6,517 research outputs found

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

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    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

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

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    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

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    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

    Analysis of data systems requirements for global crop production forecasting in the 1985 time frame

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    Data systems concepts that would be needed to implement the objective of the global crop production forecasting in an orderly transition from experimental to operational status in the 1985 time frame were examined. Information needs of users were converted into data system requirements, and the influence of these requirements on the formulation of a conceptual data system was analyzed. Any potential problem areas in meeting these data system requirements were identified in an iterative process

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

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    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

    Forecasts of winter wheat yield and production using LANDSAT data

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    There are no author-identified significant results in this report

    The economics of irrigating wheat in a humid climate - A study in the East of England

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    In the UK, wheat is the most important cultivated cereal, grown extensively as a rainfed crop. Irrigation of wheat has previously been considered uneconomic, but increases in world wheat prices and recent droughts have led to some farmers revising their views. Widespread adoption of wheat irrigation would have major implications for wheat production, the irrigation industry and water resources in regions that are already water scarce. This study investigated the financial viability of irrigating winter wheat grown on a sandy loam soil in the East of England. Long-term climate data (1961–2011) for Silsoe (Bedfordshire) was used to drive a biophysical crop model to assess irrigation water requirements and yield response. Modelling assumed a typical irrigation schedule to maximise yield and quality, and average reported wheat prices for 2007 to 2012. Irrigation costs were calculated assuming an overhead mobile hosereel–raingun system applying river water, abstracted either in summer and used directly, or abstracted in winter and stored in an on-farm reservoir. The results suggest that the yield benefit would justify supplemental irrigation by farmers who have unused irrigation equipment and unused summer water, although irrigation of higher-value field vegetable crops later in the season would normally take precedence – the Added Value of Water (AVW) usefully applied to milling winter wheat under these conditions ranged between 0.24 and 0.32 £ m−3. Investment in new irrigation schemes could also be marginally viable if unused summer river water was available for direct abstraction (AVW = 0.08 £ m−3). Investments in new farm reservoirs for irrigating wheat are currently not profitable (AVW = –0.23 £ m−3). Sensitivity analysis suggests that in the longer term, the expected increase in world wheat prices and the impacts of climate change are likely to make the financial benefits stronger, particularly in the drier catchments further east and on low moisture retentive soils, but competing demands for water would still make extensive wheat irrigation unlikely

    Crop calendars for the US, USSR, and Canada in support of the early warning project

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    New crop calendars are produced for U.S. regions where several years of periodic growth stage observations are available on a CRD basis. Preexisting crop calendars from the LACIE are also collected as are U.S. crop calendars currently being created for the Foreign Commodities Production Forecast project. For the U.S.S.R. and Canada, no new crop calendars are created because no new data are available. Instead, LACIE crop calendars are compared against simulated normal daily temperatures and against the Robertson wheat and Williams barley phenology models run on the simulated normal temperatures. Severe inconsistencies are noted and discussed. For the U.S.S.R., spring and fall planting dates can probably be estimated accurately from satellite or meteorological data. For the starter model problem, the Feyerherm spring wheat model is recommended for spring planted small grains, and the results of an analysis are presented. For fall planted small grains, use of normal planting dates supplemented by spectral observation of an early stage is recommended. The importance of nonmeteorological factors as they pertain to meteorological factors in determining fall planting is discussed. Crop calendar data available at the Johnson Space Center for the U.S., U.S.S.R., Canada, and other countries are inventoried
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