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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Thermography for estimating near-surface soil moisture under developing crop canopies

Previous investigations of thermal infrared techniques using remote sensors (thermography) for estimating soil water content have been limited primarily to bare soil. Ground-based and aircraft investigations were conducted to evaluate the potential for extending the thermography approach to developing crop canopies. A significant exponential relationship was found between the volumetric soil water content in the 0-4 cm soil layer and the diurnal difference between surface soil temperature measured at 0230 and 1330 LST (satellite overpass times of NASA's Heat Capacity Mapping Mission - HCMM). Surface soil temperatures were estimated using minimum air temperature, percent cover of the canopy and remote measurements of canopy temperature. Results of the investigation demonstrated that thermography can potentially be used to estimate soil temperature and soil moisture throughout a complete growing season for a number of different crops and soils.

Heilman, J. L.↗
NASA NTRS1980

Illustration of year-to-year variation in wheat spectral profile crop growth curves

Data previously compiled on the year to year variability of spectral profile crop growth parameters for spring and winter wheat in Kansas, Oklahoma, and the Dakotas were used with a profile model to develop graphs illustrating spectral profile crop growth curves for a number of years and a number of spring and winter wheat segments. These curves show the apparent variability in spectral profiles for wheat from one year to another within the same segment and from one segment to another within the same year.

Gonzalez, P.↗
NASA NTRS1980

Spatial variability of surface temperature as related to cropping practice with implications for irrigation management

Crop stress measured using thermal infrared emission is evaluated with the stress-degree-day (SDD) concept. Throughout the season, the accumulation of SDD during the reproductive stage of growth is inversely related to yield. This relationship is shown for durum wheat, hard red winter wheat, barley, grain sorghum and soybeans. It is noted that SDD can be used to schedule irrigations for maximizing yields and for applying remotely sensed data to management of water resources. An airborne flight with a thermal-IR scanner was used to examine the variability in temperature that may exist from one field to another and to determine realistic within-field temperature variations. It was found that the airborne and the ground-based data agreed very well and that there was less variability in the fields that were completely covered with crops than those of bare soil.

Hatfield, J. L.↗
NASA NTRS1981

Development of rotation sample designs for the estimation of crop acreages

The idea behind the use of rotation sample designs is that the variation of the crop acreage of a particular sample unit from year to year is usually less than the variation of crop acreage between units within a particular year. The estimation theory is based on an additive mixed analysis of variance model with years as fixed effects, (a sub t), and sample units as a variable factor. The rotation patterns are decided upon according to: (1) the number of sample units in the design each year; (2) the number of units retained in the following years; and (3) the number of years to complete the rotation pattern. Different analytic formulae for the variance of (a sub t) and the variance comparisons in using a complete survey of the rotation patterns.

Lycthuan-Lee, T. G.↗
NASA NTRS1981

Evaluation of the Doraiswamy-Thompson winter wheat crop calendar model incorporating a modified spring restart sequence

The Robertson phenology was used to provide growth stage information to a wheat stress indicator mode. A stress indicator model demands two acurate predictions from a crop calendar: date of spring growth initiation; and crop calendar stage at growth initiation. Several approaches for restarting the Robertson phenology model at spring growth initiation were studied. Although best results were obtained with a solar thermal unit method, an alternate approach which indicates soil temperature as the controlling parameter for spring growth initiation was selected and tested. The modified model (Doraiswamy-Thompson) is compared to LACIE-Robertson model predictions.

Taylor, T. W.↗
NASA NTRS1981

Analysis of scanner data for crop inventories

Progress and technical issues are reported in the development of corn/soybeans area estimation procedures for use on data from South America, with particular emphasis on Argentina. Aspects related to the supporting research section of the AgRISTARS Project discussed include: (1) multisegment corn/soybean estimation; (2) through the season separability of corn and soybeans within the U.S. corn belt; (3) TTS estimation; (4) insights derived from the baseline corn and soybean procedure; (5) small fields research; and (6) simulating the spectral appearance of wheat as a function of its growth and development. To assist the foreign commodity production forecasting, the performance of the baseline corn/soybean procedure was analyzed and the procedure modified. Fundamental limitations were found in the existing guidelines for discriminating these two crops. The temporal and spectral characteristics of corn and soybeans must be determined because other crops grow with them in Argentina. The state of software technology is assessed and the use of profile techniques for estimation is considered.

Horvath, R.↗
NASA NTRS1981

Ground truth crop proportion summaries for US segments, 1976-1979

The original ground truth data was collected, digitized, and registered to LANDSAT data for use in the LACIE and AgRISTARS projects. The numerous ground truth categories were consolidated into fewer classes of crops or crop conditions and counted occurrences of these classes for each segment. Tables are presented in which the individual entries are the percentage of total segment area assigned to a given class. The ground truth summaries were prepared from a 20% sample of the scene. An analysis indicates that this size of sample provides sufficient accuracy for use of the data in initial segment screening.

Horvath, R.↗
NASA NTRS1982

Second Generation Crop Yield Models Review

Second generation yield models, including crop growth simulation models and plant process models, may be suitable for large area crop yield forecasting in the yield model development project. Subjective and objective criteria for model selection are defined and models which might be selected are reviewed. Models may be selected to provide submodels as input to other models; for further development and testing; or for immediate testing as forecasting tools. A plant process model may range in complexity from several dozen submodels simulating (1) energy, carbohydrates, and minerals; (2) change in biomass of various organs; and (3) initiation and development of plant organs, to a few submodels simulating key physiological processes. The most complex models cannot be used directly in large area forecasting but may provide submodels which can be simplified for inclusion into simpler plant process models. Both published and unpublished models which may be used for development or testing are reviewed. Several other models, currently under development, may become available at a later date.

Hodges, T.↗
NASA NTRS1982

Crop weather models of corn and soybeans for Agrophysical Units (APU's) in Iowa using monthly meteorological predictors

Models based on multiple regression were developed to estimate corn and soybean yield from weather data for agrophysical units (APU) in Iowa. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for crop reporting districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU's were selected to be more homogeneous with respect crop to production than the CRDs. The APU models are quite similar to the CRD models, similar explained variation and number of predictor variables. The APU models are to be independently evaluated and compared to the previously evaluated CRD models. That comparison should indicate the preferred model area for this application, i.e., APU or CRD.

Leduc, S.↗
NASA NTRS1982

A review of crop canopy reflectance models

Various models for calculating crop canopy reflectance, in the visible and infrared wavelengths, from the optical and geometrical properties of a canopy and its constituents are reviewed. The radiative transfer equation is discussed as well as both analytical and numerical crop reflectance models which are manifestations of the solution of this equation. Recommendations are made for further work in modeling of canopy reflectance.

Goel, N. S.↗
NASA NTRS1981

Crop-phenology and LANDSAT-based irrigated lands inventory in the high plains

Crop calendars for 1979 and 1980 were investigated in support of an effort to develop techniques for mapping the High Plains aquifer region. Optimal LANDSAT image dates for 1980 were preliminarily identified based on ESS weekly crop weather reports and 1979 ESS agricultural statistics were entered into the computer. A questionnaire was compiled and sent to ASCS county agents with the approval of the Extension Directors in each state involved. Data from returning questionnaires were tabulated and development started on a set of computer programs to allow the preparation of computer assisted graphic displays of much of the collected data.

Martinko, E. A.↗
NASA NTRS1983

Area estimation using multiyear designs and partial crop identification

Progress is reported for the following areas: (1) estimating the stratum's crop acreage proportion using the multiyear area estimation model; (2) assessment of multiyear sampling designs; and (3) development of statistical methodology for incorporating partially identified sample segments into crop area estimation.

Sielken, R. L., Jr.↗
NASA NTRS1982

Australia ground data collection 1981-82 crop year, volume 1

Under AgRISTARS management, ground data were collected at 20 agricultural sites within Australia during the crop year 1981-82. The data collection activity is summarized. Specifically, the following information is provided: discussion of data procedures, methods, and products; crop production results; photographs of the Australia agriculture scene, map sheets of segments, LANDSAT full frames, and aerial photographs of data collection areas; and summarizations of district agronomist reports.

Quinones, C. R.↗
NASA NTRS1983

A concept for global crop forecasting

The mission, instrumentation, and design concepts for microwave radiometer satellites for continuous crop condition forecasting and monitoring on a global basis are described. Soil moisture affects both crop growth and the dielectric properties of the soil, and can be quantified by analysis of reflected radiance passively received by orbiting spacecraft. A dedicated satellite reading a swath 200 km across, with 1 km and 1 K temperature resolution, could track the time-varying changes of solid moisture, sea ice, and water surface temperature. Launched by the Shuttle into an interim orbit, a boost would place the satellite in a 400 or 700 km orbit. Resolution requirements indicate a 45-725 m diam antenna, with 70 dB gain, operating at frequencies of 1.08, 2.03, and 4.95 GHz to ensure atmospheric transparency. Alternative structural concepts include either double-layer tetrahedral or single-layer geodesic trusses as the basic structural members. An analysis of the electrostatic positioning of the parabolic antenna membrane is outlined.

Lovelace, U. M.↗
NASA NTRS1983

Directional radiometric measurements of row-crop temperatures

The variability of directional sensor response for a cotton row crop in Phoenix, Arizona was measured for various solar zenith angles. The geometric structure of the canopy was described with regard to height, width, spacing, and shape of rows. In addition, radiometric temperature data were collected on four scene components: sunlit and shaded vegetation and sunlit and shaded soil. These data were used to test the predictions and assumptions of a modified version of the row crop model of Jackson et al. (1979), which predicts the thermal infrared response of a sensor as a function of sensor view angle, component temperature, and geometrical structure of the canopy. The field data showed sensor response differentials as great as 16.2 C when going from a zenith view angle of 0 deg to one of 80 deg normal to the row direction. The rms deviation between the predicted and measured sensor response for all measurement periods and view angles was 0.96 C.

Kimes, D. S.↗