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At least 163 records · Page 9

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NASA NTRS1982

Development, implementation and evaluation of satellite-aided agricultural monitoring systems

Research activities in support of AgRISTARS Inventory Technology Development Project in the use of aerospace remote sensing for agricultural inventory described include: (1) corn and soybean crop spectral temporal signature characterization; (2) efficient area estimation techniques development; and (3) advanced satellite and sensor system definition. Studies include a statistical evaluation of the impact of cultural and environmental factors on crop spectral profiles, the development and evaluation of an automatic crop area estimation procedure, and the joint use of SEASAT-SAR and LANDSAT MSS for crop inventory.

Cicone, R. C.↗

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 NTRS1982

Labeling research in support of through-the-season area estimation

The development of LANDSAT-based through-the-season labeling procedures for corn and soybeans is discussed. A model for predicting labeling accuracy within key time periods throughout the growing season is outlined. Two methods for establishing the starting point of one key time period, viz., early season, are described. In addition, spectral-temporal characteristics for separating crops in the early season time period are discussed.

Colwell, R. N.↗

NASA NTRS1982

Development, implementation and evaluation of satellite-aided agricultural monitoring systems

Research supporting the use of remote sensing for inventory and assessment of agricultural commodities is summarized. Three task areas are described: (1) corn and soybean crop spectral/temporal signature characterization; (2) efficient area estimation technology development; and (3) advanced satellite and sensor system definition. Studies include an assessment of alternative green measures from MSS variables; the evaluation of alternative methods for identifying, labeling or classification targets in an automobile procedural context; a comparison of MSS, the advanced very high resolution radiometer and the coastal zone color scanner, as well as a critical assessment of thematic mapper dimensionally and spectral structure.

Cicone, R.↗

NASA NTRS1982

A model for microwave emission from vegetation-covered fields

The measured brightness temperatures over vegetation-covered fields are simulated by a radiative transfer model which treats the vegetation as a uniform canopy with a constant temperature, over a moist soil which emits polarized microwave radiation. The analytic formula for the microwave emission has four parameters: roughness height, polarization mixing factor, effective canopy optical thickness, and single scattering albedo. A good representation has been obtained with the model for both the horizontally and vertically polarized brightness temperatures at 1.4 and 5 GHz frequencies, over fields covered with grass, soybean and corn. A directly proportional relation is found between effective canopy optical thickness and the amount of water present in the vegetation canopy. The effective canopy single scattering albedo depends on vegetation type.

Mo, T.↗

NASA NTRS1983

Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

Ulaby, F. T.↗

NASA NTRS1982

A study of Minnesota land and water resources using remote sensing

A pilot study of 60 lakes in Minnesota shows that LANDSAT data correlate very well with the Carlson trophic state index which is derived from measurements in the field. Nimbus satellite data reveal improvement in water quality in Lake Superior since the dumping of taconite tailings stopped in 1980. A feasibility study of using color infrared photography as a near real time tool for soil and crop management in corn and soybean areas of the state generated strong interest from farmers and agribusiness firms. The state geological survey had success in the use and applications of LANDSAT images. Subtleties of changes in vegetation, soil, and topography are such that ground water presence and depth to water table are nearly always impossible to qualify except for broad scale applications. Bedrock and structural differences as shown in lineaments offer great potential for resolution of some kinds of geologic studies. A synergistic concept is to be used to search for mineral resources in the northeastern part of the state.

Source record↗

NASA NTRS1983

Crop identification of SAR data using digital textural analysis

After preprocessing SEASAT SAR data which included slant to ground range transformation, registration to LANDSAT MSS data and appropriate filtering of the raw SAR data to minimize coherent speckle, textural features were developed based upon the spatial gray level dependence method (SGLDM) to compute entropy and inertia as textural measures. It is indicated that the consideration of texture features are very important in SAR data analysis. The SEASAT SAR data are useful for the improvement of field boundary definitions and for an earlier season estimate of corn and soybean area location than is supported by LANDSAT alone.

Nuesch, D. R.↗

NASA NTRS1984

Determination of the Sources of Radar Scattering

Fine-resolution radar backscattering measurements were proposed to determine the backscattering sources in various vegetation canopies and surface targets. The results were then used to improve the existing theoretical models of terrain scattering, and also to enhance understanding of the radar signal observed by an imaging radar over a vegetated area. Various experiments were performed on targets such as corn, milo, soybeans, grass, asphalt pavements, soil and concrete walkways. Due to the lack of available references on measurements of this type, the obtained results will be used primarily as a foundation or future experiments. The constituent backscattering characteristics of the vegetation canopies was also examined.

Moore, R. K.↗

NASA NTRS1983

Application of a U.S.-based analysis approach to Argentina crop identification

A generic, U.S.-based analysis approach was evaluated with respect to corn and soybean identification in Argentina. Using crop separability expectations derived from the analysis of Argentina ancillary data and U.S. spectral data, the approach was applied to Argentina spectral data by an expert analyst. Eight classes were detected and labeled independent of ground data. A high correspondence between the labels and limited ground data was achieved. It was concluded that an approach of this type could be applied to Argentina without major difficulty.

Odenweller, J. B.↗

NASA NTRS1982

Research in satellite-aided crop inventory and monitoring

Automated information extraction procedures for analysis of multitemporal Landsat data in non-U.S. crop inventory and monitoring are reviewed. Experiments to develop and evaluate crop area estimation technologies for spring small grains, summer crops, corn, and soybeans are discussed. Previously announced in STAR as N82-32793

Erickson, J. D.↗

NASA NTRS1984

Assessment of technologies for classification of mixed pixels

A new method of directly classifying mixed pixels is described. This method and four frequently used indirect mixed pixel classification techniques are evaluated on Landsat MSS data from the U.S. Corn Belt using an automatic corn and soybean labeling technique. The results indicate that while more sophisticated, physically-based techniques for classsifying mixed pixels may yield a higher Percent Correct Classification (PCC) for those pixels, the net effect on a crop area proportion estimation procedure may be negative.

Metzler, M. D.↗

NASA NTRS1984

Landsat thematic mapper (TM) soil variability analysis over Webster County, Iowa

Thematic mapper simulator (TMS) data acquired June 7, June 23, and July 31, 1982, and Landsat thematic mapper (TM) data acquired August 2, September 3, and October 21, 1982, over Webster County, Iowa, were examined for within-field soil effects on corn and soybean spectral signatures. It was found that patterns displayed on various computer-generated map products were in close agreement with the detailed soil survey of the area. The difference in spectral values appears to be due to a combination of subtle soil properties and crop growth patterns resulting from the different soil properties. Bands 4 (0.76-.90 micron), 5 (1.55-1.75 micron), and 7 (2.08-2.35 micron) were found to be responding to the within-field soil variability even with increasing ground cover. While these results are preliminary, they do indicate that the soil influence on the vegetation is being detected by TM and should provide improved information relating to crop and soil properties.

Thompson, D. R.↗

NASA NTRS1984

Dynamic descriptors for contextual classification of remotely sensed hyperspectral image data analysis

The extended CIE transformation procedure of Chiou (1984) is applied to five sets of remotely sensed 0.4-2.5-micron spectrometric data on field crops including winter and spring wheat, corn, and soybeans) obtained at the Purdue University Laboratory for Applications of - Remote Sensing during 1977-1980 using the techniques described by Hinzman (1981). The results are presented in tables and chromaticity diagrams and it is found that each crop has an identifiable time-variant spectral characteristic permitting determination of seasonal growth patterns. The applicability of the method to data from airborne and spaceborne imaging spectrometers is indicated.

Chiou, W. C., Sr.↗

NASA NTRS1985

Comparative study of Suits and SAIL canopy reflectance models

A detailed understanding of the relationships between the canopy reflectance and the characteristics of canopy elements is an important factor for the full exploitation of the potential of remote sensing from aircraft and spacecraft altitudes to map vegetation and estimate key agronomic parameters such as the leaf area index (LAI) and biomass (BM). Suits (1972) idealized the canopy geometry by replacing each plant component with three orthogonal projections of that component. Verhoeff and Bunnik (1981) extended the Suits model, henceforth called the SAIL (Scattering from Arbitrarily Inclined Leaves) model, by removing certain constraints. The present investigation is concerned with an evaluation of the performance of the Suits and SAIL models, taking into account two data sets on soybean and corn. It was found that the tested models have significant deficiencies. However, the performance of the SAIL model is better than that of the Suits model because it provides a more realistic description of the canopy architecture.

Badhwar, G. D.↗

NASA NTRS1985

Shortwave infrared detection of vegetation

Shortwave infrared sensors were included on the Thematic Mapper (TM) to observe vegetation reflected radiance patterns related to water leaf content. Analysis of field measurements for corn and soybeans throughout the growing season showed that shortwave infrared measurements enhance discrimination between the species, particularly in midseason. A numerical model of the canopy reflectance showed that differential leaf absorptance can produce the observed patterns. Analysis of coincident studies of leaf optical properties were conducted to generalize the results to other types of vegetation.

Goward, S. N.↗

NASA NTRS1985

Contrasts among bidirectional reflectance of leaves, canopies, and soils

Simple models are presented for predicting the bidirectional reflectance distribution functions (BRDFs) for soils and plant canopies viewed from various directions. BRDFs are predicted for bare soil, individual leaves, and plant canopies, and the results are compared with measurements and a three coefficient empirical equation. BRDF measurements for corn and soybean leaves are presented to contrast with canopy and soil distributions. Estimates of the soil, canopy, and leaf BRDFs are combined into a model called Cupid to predict BRDFs for complex natural surfaces.

Norman, J. M.↗

NASA NTRS1987

Signature-extendable technology - Global space-based crop recognition

The use of signature-extendable technology to improve the efficiency of machine processing of remotely sensed data is examined. Temporal profile technology is employed to automatically recognize crops; the technique uses the Kauth and Thomas (1976) transform of Landsat, multidata, and parameters derived from a model of each crop's greenness-time trajectory. The basic characteristics of temporal profile technology and the U.S. based labeling algorithm are described. Consideration is given to signature extension, signature-extendable spaces, and signature-extendable features. The greenness and brightness parameters used in temporal profile technology are derived. The signature extendability of the parameters is evaluated by applying them to the analysis of corn and soybean crops in the U.S. and Argentina. It is noted that the technique is an affordable and efficient method for deriving data on crops on a global basis.

Hall, Forrest G.↗