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NASA NTRS2021

Evaluation of SWIR Crop Residue Bands for the Landsat Next Mission

This research reports the findings of a Landsat Next expert review panel that evaluated the use of narrow shortwave infrared (SWIR) reflectance bands to measure ligno-cellulose absorption features centered near 2100 and 2300 nm, with the objective of measuring and mapping non-photosynthetic vegetation (NPV), crop residue cover, and the adoption of conservation tillage practices within agricultural landscapes. Results could also apply to detection of NPV in pasture, grazing lands, and non-agricultural settings. Currently, there are no satellite data sources that provide narrowband or hyperspectral SWIR imagery at sufficient volume to map NPV at a regional scale. The Landsat Next mission, currently under design and expected to launch in the late 2020’s, provides the opportunity for achieving increased SWIR sampling and spectral resolution with the adoption of new sensor technology. This study employed hyperspectral data collected from 916 agricultural field locations with varying fractional NPV, fractional green vegetation, and surface moisture contents. These spectra were processed to generate narrow bands with centers at 2040, 2100, 2210, 2260, and 2230 nm, at various bandwidths, that were subsequently used to derive 13 NPV spectral indices from each spectrum. For crop residues with minimal green vegetation cover, two-band indices derived from 2210 and 2260 nm bands were top performers for measuring NPV (R^(2) = 0.81, RMSE = 0.13) using bandwidths of 30 to 50 nm, and the addition of a third band at 2100 nm increased resistance to atmospheric correction residuals and improved mission continuity with Landsat 8 Operational Land Imager Band 7. For prediction of NPV over a full range of green vegetation cover, the Cellulose Absorption Index, derived from 2040, 2100, and 2210 nm bands, was top performer (R^(2) = 0.77, RMSE = 0.17), but required a narrow (≤20 nm) bandwidth at 2040 nm to avoid interference from atmospheric carbon dioxide absorption. In comparison, broadband NPV indices utilizing Landsat 8 bands centered at 1610 and 2200 nm performed poorly in measuring fractional NPV (R^(2) = 0.44), with significantly increased interference from green vegetation

Wells Dean Hively↗

NASA NTRS1985

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

Pelletier, R. E.↗

NASA NTRS1986

Utility of remotely sensed data for identification of soil conservation practices

Discussed are a variety of remotely sensed data sources that may have utility in the identification of conservation practices and related linear features. Test sites were evaluated in Alabama, Kansas, Mississippi, and Oklahoma using one or more of a variety of remotely sensed data sources, including color infrared photography (CIR), LANDSAT Thematic Mapper (TM) data, and aircraft-acquired Thermal Infrared Multispectral Scanner (TIMS) data. Both visual examination and computer-implemented enhancement procedures were used to identify conservation practices and other linear features. For the Kansas, Mississippi, and Oklahoma test sites, photo interpretations of CIR identified up to 24 of the 109 conservation practices from a matrix derived from the SCS National Handbook of Conservation Practices. The conservation practice matrix was modified to predict the possibility of identifying the 109 practices at various photographic scales based on the observed results as well as photo interpreter experience. Some practices were successfully identified in TM data through visual identification, but a number of existing practices were of such size and shape that the resolution of the TM could not detect them accurately. A series of computer-automated decorrelation and filtering procedures served to enhance the conservation practices in TM data with only fair success. However, features such as field boundaries, roads, water bodies, and the Urban/Ag interface were easily differentiated. Similar enhancement techniques applied to 5 and 10 meter TIMS data proved much more useful in delineating terraces, grass waterways, and drainage ditches as well as the features mentioned above, due partly to improved resolution and partly to thermally influenced moisture conditions. Spatially oriented data such as those derived from remotely sensed data offer some promise in the inventory and monitoring of conservation practices as well as in supplying parameter data for a variety of computer-implemented agricultural models.

Pelletier, R. E.↗

NASA NTRS2020

Gila Water Resources II: Using Earth Observations to Identify Wildfire Impacts on Hydrologic Functions and Recovery in the Gila National Forest

Wildfires have the potential to cause devastating and long-lasting impacts on ecological systems. In the Gila National Forest (Gila NF), wildfire events have occurred with increasing frequency and severity over recent years. These disturbances, such as the historic Whitewater Baldy Complex Fire (2012) and Silver Fire (2013), have raised concerns over post-fire flooding, debris flows, and vegetation recovery. Understanding connections between burn events and ecological functions is crucial for developing effective land management practices within the Gila NF that ensure conservation of the watershed. The Gila Water Resources II team worked in partnership with the US Department of Agriculture (USDA) US Forest Service’s (USFS) Gila National Forest and Region 3. This project provided insight into the influence of wildfires on increased flooding events and determined if restoration efforts in the Gila NF are having a beneficial impact on vegetation regeneration. To understand recovery trends and hydrologic impact in the Gila NF between 2000-2019, this project used Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, Global Precipitation Measurement Integrated Multi-satellite Retrievals for GPM precipitation, along with ancillary data from USGS stream gauges and data provided by USDA USFS’s Gila National Forest and Region 3. Based on these data, the team identified burn areas that received restorative treatments and compared Normalized Burn Ratio for different land cover types to better inform land management decisions. Additionally, the team analyzed the relationship between precipitation and streamflow from stream gauges to investigate the impact wildfires have on hydrology within the watershed.

Water Resources↗

NASA NTRS2020

Gila Water Resources II: Using Earth Observations to Identify Wildfire Impacts on Hydrologic Functions and Recovery in the Gila National Forest

Wildfires have the potential to cause devastating and long-lasting impacts on ecological systems. In the Gila NF, wildfire events have occurred with increasing frequency and severity over recent years. These disturbances such as the historic Whitewater-Baldy Complex Fire (2012) and Silver Fire (2013) have raised concerns over post-fire soil erosion, flooding, debris flows, and vegetation recovery. Understanding the connection between burn events and ecological functions is crucial for developing effective land management practices within the Gila NF that ensure the conservation of the watershed. Our Gila Water Resources II team worked in partnership with the US Department of Agriculture (USDA) US Forest Service’s (USFS) Gila National Forest and Region 3. This project was designed to provide insight into the influence of wildfires on increased flooding events and to determine if restoration efforts in the Gila NF are having a beneficial and noticeable impact on recovery. The goals of this project included generating data-supported end products to inform land management decisions, including the prioritization of specific regions and time scales for post-fire restoration efforts. To understand recovery trends and hydrologic impact in the Gila NF between 2000 and 2020, this project used NASA EO and ancillary data, including, but not limited to, Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), USGS stream gauge data, and data provided by USDA USFS’s Gila National Forest and Region 3.

Water Resources↗

NASA NTRS2016

Remote Sensing and Modeling for Improving Operational Aquatic Plant Management

The California Sacramento-San Joaquin River Delta is the hub for California’s water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.

Agriculture↗

NASA NTRS2016

Adaptive Management Methods to Protect the California Sacramento-San Joaquin Delta Water Resource

The California Sacramento-San Joaquin River Delta is the hub for California's water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.

Agriculture↗

NASA NTRS2023

Bhutan Agriculture III: Monitoring Cropland Changes in Bhutan using Remote Sensing to Bolster Food Security and Support Crop Monitoring

The Bhutan Agriculture III team aimed to improve agricultural efficiency in Bhutan. Bhutan is a nation heavily reliant on agriculture, but it faces challenges such as geophysical limitations and lack of scientific agricultural practice. The team partnered with a primary end user, Bhutan’s Department of Agriculture (DoA), and with collaborators; the Bhutan Foundation, National Plant Protection Centre (NPPC), Agricultural Research Department Centre (ARDC), National Statistics Bureau (NSB), and the Ugyen Wangchuck Institute for Conservation and Environment Research (UWICER). Advised by NASA SERVIR, the team developed crop masks and monitored rice distribution from 2015 to 2022 utilizing Earth observations such as Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR), Sentinel-2 MultiSpectral Instrument (MSI) and Shuttle Radar Topography Mission (SRTM). The team gathered 5,000 points from the five dzongkhags that yield the most rice in Bhutan (Paro, Punakha, Samtse, Sarpang and Wangue Phodrang) using Collect Earth Online (CEO). With the data collected, the team split the data into training and validation data on Google Earth Engine (GEE) for a random forest (RF) classifier for rice and non-rice classification. After running the data on the Random Forest (RF) model, the team got an accuracy score of 81.48%, a kappa score of 55.75% and an F1 score of 86.11%. This data supports better agricultural decision-making for the governing body of Bhutan, helps enhance farming efficiency and foster sustainable practices, assists in overcoming data inaccuracy and bolsters food security in the country.

Sonam Seldon Tshering↗

NASA NTRS2025

Jemez Pueblo Agriculture: Monitoring Rangeland Conditions to Inform Drought and Land Management in New Mexico

The Jemez Pueblo, a community located in the semi-arid high desert region of northcentral New Mexico, faces challenges with drought mitigation and livestock management. NASA DEVELOP partnered with the Pueblo of Jemez Natural Resources Department and The Nature Conservancy to provide recent and historical rangeland conditions to aid present decision-making, which relies on cultural practices, site familiarity, available resources, and physical data. This partnership offers the opportunity to support management practices by leveraging remote sensing and virtual fencing technologies. Our project explored Rangeland Analysis Platform (RAP) products incorporating NASA Earth observation Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2 remote-sensed imagery as an agricultural land management tool. We performed linear regression analysis to evaluate RAP data to field data and explored RAP annual herbaceous biomass, ground cover trends, and climatic factors at the pasture level. We then computed study area summary statistics, performed pixel-by-pixel trend analysis across the study period, and evaluated ground cover trends near water sources. Based on available data, RAP was poorly correlated to bare ground and herbaceous biomass, generally underestimating the former and overestimating the latter. To improve the evaluation of RAP products, we suggest increasing the spatiotemporal distribution of the field dataset. According to RAP, from 1986 to 2023, the site became hotter and drier, bare ground increased, and annual forbs and grasses increased while perennials decreased. RAP products did not agree with field-collected data; however, the trends over time may be useful for informing rangeland management actions.

cattle grazing management↗

NASA NTRS2015

Using Science Skills to Understand Ecophysiology and Manage Resources

Presentation will be for a general audience and focus on plant science and ecosystem science in NASA. Examples from the projects involving the presenter will be used to illustrate. Specifically, the California Sacramento-San Joaquin River Delta project. This collaboration supports the goals of the Delta Plan in developing science-based, adaptive-management strategies. The mission is to improve reliability of water supply and restore a healthy Delta ecosystem while enhancing agriculture and recreation. NASA can contribute gap-filling science understanding of overall functions in the Delta ecosystem and assess and help develop management plans for specific issues. Airborne and satellite remote-sensing, ecosystem modeling, and biological studies provide underlying data needed by Delta stakeholders to assess and address water, ecosystem restoration, and environmental and economic impacts of potential actions in the Delta. The California Sacramento-San Joaquin River Delta, the hub for California's water supply, supports important ecosystem services for fisheries, supplies drinking water for millions, and distributes water from Northern California to agriculture and urban communities to the south; millions of people and businesses depend on Delta water. Decades of competing demands for Delta resources and year-to-year variability in precipitation has resulted in diminished overall health of the Delta. Declines in fish populations, threatened ecosystems, endangered species, invasive plants and animals, cuts in agricultural exports, and increased water conservation is the result. NASA and the USDA, building on previous collaborations, aide local Delta stakeholders in assessing and developing an invasive weed management approach. Aquatic, terrestrial, and riparian invasive weeds threaten aquatic and terrestrial ecosystem restoration efforts. Aquatic weeds are currently detrimental economically, environmentally, and sociologically in the Delta. They negatively impact the redistribution of water and disrupt the ecology of the Bay Delta food web. Filling current science gaps in the Delta Plan and improving management practices within the Delta are important to achieving the mission of improved Delta health. Methods developed can become routine land and water management tools. New high-resolution NASA sensor systems could be used to provide data packages specifically designed for water system The presenter will also speak about his personal experience and the role Delaware Valley College played in preparation for a professional career science.

Water↗

NASA NTRSDate not supplied

Predicting the Likelihood of Human-Elephant Conflict and Assessing Patterns in Elephant Movements Over Varying Habitat Conditions in the Kavango-Zambezi Area

In the Kavango-Zambezi area of southern Africa, three million people live within areas frequently traveled by free-ranging elephants. As the region continues to develop rapidly, urban and agricultural settlements further encroach upon the land that these elephants use. As elephants come into more frequent contact with urban and agricultural areas, human populations face financial loss through crop damage and the potential for injury from direct conflict with elephants. Elephant populations are also at risk of injuries from conflict as well as illness related to the consumption of waste. In order to implement human-elephant conflict mitigation strategies, local conservation groups need to be informed on best practices for coexistence. This project aided The Ecoexist Project and Connected Conservation in understanding the ecological factors that drive elephant movement into human settlements and provided Earth observation data to support conflict management in the future. The team used Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI) data to create land use land cover maps and calculate vegetation indices, and used TerraClimate data to analyze drought conditions. These classified maps allowed us to display a time series of human settlement from 1990 to the present and were made explorable alongside other environmental variables in an updated Google Earth Engine (GEE) tool. This project also provided heat maps that show the risk of human-elephant conflict based on historical data of HEC locations. This analysis will provide support for conservation experts in determining best practices for future mitigation and prevention of human-elephant conflict.

Ariel Calle↗

NASA NTRSDate not supplied

Relating Land Cover Change to Runoff Distribution Using NASA Earth Observations in Riley County, Kansas

Riley County, Kansas, has observed increased levels of flooding, potentially due to changes in land use/land cover (LULC) and seasonal vegetation variation. This study contrasts two methods of generating runoff curve numbers (CN) from 2006-2020. (1) The traditional Soil Conservation Service CN calculation method uses a look-up table and tracked LULC to determine runoff changes. These tables allow for CN values specific to various land and crop cover types and account for various farming best practices but lack flexibility in calculations for various seasons or plant health. (2) A dynamic method employs normalized difference vegetation index (NDVI) compiled over the rainy season each year to calculate CN using seasonal vegetation. This method allows for a more precise analysis of runoff variability within and between rainy seasons because it can be updated with greater temporal detail and it captures higher spatial resolutions by using NDVI as a proxy for LULC. This study further uses inputs from the United States Geologic Survey (USGS) National Land Cover Database (NLCD), the United States Department of Agriculture (USDA) Cropland Data Layer, and Landsat imagery to create more precise LULC raster datasets including both urban cover and crop-specific land use and curve number maps of the area. Results can guide decision makers in the City of Manhattan, Riley County Department of Planning and Development, Riley County Conservation District, the Kansas Forest Service, and the Kansas Department of Health and Environment toward informed decisions on resiliency strategies to address future flooding.

Ella Griffith↗

NASA NTRS1981

AgRISTARS - Plans and first-year achievements

The results of the agriculture and resources inventory surveys through aerospace remote sensing (AgRISTARS) program managed by the USDA for exploring the use of satellite data for domestic and global commodity information needs are discussed. The program was intended to gather early warning of changes affecting production and quality of commodities and renewable resources, for predicting commodity production, land use classification and quantification, for inventories and assessments of renewable resources, land productivity measurements, assessment of conservation practices, and for pollution detection and impact evaluation. Up to 20 crop/region combinations in 7 countries were covered by the experiments, which comprised NOAA 6 and Landsat data analyses. Attempts to reduce variances through improved machine classification techniques are reported, together with soil moisture profiling, and the use of airborne sensors for providing comparative data.

Hall, F. G.↗

NASA NTRS1979

Cropping management using color and color infrared aerial photographs

The Universal Soil Loss Equation (USLE) is a widely accepted tool for erosion prediction and conservation planning. Solving this equation yields the long-term average annual soil loss that can be expected from rill and inter-rill erosion. In this study, manual interpretation of color and color infrared 70 mm photography at the scale of 1:60,000 is used to determine the cropping management factor in the USLE. Accurate information was collected about plowing practices and crop residue cover (unharvested vegetation) for the winter season on agricultural land in Pheasant Branch Creek watershed in Dane County, Wisconsin.

Morgan, K. M.↗

NASA NTRS1997

An Investigation of the Migration of Africanized Honey Bees into the Southern United States

It is estimated that Apis mellifera scutellata, a honey bee subspecies from Africa, now extends over a 20 million square kilometer range that includes much of South America and practically all of Central America, and recently has been introduced to the southern United States. African honeybees were introduced into Brazil in 1956 by a Brazilian geneticist, Mr. Warwick Kerr. At the insistence of the Brazilian Ministry of Agriculture, in 1957, 26 colonies were accidentally released in a eucalyptus forest outside S5o Paulo. The swelling front of the bees was recorded as traveling between 80 and 500 kilometers a year. David Roubik, one of the original killer bee team members estimated that there were one trillion individual Africanized/African honey bees in Latin America. An estimate that is thought to be conservative.

Navarro, Hector↗

NASA NTRS2010

Improved Hypoxia Modeling for Nutrient Control Decisions in the Gulf of Mexico

As required by the Harmful Algal Bloom and Hypoxia Research Control Act of 1998, the Mississippi River/Gulf of Mexico Watershed Nutrient Task Force issued the 2001 Gulf Hypoxia Action Plan (updated in 2008). In response to the Gulf Hypoxia Action Plan of 2001 (updated in 2008), the EPA Gulf of Mexico Hypoxia Modeling and Monitoring Project has established a detailed model for the Mississippi-Attchafalaya River Basin which provides a capability to forecast the multi-source nutrient loading to the Gulf and the subsequent bio-geochemical processes leading to hypoxic conditions and subsequent effects on Gulf habitats and fisheries. The primary purpose of the EPA model is to characterize the impacts of nutrient management actions, or proposed actions on the spatial and temporal characteristics of the Gulf hypoxic zone. The model is expected to play a significant role in determining best practices and improved strategies for incentivizing nutrient reduction strategies, including installation of on-farm structures to reduce sediment and nutrient runoff, use of cover crops and other agricultural practices, restoration of wetlands and riparian buffers, improved waste water treatment and decreased industrial nitrogen emissions. These decisions are currently made in a fragmented way by federal, state, and local agencies, using a variety of small scale models and limited data. During the past three years, EPA has collected an enormous amount of in-situ data to be used in the model. We believe that the use of NASA satellite data products in the model and for long term validation of the model has the potential to significantly increase the accuracy and therefore the utility of the model for the decision making described above. This proposal addresses the Gulf of Mexico Alliance (GOMA) priority issue of reductions in nutrient inputs to coastal ecosystem. It further directly relates to water quality for healthy beaches and shellfish beds and wetland and coastal conservation restoration.

Habib, Shaid↗

NASA NTRS2025

Nevada Wildland Fires: Mapping Historical Burned Areas and Identifying Drivers of Fuel Load Growth to Inform Desert Tortoise Habitat Management in Southern Nevada

Wildfire frequency and intensity in the Mojave desert are increasing, driven by invasive grasses that outcompete native vegetation not well-adapted to wildfire. These grasses, primarily cheatgrass (Bromus tectorum) and red brome (Bromus rubens), and the wildfires that occur when the grasses ignite, are a serious threat to the critically endangered Mojave desert tortoise (Gopherus agassizii). Declining Mojave desert tortoise populations are of great concern to project partners, the Bureau of Land Management Southern Nevada District Office, the US Forest Service’s Rocky Mountain Research Station, and the US Department of Agriculture Agricultural Research Service’s Arid Lands Ecology Lab, who currently lack the resources for fire recovery studies essential for informed fire and invasive grass management. To address this gap, the team utilized NASA Earth observations including Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Terra MODIS, Landsat 5 Thematic Mapper (TM), and Landsat 8 Operational Land Imager (OLI), to analyze trends in burned areas over the past 20 years through historic burn maps and to examine fuel load growth drivers, with a focus on invasive vegetation. These historical burn maps revealed a pattern of precipitation anomalies that strongly correlate with higher Normalized Difference Vegetation Index (NDVI) values. Years with significant precipitation and NDVI spikes led to greater fuel load in the dry season and larger burns. Additionally, El Niño years correlated significantly with precipitation anomalies which may provide our partners with insights into burn trends and enable better allocation of fuel load treatment practices. However, while identifying drivers of fuel load growth proved feasible, a lack of in situ data hindered attempts to analyze pre-fire growth of invasive grasses compared with native grasses. Despite this limitation, the project demonstrated the feasibility of using Earth observations for wildfire and habitat management, ultimately benefiting conservation efforts for the Mojave desert tortoise.

fuel load↗

NASA NTRS1996

Development of a Land Use Mapping and Monitoring Protocol for the High Plains Region: A Multitemporal Remote Sensing Application

The purpose of this project was to develop a practical protocol that employs multitemporal remotely sensed imagery, integrated with environmental parameters to model and monitor agricultural and natural resources in the High Plains Region of the United States. The value of this project would be extended throughout the region via workshops targeted at carefully selected audiences and designed to transfer remote sensing technology and the methods and applications developed. Implementation of such a protocol using remotely sensed satellite imagery is critical for addressing many issues of regional importance, including: (1) Prediction of rural land use/land cover (LULC) categories within a region; (2) Use of rural LULC maps for successive years to monitor change; (3) Crop types derived from LULC maps as important inputs to water consumption models; (4) Early prediction of crop yields; (5) Multi-date maps of crop types to monitor patterns related to crop change; (6) Knowledge of crop types to monitor condition and improve prediction of crop yield; (7) More precise models of crop types and conditions to improve agricultural economic forecasts; (8;) Prediction of biomass for estimating vegetation production, soil protection from erosion forces, nonpoint source pollution, wildlife habitat quality and other related factors; (9) Crop type and condition information to more accurately predict production of biogeochemicals such as CO2, CH4, and other greenhouse gases that are inputs to global climate models; (10) Provide information regarding limiting factors (i.e., economic constraints of pumping, fertilizing, etc.) used in conjunction with other factors, such as changes in climate for predicting changes in rural LULC; (11) Accurate prediction of rural LULC used to assess the effectiveness of government programs such as the U.S. Soil Conservation Service (SCS) Conservation Reserve Program; and (12) Prediction of water demand based on rural LULC that can be related to rates of draw-down of underground water supplies.

Price, Kevin P.↗