Agricultural Research Service research highlights in remote sensing for calendar year 1981

Selected examples of research accomplishments related to remote sensing are compiled. A brief statement is given to highlight the significant results of each research project. A list of 1981 publication and location contacts is given also. The projects cover emission and reflectance analysis, identification of crop and soil parameters, and the utilization of remote sensing data

A preliminary study of the statistical analyses and sampling strategies associated with the integration of remote sensing capabilities into the current agricultural crop forecasting system

Extending the crop survey application of remote sensing from small experimental regions to state and national levels requires that a sample of agricultural fields be chosen for remote sensing of crop acreage, and that a statistical estimate be formulated with measurable characteristics. The critical requirements for the success of the application are reviewed in this report. The problem of sampling in the presence of cloud cover is discussed. Integration of remotely sensed information about crops into current agricultural crop forecasting systems is treated on the basis of the USDA multiple frame survey concepts, with an assumed addition of a new frame derived from remote sensing. Evolution of a crop forecasting system which utilizes LANDSAT and future remote sensing systems is projected for the 1975-1990 time frame

Use of soil moisture information in yield models

There are no author-identified significant results in this report

Agricultural Research Service research highlights in remote sensing for calendar year 1980

The AR research mission in remote sensing is to develop the basic understanding of the soil plant animal atmosphere continuum in agricultural ecosystems and to determine when remotely sensed data can be used to provide information about these agricultural ecosystems. A brief statement of the significant results of each project is given. A list of 1980 publication and location contacts is also given

Quantitative estimation of plant characteristics using spectral measurement: A survey of the literature

There are no author-identified significant results in this report

Large Area Crop Inventory Experiment (LACIE). Level 3 baseline; Yield Estimation Subsystem (YES) requirements, volume 3, revision A

There are no author-identified significant results in this report

Crop yield literature review for AgRISTARS crops: Corn, soybeans, wheat, barley, sorghum, rice, cotton, and sunflowers

There are no author-identified significant results in this report

Earth Observations and Integrative Models in Support of Food and Water Security

Global food production depends upon many factors that Earth observing satellites routinely measure about water, energy, weather, and ecosystems. Increasingly sophisticated, publicly-available satellite data products can improve efficiencies in resource management and provide earlier indication of environmental disruption. Satellite remote sensing provides a consistent, long-term record that can be used effectively to detect large-scale features over time, such as a developing drought. Accuracy and capabilities have increased along with the range of Earth observations and derived products that can support food security decisions with actionable information. This paper highlights major capabilities facilitated by satellite observations and physical models that have been developed and validated using remotely-sensed observations. Although we primarily focus on variables relevant to agriculture, we also include a brief description of the growing use of Earth observations in support of aquaculture and fisheries

Proceedings of the 1974 Lyndon B. Johnson Space Center Wheat-Yield Conference

The proceedings of the 1974 Lyndon B. Johnson Space Center Wheat-Yield Conference are presented. The state of art of wheat-yield forecasting and the feasibility of incorporating remote sensing into this forecasting were discussed with emphasis on formulating common approach to wheat-yield forecasting, primarily using conventional meteorological measurements, which can later include the various applications of remote sensing. Papers are presented which deal with developments in the field of crop modelling

Characterizing crop productivity under heat stress using MODIS data

Stress caused by high temperatures is a critical limiting factor of crop growth and development. Although remote sensing has been used to investigate the impacts of high temperatures on crops, its ability to detect heat stress independently of other stressors and assess its effects on gross primary production (GPP) estimation is unclear. This study developed an innovative approach to distinguish crop heat stress periods from normal growth conditions in croplands independent of water stress and light limitation. Multispectral broad bands and spectral vegetation indices (VIs) derived from MODIS for 78 periods of heat stress were used to assess the sensitivity of canopy reflectance to heat stress and its impacts on GPP. Results reveal that heat stress significantly increased the reflectance in the red band. VIs, in general, enhanced the detection of heat-induced spectral variations, and exhibited sufficient skill in distinguishing crops under heat stress and normal conditions. Three visible-based indices (the Visible Atmospherically Resistant Index, the Green Leaf Index, and the Normalized Green–Red Difference Index) exhibited the highest discriminability (p-value < 0.01 in the Mann–Whitney U test), while the Enhanced Vegetation Index displayed the highest accuracy in GPP estimation (R2 = 0.62, RMSE = 5.49, RRMSE = 0.35) under heat conditions. Overall, the isolation of heat stress impact on crop growth has important implications for advancing large-scale crop modeling and climate change studies, for example, incorporating the suggested VIs into temperature response simulations within crop models