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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Temporal analysis of multispectral scanner data.

Multispectral scanner reflectance data were sampled for bare soil, cotton, sorghum, corn, and citrus at four dates during a growing season (April, May, June, and July 1969) to develop a time-dependent signature for crop and soil discrimination. Discrimination tests were conducted for single-date and multidate formats using training and test data sets. For classifications containing several crops, the multidate or temporal approach improved discrimination compared with the single-date approach. The multidate approach also preserved recognition accuracy better in going from training fields to test fields than the single-date analysis. The spectral distinctiveness of bare soil versus vegetation resulted in essentially equal discrimination using single-date versus multidate data for those two categories.

Richardson, A. J.↗
NASA NTRS1974

Skylab S192 data evaluation: Comparisons with ERTS-1 results

The author has identified the following significant results. The Skylab S192 data was evaluated by: (1) comparing the classification results using S192 and ERTS-1 data over the Holt County, Nebraska agricultural study area, and (2) investigating the impact of signal-to-noise ratio on classification accuracies using registered S192 and ERTS-1 data. Results indicate: (1) The classification accuracy obtained on S192 data using its best subset of four bands can be expected to be as high as that on ERTS-1 data. (2) When a subset of four S192 bands that are spectrally similar to the ERTS-1 bands was used for classification, an obvious deterioration in the classification accuracy was observed with respect to the ERTS-1 results. (3) The thermal bands 13 and 14 as well as the near IR bands were found to be relatively important in the classification of agricultural data. Although bands 11 and 12 were highly correlated, both were invariably included in the best subsets of the band sizes, four and beyond, according to the divergence criterion. (4) The differentiation of corn from popcorn was difficult on both S192 and ERTS-1 data acquired at an early summer date. (5) The results on both sets of data indicate that it was relatively easy to differentiate grass from any other class.

Chang, C. Y.↗
NASA NTRS1974

Reflectance of vegetation, soil, and water

The author has identified the following significant results. Reflectance of crop residues, that are important in reducing wind and water erosion, was more often different from bare soil in band 4 than in bands 5, 6, or 7. The plant parameters leaf area index, plant population, plant cover, and plant height explained 95.9 percent of the variation in band 7 (reflective infrared) digital counts for cotton and 78.2 percent of the variation in digital counts for the combined crops sorghum and corn; hence, measurable plant parameters explain most of the signal variation recorded for corpland. Leaf area index and plant population are both highly correlated with crop yields; since plant population can be readily measured (or possibly inferred from seeding rates), it is useful measurement for calibrating ERTS-type MSS digital data in terms of yield.

Wiegand, C. L.↗
NASA NTRS1974

Absorption characteristics of glass fiber materials at normal and oblique incidence

The absorption characteristics of several fibrous materials of the Owens Corning 700 Fiberglas Series were measured to determine the variation in impedance as a function of incident angle of the sound wave. The results, indicate that the fibrous absorbents behave as extended reacting materials. The poor agreement between measurement and theory for sound absorption based on the parameters of flow resistance and porosity indicates that this theory does not adequately predict the acoustic behavior of fibrous materials. A much better agreement with measured results is obtained for values calculated from the bulk acoustic parameters of the material.

Wyerman, B. R.↗
NASA NTRS1974

Utilizing ERTS imagery to detect plant diseases and nutrient deficiencies, soil types and soil moisture levels

The author has identified the following significant results. ERTS-1 imagery may be used to delineate soil associations. It does have the capacity to divide soils into groups such that their land use and management would be similar. It offers definite potential for making grass flood-plain, wetland, river shoreline, and land use change surveys. Production of volume strata and forest type from the two usable bands of ERTS-1 imagery were of questionable value. No imagery was received for evaluation during the time of year when maine dwarf mosaic virus and southern corn leaf blight were active.

Parks, W. L.↗
NASA NTRS1974

Reflectance of vegetation, soil, and water

The author has identified the following significant results. The Kubelka-Munk model, a regression model, and a combination of these models were used to extract plant, soil, and shadow reflectance components of vegetated surfaces. The combination model was superior to the others; it explained 86% of the variation in band 5 reflectance of corn and sorghum, and 90% of the variation in band 6 reflectance of cotton. A fractional shadow term substantially increased the proportion of the digital count sum of squares explained when plant parameters alone explained 85% or less of the variation. Overall recognition of 94 agricultural fields using simultaneously acquired aircraft and spacecraft MSS data was 61.8 and 62.8%, respectively; recognition of vegetable fields larger than 10 acres and taller than 25 cm, rose to 88.9 and 100% for aircraft and spacecraft, respectively. Agriculture and rangeland, were well discriminated for the entire county but level 2 categories of vegetables, citrus, and idle cropland, except for citrus, were not.

Wiegand, C. L.↗
NASA NTRS1974

Research in remote sensing of agriculture, earth resources, and man's environment

Research performed on NASA and USDA remote sensing projects are reviewed and include: (1) the 1971 Corn Blight Watch Experiment; (2) crop identification; (3) soil mapping; (4) land use inventories; (5) geologic mapping; and (6) forest and water resources data collection. The extent to which ERTS images and airborne data were used is indicated along with computer implementation. A field and laboratory spectroradiometer system is described together with the LARSYS software system, both of which were widely used during the research. Abstracts are included of 160 technical reports published as a result of the work.

Landgrebe, D. A.↗
NASA NTRS1974

Crop identification and acreage measurement utilizing ERTS imagery

The Statistical Reporting Service of the U.S. Department of Agriculture is evaluating ERTS-1 imagery as a potential tool for estimating crop acreage. A main data source for the estimates is obtained by enumerating small land parcels that have been randomly selected from the total U.S. land area. These small parcels are being used as ground observations in this investigation. The test sites are located in Missouri, Kansas, Idaho, and South Dakota. The major crops of interest are wheat, cotton, corn, soybeans, sugar beets, potatoes, oats, alfalfa, and grain sorghum. Some of the crops are unique to a given site while others are common in two or three states. This provides an opportunity to observe crops grown under different conditions. Results for the Missouri test site are presented. Results of temporal overlays, unequal prior probabilities, and sample classifiers are discussed. The amount of improvement that each technique contributes is shown in terms of overall performance. The results show that useful information for making crop acreage estimates can be obtained from ERTS-1 data.

Wigton, W. H.↗
NASA NTRS1974

Analysis of multispectral signatures and investigation of multi-aspect remote sensing techniques

Two major aspects of remote sensing with multispectral scanners (MSS) are investigated. The first, multispectral signature analysis, includes the effects on classification performance of systematic variations found in the average signals received from various ground covers as well as the prediction of these variations with theoretical models of physical processes. The foremost effects studied are those associated with the time of day airborne MSS data are collected. Six data collection runs made over the same flight line in a period of five hours are analyzed, it is found that the time span significantly affects classification performance. Variations associated with scan angle also are studied. The second major topic of discussion is multi-aspect remote sensing, a new concept in remote sensing with scanners. Here, data are collected on multiple passes by a scanner that can be tilted to scan forward of the aircraft at different angles on different passes. The use of such spatially registered data to achieve improved classification of agricultural scenes is investigated and found promising. Also considered are the possibilities of extracting from multi-aspect data, information on the condition of corn canopies and the stand characteristics of forests.

Malila, W. A.↗
NASA NTRS1974

Dimensional stability of fused silica and several ultralow expansion materials

Description of a program of measurements of the dimensional stability of fused silica and several ultralow thermal expansion materials. The two techniques used are: (1) Fizeau interferometry employed by NBS-Corning, and (2) Fabry-Perot interferometry employed by the Optical Science Center, University of Arizona. In the latter, a measurement accuracy of one part in a billion is sought.

Jacobs, S. F.↗
NASA NTRS1974

Effective use of ERTS multisensor data in the Northern Great Plains

The author has identified the following significant results. ERTS imagery was used as a tool in the identification and refinement of soil association areas; to classify land use patterns between crop and fallow fields; to identify corn, soybeans, and oats; and to identify broad generalized range ecosystems. Various data handling techniques were developed and applied to accomplish these tasks. A map outlining soil associations and relative land values was completed on a base mosaic of ERTS imagery and is included as an appendix to the report.

Myers, V. I.↗
NASA NTRS1974

The ERTS-1 investigation (ER-600). Volume 1: ERTS-1 agricultural analysis

The Agriculture Analysis Team of the Johnson Space Center conducted a 1-year-long investigation of ERTS-1 multispectral data to evaluate how well features of agricultural importance could be detected, identified, and located; and their areal extent measured. Six study areas were selected in cooperation with the U.S. Department of Agriculture. Two basic analytical approaches were used to meet the objectives. The conventional image interpretation technique revealed that a particular color was an indication of the density of vegetative cover, not an indication of crop classification. Computer-aided techniques were used to classify crop types (i.e., small grains, truck farm crops, grasses, summer fallow) to accuracies as high as 95 percent on large (12 hectares or more) well-defined fields. A further breakdown into crop species (wheat, barley, soybeans, oats, corn) reduced the accuracy to 70 to 80 percent for single-date observations.

Erb, R. B.↗
NASA NTRS1974

The effects of soil moisture and plant morphology on the radar backscatter from vegetation

The results of experimental studies on the backscattering properties of corn, milo, soybeans and alfalfa are presented. The measurements were made during the summer of 1973 over the 8 to 18 GHz frequency band. The data indicate that soil moisture estimation is best accomplished at incidence angles near nadir with lower frequencies, while crop discrimination is best accomplished using two frequencies at incidence angles ranging from 30 deg to 65 deg. It is also shown that temporal plant morphology variations can cause extreme variations in the values of the scattering coefficients. These morphological changes can be caused by growth, heavy rain and in the case of alfalfa, harvesting.

Ulaby, F. T.↗
NASA NTRS1975

Developing processing techniques for Skylab data

The author has identified the following significant results. The effects of misregistration and the scan-line-straightening algorithm on multispectral data were found to be: (1) there is greatly increased misregistration in scan-line-straightening data over conic data; (2) scanner caused misregistration between any pairs of channels may not be corrected for in scan-line-straightened data; and (3) this data will have few pure field center pixels than will conic data. A program SIMSIG was developed implementing the signature simulation model. Data processing stages of the experiment were carried out, and an analysis was made of the effects of spatial misregistration on field center classification accuracy. Fifteen signatures originally used for classifying the data were analyzed, showing the following breakdown: corn (4 signatures), trees (2), brush (1), grasses, weeds, etc. (5), bare soil (1), soybeans (1), and alfalfa (1).

Nalepka, R. F.↗
NASA NTRS1975

Development and test of video systems for airborne surveillance of oil spills

Five video systems - potentially useful for airborne surveillance of oil spills - were developed, flight tested, and evaluated. The systems are: (1) conventional black and white TV, (2) conventional TV with false color, (3) differential TV, (4) prototype Lunar Surface TV, and (5) field sequential TV. Wavelength and polarization filtering were utilized in all systems. Greatly enhanced detection of oil spills, relative to that possible with the unaided eye, was achieved. The most practical video system is a conventional TV camera with silicon-diode-array image tube, filtered with a Corning 7-54 filter and a polarizer oriented with its principal axis in the horizontal direction. Best contrast between oil and water was achieved when winds and sea states were low. The minimum detectable oil film thickness was about 0.1 micrometer.

Millard, J. P.↗
NASA NTRS1975

Crop identification technology assessment for remote sensing (CITARS). Volume 6: Data processing at the laboratory for applications of remote sensing

The results of classifications and experiments for the crop identification technology assessment for remote sensing are summarized. Using two analysis procedures, 15 data sets were classified. One procedure used class weights while the other assumed equal probabilities of occurrence for all classes. Additionally, 20 data sets were classified using training statistics from another segment or date. The classification and proportion estimation results of the local and nonlocal classifications are reported. Data also describe several other experiments to provide additional understanding of the results of the crop identification technology assessment for remote sensing. These experiments investigated alternative analysis procedures, training set selection and size, effects of multitemporal registration, spectral discriminability of corn, soybeans, and other, and analyses of aircraft multispectral data.

Bauer, M. E.↗
NASA NTRS1974

The effect of atmospheric water vapor on automatic classification of ERTS data

Absorption by atmospheric water vapor changes the spectral signatures collected by multispectral scanners if channels are not chosen to avoid the atmospheric water bands. For ERTS (Earth Resources Technology Satellite), the Multispectral Scanner band 7 (MSS 7, .8 to 1.1 micron) is the only band significantly affected. Line-by-line atmospheric absorption calculations showed that this effect can multiply the intensity by factors ranging from .77 to 1.0. If horizontal gradients in atmospheric water exist between training fields and the rest of the scene, errors are introduced in automatic classification of the imagery. The degradation of the classification of corn and soybeans was determined by using actual ERTS data and simulating the absorption effects on the MSS 7 band.

Pitts, D. E.↗
NASA NTRS1974

Statistical separability of agricultural cover types in subsets of one to twelve spectral channels

The purpose of this study was to determine the statistical separability of multispectral measurements from agricultural cover types: corn, soybeans, green forage (hay and pasture) and forest, in one to twelve spectral channels. Multispectral scanner data in twelve spectral channels in the wavelength range 0.4 to 11.7 microns, acquired for three flightlines were analysed by applying automatic pattern recognition techniques. The same analysis was performed for the data acquired a month later over the same three flightlines to investigate the effect of time on statistical separability of agricultural cover types. In the subsets of one to six spectral channels, the combination of wavelength regions (where V, N, M and T denote the visible, near infrared, middle infrared and thermal infrared wavelength regions, respectively): V, V M, V N M, V N M T, V V N M T, V V N M M T, respectively, were found to be the best choices for getting good overall statistical separability of the agricultural cover types for the data acquired.

Kumar, R.↗