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USDA's research and operational programs made use of remotely sensed data and related technologies to benefit agriculture and forestry. This section of the report highlights USDA agencies that advanced remote-sensing knowledge, developed improved applications, and used imagery and technology to produce more accurate and timely products and services.

The Agriculture Research Service (ARS) enhanced remote-sensing knowledge and developed productive applications of the technology at research facilities located throughout the United States. At Weslaco, Texas, the ARS Integrated Farming and Natural Resources Unit collected data over the Southern Great

Plains to determine the relationship between soil moisture and regional climate conditions and the variability of soil moisture over space and time. At the Jornada Experimental Range, the ARS Hydrology Laboratory collected laser profiler data and visible, thermal infrared and video imagery to infer surface temperature, albedo, vegetation indices, roughness, and other land-surface characteristics. At ARS laboratories in Ames, Iowa, Lincoln, Nebraska, and Lubbock, Texas, scientists quantified relationships among plant populations, nitrogen stress, water stress, and remotely sensed information. In Iowa, for example, ARS determined when in the growing season weeds can be differentiated from economic crops, such as corn and soybeans, and how variations in soil patterns are related to observed patterns in crops. In Phoenix, Arizona, the ARS U.S. Water Conservation Laboratory cooperated with NASA's Stennis Space Center to develop products and applications using data from multispectral airborne sensors to manage crops and soils.

Using remote-sensing technology, the ARS Remote Sensing and Modeling Laboratory (RSML) and the Hydrology Laboratory initiated a long-term experiment to evaluate the economic and environmental impact of four alternative farming practices on surface and subsurface water quality. Working with the National Agricultural Statistics Service (NASS), RSML assessed crop yields at regional scales, using models and remote-sensing data. Researchers succeeded in assessing spring wheat yields in North Dakota in just 1 month following crop maturity, compared to the usual 4 months. This increased speed and improved spatial accuracy are very important to program managers because of the potential for assessing foreign crops. RSML also developed a method for using multispectral fluorescence imaging to conduct nondestructive evaluations of crop physiological status. Likewise, RSML used fluorescent sensing to detect ozone damage, ultraviolet radiation damage to vegetation, and the effect of increased carbon dioxide. RSML research demonstrated that remote sensing can accurately assess tropospheric environmental problems.

The satellite remote-sensing program of the Foreign Agricultural Service (FAS) remained a critical element in USDA's analysis of global agricultural production and crop conditions by providing timely, accurate, and unbiased estimates of global area, yield, and production. Satellite-derived early warning of unusual crop conditions and production anomalies enabled more rapid and precise determinations of global supply conditions. FAS used NOAA, Advanced Very High Resolution Radiometer (AVHRR), Landsat, and French SPOT imagery, crop models, weather data, attaché reports, field travel, and ancillary data to forecast foreign grain, oilseed, and cotton production. FAS remote sensing supported Department of State (DoS) assessments of food needs in Indonesia, North Korea, and the former Soviet Union. Also, FAS prepared detailed analyses of the El Niño event, the record Argentine soybean crop, the bumper wheat crop in Australia, the bumper soybean crop in Brazil, flooding in China and North Korea, and drought in Mexico and Indonesia.

The Farm Service Agency (FSA) continued to share with FAS the cost of analyzing imagery of the United States. Timely analysis of U.S. crop conditions, combined with weather data, crop model results, and GIS products, made possible the development of accurate and timely projections and comprehensive evaluations of crop disaster situations. FSA continued to be a partner in NAPP and the National Digital Orthoquad Program (NDOP). FSA started to field reengineered business processes that combine the use of digital orthophotography, GIS, GPS, and satellite imagery to replace the use of hardcopy NAPP aerial photography and 35-millimeter slides.

The USDA Forest Service and Stephen F. Austin University hosted the Seventh Forest Service Remote Sensing Applications Conference, in Nassau Bay, Texas. The conference, focusing on "Natural Resources Management Using Remote Sensing and GIS," attracted a wide range of representatives from Federal and State government, the private sector, and academia, and it resulted in more than 35 published papers. Besides using remotely sensed data to manage 191 million acres of land in the National Forest System, the Forest Service supported many international projects by providing remotely sensed data and expertise. These projects included prefire planning in Brazil, fire suppression support in Mexico, and fire recovery work in Indonesia. All three countries received fire mapping support, for which remotely sensed data were essential in providing timely and accurate information.

NASS used remote-sensing data to construct area frames for statistical sampling, to estimate crop area, to create crop-specific land-cover data layers for GIS, and to assess crop conditions. For area frame construction, NASS combined digital Landsat and SPOT data with USGS digital line-graph data, enabling the user to assign each piece of land in a State to a category, based on the percentage of cultivation or other variables. NASS implemented new remote-sensing-based area frames and samples for Texas and Puerto Rico for the survey and census of agriculture coverage measures. The remote-sensing acreage estimation project analyzed Landsat data of the 1997 crop season in Arkansas, North Dakota, and South Dakota and then collected 1998 crop season data for the same three States. End-of-season TM analysis produced crop acreage estimates for major crops at State and county levels, as well as a crop-specific categorization in the form of a digital mosaic of TM scenes distributed to users on a CD-ROM. Vegetation condition images based on AVHRR data were used with conventional survey data to assess crop conditions.

The Natural Resources Conservation Service (NRCS) continued its partnership with Federal, State, and local agencies in sharing costs to develop 1-meter digital ortho-imagery coverage through NDOP. By year's end, 76 percent of the Nation's digital ortho-imagery was either complete or in progress. Federal-State cooperative agreements for statewide ortho-imagery were started in Indiana, Kentucky, Louisiana, Maryland, Missouri, Ohio, Texas, and West Virginia. Indiana was the first project of this magnitude to use airborne GPS horizontal ground control acquired concurrently with new aerial imagery. The NRCS increased the use of remote sensing to collect natural resource data for its National Resources Inventory Program by contracting for low-level high-resolution imagery over 6,000 sampling sites across the Nation during the growing season.

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