites (in two orbits). (The U.S. will rely on European satellites for operational weather observations from the remaining orbit.) The NPP launch has been delayed to 2011, and the launch of the first NPOESS platform (C-1) was expected to be in late 2014. (These would each be delays of five years from the original plan.) At that time the new life-cycle cost estimate (through FY2024 due to delays) was approximately $12B for this reduced capability. The current official baseline life-cycle cost estimate is approximately $13.9B.

A new direction for ensuring continuity of polar-orbiting satellite measurements:

After reviewing options, including those suggested by an Independent Review Team (IRT) and Congressional Committees, the President’s FY2011 budget takes significant new steps. Today the White House is announcing that NOAA and the Air Force will no longer continue to jointly procure the polar-orbiting satellite system called NPOESS. This decision is in the best interest of the American public to preserve critical weather and climate observations into the future.

• The three agencies (DOD, NOAA and NASA) have and will continue to partner to ensure a successful way forward for the respective programs, while utilizing international partnerships to sustain and enhance weather and climate observation from space.

• The major challenge of NPOESS was jointly executing the program between three agencies of different size with divergent objectives and different acquisition procedures. The new system will resolve this challenge by splitting the procurements. NOAA and NASA will take primary responsibility for the afternoon orbit, and DOD will take primary responsibility for the morning orbit. The agencies will continue to partner in those areas that have been successful in the past, such as a shared ground system. The restructured programs will also eliminate the NPOESS tri-agency structure that that has made management and oversight difficult, contributing to the poor performance of the program.

• NOAA and the Air Force have already begun to move into a transition period during which the current joint procurement will end. A detailed plan for this transition period will be available in a few weeks. The agencies will continue a successful relationship that that they have developed for their polar and geostationary satellite programs to date. NOAA’s portion will notionally be named the “Joint Polar Satellite System” (JPSS) and will consist of platforms based on the NPP satellite.

• In addition, these Agencies have a strong partnership with Europe through the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) that will continue to be a cornerstone of our polar-orbiting constellation, and will ensure our ability to provide continuous measurements.

• These changes to the NPOESS program will better ensure continuity of crucial civil climate and weather data in the future. Decisions on future satellite programs will be made to ensure the best plan for continuity of data.

• While the Air Force continues to have remaining Defense Meteorological Satellite Program (DMSP) polar-orbiting satellites available for launch for the next few years, NOAA launched its final polar-orbiting satellite in February 2009. Given that weather forecasters and climate scientists rely on the data from NOAA’s current on-orbit assets, efforts will focus development of the first of the JPSS platforms on ensuring both short- and long-term continuity in crucial climate and weather data.

• NASA’s role in the restructured program will be modeled after the procurement structure of the successful POES and GOES programs, where NASA and NOAA have a long and effective partnership. Work is proceeding rapidly with NOAA to establish a JPSS program at NASA’s Goddard Space Flight Center (GSFC).

- The NASA developed and operating Earth Observing System (EOS) Aqua satellite and ground system are very similar in scope and magnitude to the proposed JPSS program.
- NOAA and NASA will strive to ensure that all current NPOESS requirements are met on the most rapid practicable schedule without reducing system capabilities.
- NASA program and project management practices have been refined over decades of experience developing and acquiring space systems and NASA anticipates applying its current practices to JPSS. NASA program and project management processes will include thorough and ongoing review and oversight of project progress. Cost-estimates will be produced at or close to the 80% confidence level.

• DOD remains committed to a partnership with NOAA in preserving the Nation’s weather and climate sensing capability. For the morning orbit, the current DOD plan for deploying DMSP satellites ensures continued weather observation capability. The availability of DMSP satellites supports a short analysis (in cooperation with the partner agencies) of DOD requirements for the morning orbit and solutions with the start of a restructured program in the 4th quarter of fiscal year 2011. While this study is being conducted, DOD will fully support NOAA’s needs to ensure continuity of data in the afternoon orbit by transitioning appropriate and relevant activities from the current NPOESS effort.

• We expect much of the work being conducted by Northrop-Grumman and their subcontracts will be critical to ensuring continuity of weather observation in the afternoon orbit. DOD will work closely with the civil partners to ensure the relevant efforts continue productively and efficiently, and ensure the requirements of the national weather and climate communities are taken into consideration in building the resultant program for the morning orbit.

Additional Points:

• Observations of the Earth’s environment, both from space and on the surface, are a priority for this Administration. Information about the planet is vital to our ability to plan, predict, respond, and protect our citizens and infrastructure. The nation’s system of polar-orbiting environmental satellites is essential for supporting climate research as well as operational weather and storm forecasting for civil, military, and international partners.

• For this reason, maintaining a capable, operational environmental satellite system is vitally important, and a primary focus of this effort remains on the continuity of the polar-orbiting satellite data that system users – both civil and defense – have come to rely on.

• The NPOESS program was designed to deliver improved capabilities above the current system of civil and defense weather satellites. The U.S. leadership in this area over the last three decades will continue into the future. The partner agencies (DOD, NOAA and NASA) are committed to maintaining collaborations towards the goal of continuity of earth observations from space, and minimizing – if not eliminating – potential gaps in data.

• The NPOESS program has experienced several challenges to date, including schedule delays and cost increases. Recent reports have illustrated the difficulties the program has experienced, and the Administration has closely examined the findings in these reports.

• Since August, an Executive Office of the President (EOP) Task Force (with participation from OSTP, OMB and NSC), working in close cooperation with the partner agencies, has been investigating various options for how to go forward with the NPOESS program.

• The Task Force performed a careful and in-depth analysis of NPOESS management challenges, agency requirements, and potential options for strengthening the program. A primary goal of the interagency discussions has been to provide a more robust operational satellite system, with specific attention on the need for ensuring continuity in the environmental measurements.

• Although challenges remain, development of NPOESS assets has continued through this process. Significant progress has been made with the NPP, now with a realistic and achievable launch date of September 2011. A key instrument, the Visible Infrared Imager Radiometer Suite (VIIRS), has been tested and shipped from the developers to NPP and can now be integrated onto the spacecraft. The Ozone Mapping and Profiler Suite (OMPS) has been developed, integrated onto the NPP spacecraft, and tested for flight. The Advanced Technology Microwave Sounder (ATMS) has been integrated and fully tested for flight. NOAA and NASA have taken advantage of the NPP opportunity to add the Clouds and the Earth’s Radiant Energy System (CERES) instrument to NPP. This instrument has been integrated onto the spacecraft and tested for flight, thus ensuring the continuity of this critical data set beyond the NASA EOS (Terra and Aqua) missions.

• Partnerships are the key to our ability to provide continuous polar-orbiting measurements. NOAA, NASA, and the DOD/Air Force have had a very productive relationship in polar observations; sharing data, coordinating user needs, and operating satellites. This cooperative relationship is essential and will continue for years to come. Likewise, partnerships with Europe through EUMETSAT will continue to be a strong part of our polar-orbiting constellation.

The Open Geospatial Consortium, Inc. (OGC®) announces a Call for Participation (CFP) in Phase 3 of the GEOSS (Global Earth Observation System of Systems) Architecture Implementation Pilot (AIP) issued by the Group on Earth Observations (GEO). The CFP documents are available at: http://earthobservations.org/geoss_call_aip.shtml.

AIP-3 will build on previous project phases and is coordinated with other GEO Tasks. Specific areas of emphasis for AIP-3 include increasing the capacity for GEOSS to support Societal Benefit Areas; building on the AIP Service Architecture and the GEOSS Common Infrastructure; and increasing availability of data in GEOSS in accordance with the GEOSS Data Sharing Guidelines. AIP-3 will be conducted in 2010 with support to the Earth Observation Summit, November 2010.

The AIP-3 CFP invites GEO Members and Participating Organizations to participate in activities involving: registering components and services; testing of services; and participating in refinement of Societal Benefit Area scenarios to guide testing, demonstrations and operations of the identified interoperable services.

CFP responses are requested by 3 March 2010. Organizations responding to the CFP should plan to attend the kickoff workshop to begin development of AIP-3 to be held 11-12 March 2010, at the European Space Agency facility in Frascati, Italy.

Discussion and clarification of the CFP will be the topic of several teleconferences before the Kickoff Workshop. Agenda and logistics for these teleconferences are posted at http://www.ogcnetwork.net/AIPtelecons.

The point of contact for the AIP task is George Percivall percivall@opengeospatial.org.

The OGC® is an international consortium of more than 385 companies, government agencies, research organizations, and universities participating in a consensus process to develop publicly available geospatial standards. OGC Standards empower technology developers to make geospatial information and services accessible and useful with any application that needs to be geospatially enabled. Visit the OGC website at http://www.opengeospatial.org.

GEO (Group on Earth Observations) is a voluntary partnership of 124 governments and international organizations, launched in response to calls for action by the 2002 World Summit on Sustainable Development and by the G8 (Group of Eight) leading industrialized countries. GEO is coordinating efforts to build a Global Earth Observation System of Systems, or GEOSS. See http://earthobservations.org/about_geo.shtml.

NASA reprint from Jan 28, 2010

In response to the disaster in Haiti on Jan. 12, NASA has added a series of science overflights of earthquake faults in Haiti and the Dominican Republic on the island of Hispaniola to a previously scheduled three-week airborne radar campaign to Central America.

NASA’s Uninhabited Aerial Vehicle Synthetic Aperture Radar, or UAVSAR, left NASA’s Dryden Flight Research Center in Edwards, Calif., on Jan. 25 aboard a modified NASA Gulfstream III aircraft.

During its trek to Central America, which will run through mid-February, the repeat-pass L-band wavelength radar, developed by NASA’s Jet Propulsion Laboratory, Pasadena, Calif., will study the structure of tropical forests; monitor volcanic deformation and volcano processes; and examine Mayan archeology sites.

After the Haitian earthquake, NASA managers added additional science objectives that will allow UAVSAR’s unique observational capabilities to study geologic processes in Hispaniola following the earthquake.

UAVSAR’s ability to provide rapid access to regions of interest, short repeat flight intervals, high resolution and its variable viewing geometry make it a powerful tool for studying ongoing Earth processes.

“UAVSAR will allow us to image deformations of Earth’s surface and other changes associated with post-Haiti earthquake geologic processes, such as aftershocks, earthquakes that might be triggered by the main earthquake farther down the fault line, and the potential for landslides,” said JPL’s Paul Lundgren, the principal investigator for the Hispaniola overflights.

2. Enriquillo-Plantain Garden fault zone runs across Haiti. Fault system in the vicinity of the 12 January 2010 quake, epicenter is the orange square. Enriquillo-Plantain Garden Strike-Slip Fault Zone: A Major Seismic Hazard Affecting Dominican Republic, Haiti And Jamaica.

“Because of Hispaniola’s complex tectonic setting, there is an interest in determining if the earthquake in Haiti might trigger other earthquakes at some unknown point in the future, either along adjacent sections of the Enriquillo-Plantain Garden fault that was responsible for the main earthquake, or on other faults in northern Hispaniola, such as the Septentrional fault.”

Lundgren says these upcoming flights, and others NASA will conduct in the coming weeks, months and years, will help scientists better assess the geophysical processes associated with earthquakes along large faults and better understand the risks.

UAVSAR uses a technique called interferometric synthetic aperture radar, or InSAR, that sends pulses of microwave energy from the aircraft to the ground to detect and measure very subtle deformations in Earth’s surface, such as those caused by earthquakes, volcanoes, landslides and glacier movements. Flying at a nominal altitude of 12,500 meters (41,000 feet), the radar, located in a pod under the aircraft’s belly, collects data over a selected region.

It then flies over the same region again, minutes to months later, using the aircraft’s advanced navigation system to precisely fly over the same path to an accuracy of within 5 meters (16.5 feet). By comparing these camera-like images, interferograms are formed that have encoded the surface deformation, from which scientists can measure the slow surface deformations involved with the buildup and release of strain along earthquake faults.

Since November of 2009, JPL scientists have collected data gathered on a number of Gulfstream III flights over California’s San Andreas fault and other major California earthquake faults, a process that will be repeated about every six months for the next several years. From such data, scientists will create 3-D maps for regions of interest.

Flight plans call for multiple observations of the Hispaniola faults this week and in early to mid-February. Subsequent flights may be added based on events in Haiti and aircraft availability.

3. Major Tectonic Boundaries: Subduction Zones – purple, Ridges – red and Transform Faults – green.

After processing, NASA will make the UAVSAR imagery available to the public through the JPL UAVSAR website and the Alaska Satellite Facility Distributed Active Archive Center. The initial data will be available in several weeks.

Lundgren said the Dominican Republic flights over the Septentrional fault will provide scientists with a baseline set of radar imagery in the event of future earthquakes there.

Such observations, combined with post-event radar imagery, will allow scientists to measure ground deformation at the time of the earthquakes to determine how slip on the faults is distributed and also to monitor longer-term motions after the earthquakes to learn more about fault zone properties.

The UAVSAR data could also be used to pinpoint exactly which part of the fault slipped during an earthquake, data that can be used by rescue and damage assessment officials to better estimate what areas might be most affected.

¹ US Geological Survey Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD.
² ASRC Research & Technology Solutions (ARTS), contractor to the US Geological Survey EROS Center. Work performed under USGS contract 08HQCN0007, Sioux Falls, SD.

Figure 1. Relative production as a fraction of the high 2005/06 production year in Zimbabwe. Actual Σv production estimates (tons) for each production year are shown on top and PECAD production figures are shown at right. The 2006/07 production estimate is shown with an error estimate included.

Introduction

The recent global food crisis brought food security issues to the forefront of the world’s consciousness. The impacts of the crisis have been felt most seriously in third world countries. According to the International Monetary Fund, food prices increased 43 percent between March 2007 and March 2008. While developed countries are often able to mitigate impacts of such crises, developing countries are most affected and take much longer to recover. The poorest populations spend a larger proportion of their income on basic food supplies, making them the most vulnerable to increased prices. A recent US Agency for International Development (USAID) report stated that nearly 1 billion people, approximately one sixth of the world’s population, live on less than $1 per day and, of these, 162 million survive on less than $.50 per day.

In addition to market-driven impacts on food security, many of those at risk rely upon adequate weather conditions for subsistence agricultural activities. Subsistence agriculture, a form of farming where nearly all commodities produced are consumed by farmers and their families, persists in many parts of the world and is especially widespread in sub-Saharan Africa. The combination of high food prices and poor growing season conditions can be devastating for this segment of the world’s population. Therefore, there is a profound need to accurately monitor growing season conditions that impact food security in the developing world.

Background

Scientists with the U.S. Geological Survey (USGS) are part of a network of both private and government institutions that monitor food security in many of the poorest nations in the world. The Famine Early Warning Systems Network (FEWS NET) is a USAID-funded activity that collaborates with international, regional, and national partners to provide timely and rigorous early warning and vulnerability information on emerging and evolving food security issues. Currently, FEWS NET professionals in Africa, Central America, Haiti, Afghanistan and the United States monitor and analyze relevant data and information in terms of its impacts on livelihoods and markets to identify potential threats to food security.

FEWS NET uses a suite of communications and decision support products to help decision makers act to mitigate food insecurity. These products include monthly food security updates, regular food security outlooks and alerts, as well as briefings and support to contingency and response planning efforts.

Figure 2. Σv (left column) and Σv anomalies (right column) for seven growing seasons, 2001/02 through 2007/08, ranked from worst to best based on PECAD production estimates for Zimbabwe.

Need for Remote Sensing

FEWS NET relies heavily upon its national and regional offices in sub-Saharan Africa to monitor aspects of food security. However, the broad scope of information that these offices are responsible for analyzing and the large areas which are being monitored drive the need for tools such as remote sensing to provide additional data for food security decision making.

Remote sensing provides the ability to monitor large areas on regular intervals. Satellite-based data and modeled derivatives are used in combination with ground-based information to better assess potential impacts to the food supply system. The USGS Earth Resources Observation and Science (EROS) Center, in collaboration with other FEWS NET implementing partners (NASA, NOAA, University of California, Santa Barbara), provides a number of remotely sensed inputs to the FEWS NET decision making process.

Agricultural Monitoring Products

Some of the most widely used remotely sensed products for agricultural monitoring are precipitation, crop water requirements, and vegetation indices. Precipitation is monitored primarily through the use of satellite-based rainfall estimates (RFEs) that augment the sparse observational network of rain gauge stations found in many FEWS NET countries. RFEs provide daily estimates at a gridded cell size where each cell represents a 0.1 by 0.1 degree area on the ground. These data are useful for large area precipitation monitoring and are also used as inputs to crop performance models.

One such crop model, the water requirement satisfaction index (WRSI), is based on the water supply and demand a crop experiences during a growing season. It is a ratio of seasonal evapotranspiration to the seasonal crop water requirement. The water requirements of specific crops are adjusted for various growth stages and are compared to the available moisture (incoming precipitation and existing soil moisture). Output from this model is used extensively to monitor both cropland and pasture conditions, and to assess potential food security impacts.

The normalized difference vegetation index (NDVI) is one of the original remotely sensed data types used by FEWS NET more than 20 years ago, and still used today. NDVI, calculated by measuring the intensity of visible and near-infrared light reflected by the land surface and “sensed” by satellites, quantifies the amount and vigor of vegetation at the land surface. Daily NDVI measures are combined into multi-day composites that portray the Earth’s vegetation condition and identify areas where plants are flourishing and where they may be under stress.

Case Studies

These agricultural monitoring products are used on a routine basis for operational monitoring of near-term factors that may impact food security. On occasion there is a need to go beyond our operational monitoring efforts and address specific questions that respond to specific food security questions. In the remainder of this article, we highlight two case studies that illustrate the use of NDVI data for analyzing both maize production and winter wheat yields. Each of these targeted analyses provided timely information that had a significant impact on food security decision making.

Zimbabwe

Introduction

Responding to a request by USAID, we analyzed remote sensing data that helped assess maize harvest prospects for Zimbabwe. Maize is the most widely grown cereal crop in Zimbabwe with lesser amounts of wheat, sorghum, and millet also being grown. We used an NDVI-based metric, sum v (Σv), that relies on measures of vegetation condition throughout the growing season to assess the likely production outcome. The initial analysis, for the 2006/07 growing season, has been replicated each year since.

Methods

The Σv method relies on the finding that late season NDVI correlated well with US Department of Agriculture (USDA) Production Estimates and Crop Assessment Division (PECAD) production estimates for those years prior to the 2006/07 season. Therefore we could use measurements of late season NDVI for a given year to estimate production numbers. We used Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data for the years 2000 through 2007. In order to minimize the influence of non-agricultural lands on Σv, we applied a mask to the NDVI time series using a cultivated lands map. We were not able to specifically isolate maize within the agricultural zone, but the fact that maize is the major cereal crop gives confidence that monitoring these areas will be a good surrogate for assessing overall food security. The NDVI time series for agricultural lands were adjusted based on varied onset of season times determined from rainfall inputs. The onset-adjusted NDVI values were set to zero to represent the beginning of the growing season. Once adjusted, we ignore the first ten 16-day periods of the time series, then accumulate NDVI over the next two 16-day periods. It is this sum of late season NDVI, or Σv, that can be used to estimate production at the national level. The onset of season or planting date is a critical component of this analysis; therefore we have recently incorporated more ground-based information for this parameter. FEWS NET field staff in southern Africa have been instrumental in making these improvements to the modeling effort and have provided extensive input to final results.

Results

Figure 3. Annual maximum NDVI and CFSAM yield figures ranked from best to worst for irrigated areas of Afghanistan. The 2008 maximum NDVI ranks worst in the series. The yield estimate for 2008 is based on the regression of maximum NDVI and historical yield figures.

For the 2006/07 season in Zimbabwe, the Σv method resulted in an estimate of 688,000 tons of maize (Figure 1). Results from the 2007/08 season showed a dramatically reduced production figure on the order of 480,000 tons. The reduction was due largely to a combination of dry conditions during critical periods of the growing season and inadequate supplies of seed and fertilizer. The effects could be seen in the Σv and Σv anomalies that show the 2007/08 season ranks as the worst among the years studied (Figure 2).

The analysis for the 2008/09 season was perhaps the most complex. The season was characterized by highly variable rainfall that may have prompted early planting in some areas and late planting in others. Our production estimate seems to fall between the USDA Foreign Agricultural Service estimate (based on low yields, and planted area significantly reduced from the previous year) and the Zimbabwe Ministry of Agriculture estimate (relatively high yields, with planted area similar to the previous year). USGS maize yield and production estimates for 2008/09 aligned closest with those for 2006/07, and provided estimates much improved over the previous season. While actual ground conditions were not (and are still not) fully known, the story seems consistent – early planting with sufficient inputs would produce good yields. December (or late) planting, combined with mid-season dryness in the north-east, could result in a 20% reduction in yields.

Remote sensing provides a method that can be used in areas where extensive field campaigns are often impractical. In the case of Zimbabwe, these annual production estimates provided one more piece of information useful for food security decision makers.

Afghanistan

Introduction

Accurate and timely assessments of winter wheat production are important elements of food security decision making for Afghanistan. Approximately 80 percent of Afghanistan’s wheat production is supplied by irrigated winter wheat that relies heavily upon spring snowmelt. The 2007/08 winter wheat season was characterized by below average snowpack, abnormally high spring temperatures, early snowmelt, and poor rainfall, which created drought conditions throughout most of the country. USAID food security analysts wanted to characterize the impact of these conditions on probable outcomes of the winter wheat season. We were asked to assess how drought conditions would impact the 2007/08 winter wheat season and frame the severity of the drought in the context of recent years as a guide to decision making.

Methods

Figure 4. The dramatically reduced productivity in 2008 is evident in this comparison with the high production year of 2003.

Investigators used MODIS 16-day composite NDVI time series and historical yield data to evaluate the 2007/08 wheat season in comparison to the previous 8 years. Seasonal maximum NDVI has been shown to correlate well with historical wheat yields. MODIS time series data for the period 2000 to 2008 were temporally smoothed to remove cloud and other atmospheric contamination, and then stratified by irrigated areas. The time series data were spatially averaged at the provincial level and then analyzed to derive the time of annual maximum, which was consistently found to be during late April – mid May. Annual maximum NDVI values were correlated with wheat yield statistics at both the national level and for an aggregation of northern provinces, which supply the majority of the country’s wheat production. Yield statistics were obtained from Crop and Food Supply Assessment Mission (CFSAM) results supported by the Food and Agriculture Organization (FAO) and the World Food Program from 2000 to 2007. Results showed good correlations for the national level (R2 = 0.92) and the northern provinces (R2 = 0.76). We used this relationship with annual maximum NDVI as a basis for ranking the 2007/08 winter wheat yield.

Results

Nationally, the 2007/08 maximum NDVI ranked as the worst in recent years. An estimated 1.14 tons per hectare was the expected yield for 2007/08 using the regression-based yield figures (Figure 3). This ranked as second worst yield on record and less than half the yield of the most productive year (2002/03). Since the majority of Afghanistan’s production comes from the northern irrigated provinces, these are of particular interest to the food security community. A ranking of provincial-level results for the north showed a situation similar to that at the national level. When considered in aggregate, 2007/08 ranked as the worst year on record for the northern provinces as well. The lack of productivity was graphically portrayed by comparing the difference in maximum NDVI between the 2007/08 season and the productive 2002/03 season (Figure 4). While this analysis focused on irrigated winter wheat, the findings strongly suggest failure of the rainfed wheat crop as well.

This method provided a very quantifiable procedure for assessing relative crop performance using the relationship of maximum NDVI and wheat yield statistics. The analysis provided timely information that, according to the USAID FEWS NET program manager, had an enormous impact on food security decisions being made for the country of Afghanistan.

In Afghanistan, snowcapped peaks loom above agricultural fields with a network of irrigation channels. Photo courtesy of Bob Bohannon.

Conclusion

In Zimbabwe and Afghanistan, years of political upheaval and intermittent drought have contributed to the prospects of widespread hunger. In Zimbabwe, during February of 2009, an estimated 7 million people faced serious food shortages, many surviving on just one meal per day. Zimbabwe’s once-thriving agricultural production had fallen significantly and changes in the agricultural system made it difficult to get good estimates of crop production. In Afghanistan, the 2008 spring snow pack appeared to be well below normal. This could mean a reduced wheat harvest due to inadequate water for irrigation, but crop production reports would not be available until many months later. In the meantime, many people could endure serious hardship.

Clear and early answers were needed by organizations poised to send famine-mitigating food aid. Remotely sensed satellite observations were able to provide non-political, objective and timely production estimates. In both cases, we were able to use historically observed relationships between NDVI and crop production/yield to develop MODIS-based crop production/yield estimates, well before conventional statistics were available. In Afghanistan, this meant that anecdotal reports of widespread crop failure could be substantiated. In Zimbabwe, remote sensing showed improved crop production over the previous year, with the number of food insecure people likely falling to a relatively low number, compared to recent history. In both cases, strategic decisions for food aid programs could be made in a timely fashion, helping to keep costs down and increase their effectiveness in staving off widespread hunger.

¹ FOR Program, International Institute for Applied Systems Analysis, Austria

² Felis, University of Freiburg, Germany

³ University of Applied Sciences for Business and Engineering Ltd., Wiener Neustadt, Austria

⁴ IES, Joint Research Centre, European Commission, Ispra, Italy

*fritz@iiasa.ac.at

Figure 1. Clearcutting in Brazilian Pantanal (© Lanthilda | Dreamstime.com).

Abstract

In recent years the ability to collect spatial information from volunteers has greatly expanded through the combination of Google Earth, geo-tagged photos and the Internet. A Geo-Wiki has been created to aid in both the validation of existing spatial information and the collection of new information through the powerful resource of crowdsourcing. A case study of a land cover validation Geo-Wiki is described, in which the tool is used to validate existing global land cover products. The potential of such a tool for other applications is also recognized.

Introduction

With an ever increasing dependence on spatial information, and an increasing importance placed on results derived from that information, it becomes crucial to better harmonize and understand the quality of this expanding volume of data. New opportunities exist to collect additional spatial information via the Internet that were non-existent until just a few years ago. Additionally, many international, intergovernmental protocols and conventions rely on this information (e.g. the Kyoto Protocol, the Convention on Biological Diversity, the Convention to Combat Desertification; and others). However, much of the spatial data used to support these important initiatives is conflicting or contains limited validation. New efforts are thus required to improve the quality of spatial information.

In recent years, the exchange of geographic information has increased exponentially [1] and an enormous resource of volunteered geographic information [2] has emerged. In particular, due to major advances in technology development along with the emergence of Web 2.0, it is now possible for ordinary citizens to build large datasets, reversing the traditional top-down flow of information.

One example, a web-validation tool for land cover (geo-wiki.org), is extremely valuable as accurate and up to date information on global land cover plays an important role in a number of different research fields (e.g. climate change, monitoring of tropical deforestation and land use monitoring). Since global land cover datasets contain large areas of disagreement (e.g. a total area of 404 million hectares is identified as croplands in GlobCover but as non-croplands in MODIS), it is beneficial to involve a wider community to validate global land cover datasets and to provide essential information which can help to improve current global land cover. The traditional approaches of data collection and accuracy assessment are still valid and necessary, but can be complemented by such validation exercises.

In addition to land cover, other opportunities exist for such a methodology, including: reporting deforestation (Fig. 1) and illegal logging, property rights infringements, health threats and others. Following the principles of the Global Earth Observation System of Systems (GEOSS), such a tool provides decision-support to a wide variety of users.

Figure 2. Results of global land cover disagreement in both cropland and forest areas, based on an analysis of three existing land cover products: GLC-2000, MODIS and GlobCover.

Case Study: Land Cover Validation

With an ever increasing amount of very fine spatial resolution images available on Google Earth, it is becoming possible for every Internet user (including non-remote sensing experts) to distinguish land cover features with a high degree of reliability. Such an approach is inexpensive and allows Internet users from any region of the world to get involved in this global validation exercise [3].

Currently in geo-wiki.org, volunteers have the ability to view both cropland and forest Disagreement Maps that were derived from three recent global land cover datasets: GLC-2000, MODIS and GlobCover. Disagreement Maps guide the volunteers to areas of the globe with the highest levels of disagreement – prioritizing the disagreement hotspots in a global cropland/forest Disagreement Map (Fig. 2).

With the help of Google Earth, the next step is to select and visualize available high resolution images as well as to upload or view geo-tagged field pictures (e.g., from Panoramio.com, Confluence.org, or from research projects such as the Global Monitoring for Food security Project (GMFS)), and determine which land cover type is found on the ground (Fig. 3). Volunteers are then asked to decide if the land cover products correctly capture what they see or know to exist on the ground. In addition, it is possible to recommend a new land cover class (i.e. select from a list of possible land cover types, and upload available photos to support the decision). All information entered by volunteers is recorded in a publically available spatial database. This validation database contains a record of the agreement among the datasets, and can be used in the future to create an improved hybrid dataset.

Remaining Challenges

Despite the enormous potential of geo-wiki.org, two main challenges remain. The first challenge is to attract a wide range of volunteers from across the globe. In terms of possible further low cost outreach facilities, one option would be to use social networks and existing user groups, especially those which include people who have some type of experience in geography, visual image analysis and mapping. The second challenge is to guarantee a certain level of quality and to ensure that the tool is not misused. As discussed by a number of authors, the question of credibility of public voluntary contributions is crucial. It can be assumed that if the application is designed in a way similar to Wikipedia and entries are to some extent monitored by volunteers (and are open to additional information by anyone who disagrees with them [4]) – the application has potential to become truly successful.

Future Outlook

Figure 3. Geo-tagged photos uploaded in geo-wiki.org (A) confirming the actual land cover seen in Google Earth high resolution images (B). Using the high resolution images available in Google Earth, in combination with available photos, a volunteer can correct existing land cover products. This combination of information sources, together with user input through the geo-wiki.org interface, creates a very powerful validation source.

IIASA, the International Institute for Applied Systems Analysis, is committed in the next years to maintain geo-wiki.org. Information collected through this tool is continuously recorded in a publicly available spatial database. This application complements previous validation exercises of these products (such as field validation by trained experts) and current efforts of the Earth Observation community to develop an improved global land cover validation database. More importantly, it is intended to lead to a hybrid consolidated land cover map, by combining different maps through geo-statistical methods, incorporating the additional land cover information retrieved by the geo-wiki tool.

Furthermore, efforts are underway to modify the geo-wiki.org to collect and analyze data on many different themes such as mapping indigenous people’s territories, locating illegal logging activities, mapping deforestation and more. Additionally, collaboration with various institutes and agencies is being fostered in an effort to obtain more geo-tagged field photos (e.g. Confluence.org, GMFS and classified satellite products e.g. FAO FRA2010). In the near future plans are being formulated to add a temporal aspect to geo-wiki.org, allowing for the monitoring of land use change.

Acknowledgements

This research was supported by the European Community’s Framework Programme (FP6/FP7) via GEOBENE (No. 037063) and EuroGEOSS (No. 226487).

References

1. Goodchild, M.F.; Fu, P.; Rich, P. Sharing geographic information: an assessment of the geospatial one-stop. Ann. Assn. Amer. Geogr. 2007, 97, 250-266.

2. Flanagin, A.J.; Metzger, M.J. The credibility of volunteered geographic information. GeoJournal 2008, 72, 137-148.

3. Fritz, S.; McCallum, I.; Schill, C.; Perger, C.; Grillmayer, R.; Achard, F.; Kraxner, F.; Obersteiner, M. Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover. Remote Sens. 2009, 1, 345-354.

4. Goodchild, M.F. Commentary: whither VGI? GeoJournal 2008, 72, 239-244.