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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Mapping Agricultural Crops with AVIRIS Spectra in Washington State

Spectroscopy is used in the laboratory to measure the molecular components and concentrations of plant constituents to answer questions about the plant type, status, and health. Imaging spectrometers measure the upwelling spectral radiance above the Earth's surface as images. Ideally, imaging spectrometer data sets should be used to understand plant type, plant status, and health of plants in an agricultural setting. An Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data set was acquired over agricultural fields near Wallula, Washington on July 23rd, 1997. AVIRIS measures upwelling radiance spectra through 224 spectral channels with contiguous 10-nm sampling from 400 to 2500 nm in the solar-reflected spectrum. The spectra are measured as images of 11 by up to 800 km with 20-m spatial resolution. The spectral images measured by AVIRIS represent the integrated signal resulting from: the solar irradiance; two way transmittance and scattering of the atmosphere; the absorptions and scattering of surface materials; as well as the spectral, radiometric and spatial response functions of AVIRIS. This paper presents initial research to derive properties of the agricultural fields near Wallula from the calibrated spectral images measured by AVIRIS near the top of the atmosphere.

Green, Robert↗
NASA NTRS1973

Identification of agricultural crops by computer processing of ERTS MSS data

Quantitative evaluation of computer-processed ERTS MSS data classifications has shown that major crop species (corn and soybeans) can be accurately identified. The classifications of satellite data over a 2000 square mile area not only covered more than 100 times the area previously covered using aircraft, but also yielded improved results through the use of temporal and spatial data in addition to the spectral information. Furthermore, training sets could be extended over far larger areas than was ever possible with aircraft scanner data. And, preliminary comparisons of acreage estimates from ERTS data and ground-based systems agreed well. The results demonstrate the potential utility of this technology for obtaining crop production information.

Bauer, M. E.↗
NASA NTRS1974

The value of improved (ERS) information based on domestic distribution effects of U.S. agriculture crops

The value of improving information for forecasting future crop harvests was investigated. Emphasis was placed upon establishing practical evaluation procedures firmly based in economic theory. The analysis was applied to the case of U.S. domestic wheat consumption. Estimates for a cost of storage function and a demand function for wheat were calculated. A model of market determinations of wheat inventories was developed for inventory adjustment. The carry-over horizon is computed by the solution of a nonlinear programming problem, and related variables such as spot and future price at each stage are determined. The model is adaptable to other markets. Results are shown to depend critically on the accuracy of current and proposed measurement techniques. The quantitative results are presented parametrically, in terms of various possible values of current and future accuracies.

Bradford, D. F.↗
NASA NTRS1977

Application of remote sensing in South Dakota to provide accurate inventories of agricultural crops, enhance contrast in photographic products, monitor rangeland habitat loss, map Aspen, and prepare hydrogeologic surveys

The author has identified the following significant results. Digital analysis of LANDSAT CCT's indicated that two discrete spectral background zones occurred among the five soil zone. K-CLASS classification of corn revealed that accuracy increased when two background zones were used, compared to the classification of corn stratified by five soil zones. Selectively varying film type developer and development time produces higher contract in reprocessed imagery. Interpretation of rangeland and cropped land data from 1968 aerial photography and 1976 LANDSAT imagery indicated losses in rangeland habitat. Thermal imagery was useful in locating potential sources of sub-surface water and geothermal energy, estimating evapotranspiration, and inventorying the land.

Myers, V. I.↗
NASA NTRS1978

Hand-held radiometer red and photographic infrared spectral measurements of agricultural crops

Red and photographic infrared radiance data, collected under a variety of conditions at weekly intervals throughout the growing season using a hand-held radiometer, were used to monitor crop growth and development. The vegetation index transformation was used to effectively compensate for the different irradiational conditions encountered during the study period. These data, plotted against time, compared the different crops measured by comparing their green leaf biomass dynamics. This approach, based entirely upon spectral inputs, closely monitors crop growth and development and indicates the promise of ground-based hand-held radiometer measurements of crops.

Tucker, C. J.↗
NASA NTRS1979

Identification and area estimation of agricultural crops by computer classification of Landsat MSS data

Landsat Multispectral Scanner (MSS) data covering a three-county area in northern Illinois were classified using computer-aided techniques as corn, soybeans, or 'other.' Recognition of test fields was 80% accurate. County estimates of the area of corn and soybeans agreed closely with those made by the USDA. Results of the use of a priori information in classification, techniques to produce unbiased area estimates, and the use of temporal and spatial features for classification are discussed. The extendability, variability, and size of training sets, wavelength band selection, and spectral characteristics of crops were also investigated.

Bauer, M. E.↗
NASA NTRS1979

Feature extraction applied to agricultural crops as seen by LANDSAT

The physical interpretation of the spectral-temporal structure of LANDSAT data can be conveniently described in terms of a graphic descriptive model called the Tassled Cap. This model has been a source of development not only in crop-related feature extraction, but also for data screening and for haze effects correction. Following its qualitative description and an indication of its applications, the model is used to analyze several feature extraction algorithms.

Kauth, R. J.↗
NASA NTRS1982

Remote sensing of agricultural crops and soils

Research results and accomplishments of sixteen tasks in the following areas are described: (1) corn and soybean scene radiation research; (2) soil moisture research; (3) sampling and aggregation research; (4) pattern recognition and image registration research; and (5) computer and data base services.

Bauer, M. E.↗
NASA NTRS1983

Remote sensing of agricultural crops and soils

Research in the correlative and noncorrelative approaches to image registration and the spectral estimation of corn canopy phytomass and water content is reported. Scene radiation research results discussed include: corn and soybean LANDSAT MSS classification performance as a function of scene characteristics; estimating crop development stages from MSS data; the interception of photosynthetically active radiation in corn and soybean canopies; costs of measuring leaf area index of corn; LANDSAT spectral inputs to crop models including the use of the greenness index to assess crop stress and the evaluation of MSS data for estimating corn and soybean development stages; field research experiment design data acquisition and preprocessing; and Sun-view angles studies of corn and soybean canopies in support of vegetation canopy reflection modeling.

Bauer, M. E.↗
NASA NTRS2016

Developing a Crop Mask for Agricultural Assessments in Kenya

Kenya relies on agricultural production for supporting local consumption and other processing value chains. The role of agriculture in supporting Kenya's economy is critical, with its contribution to the Gross Domestic product (GDP) estimated at over 277,000 Million in 2016. With changing climate in a rain-fed dependent agricultural production system, cropping zones are shifting and proper decision making will require updated data for proper delineation of cropping areas and extent; especially in agriculture and food security assessments. Where up-to-date data is not available it is important that it is generated and passed over to relevant stakeholders to inform their decision making processes. It is important that government agencies, non-governmental agencies and other agricultural stakeholders access updated tools and information to assist in their assessments. To support agricultural decision making, SERVIR E&SA will develop an updated agricultural crop mask. Due to intercropping especially in small holder farming, the mask will cover all crops to provide an overall map of cropped areas.

environment↗