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Wiegand, C. L.

Publications and source records attributed to Wiegand, C. L..

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Distinguishing vegetation from soil background information

In aircraft and satellite multispectral scanner data, soil background signals are superimposed on or intermingled with information about vegetation. A procedure which accounts for soil background would, therefore, make a considerable contribution to an operational use of Landsat and other spectral data for monitoring the productivity of range, forest, and crop lands. A description is presented of an investigation which was conducted to obtain information for the development of such a procedure. The investigation included a study of the soil reflectance that supplies the background signal of vegetated surfaces. Landsat data as recorded on computer compatible tapes were used in the study. The results of the investigation are discussed, taking into account a study reported by Kauth and Thomas (1976). Attention is given to the determination of Kauth's plane of soils, sun angle effects, vegetation index modeling, and the evaluation of vegetation indexes. Graphs are presented which show the results obtained with a gray mapping technique. The technique makes it possible to display plant, soil, water, and cloud conditions for any Landsat overpass.

Richardson, A. J.↗
NASA NTRS1977

Soil, water, and vegetation conditions in south Texas

The author has identified the following significant results. The best wavelengths in the 0.4 to 2.5 micron interval were determined for detecting lead toxicity and ozone damage, distinguishing succulent from woody species, and detecting silverleaf sunflower. A perpendicular vegetation index, a measure of the distance from the soil background line, in MSS 5 and MSS 7 data space, of pixels containing vegetation was developed and tested as an indicator of vegetation development and crop vigor. A table lookup procedure was devised that permits rapid identification of soil background and green biomass or phenological development in LANDSAT scenes without the need for training data.

Wiegand, C. L.↗
NASA NTRS1976

Soil, water, and vegetation conditions in South Texas

The author has identified the following significant results. Reflectance measurements with a field spectroradiometer on nine dates (between December 9 and April 8) during the growing season of two wheat varieties, Milam and Penjamo, showed that the reflectance curves had the characteristic shape of vegetated surfaces by 4 weeks after the emergence. Green light (0.55 micron) reflectance was maximal and between water absorption bands (1.65 and 2.2 microns) reflectance was minimal when green vegetation development was greatest. Computer classification was accomplished for 81,000 hectare coastal rangeland area for October 13 and December 10, 1975, overpass dates. A hard freeze occurred between these two dates and many of the deciduous woody species defoliated so that more light penetrated to the herbaceous understory in December than in October.

Wiegand, C. L.↗
NASA NTRS1976

Soil, water, and vegetation conditions in south Texas

The author has identified the following significant results. Field spectral measurements and laboratory densitometric measurements showed that tree canopy reflectance differences among the Marrs, Redblush, and Valencia varieties in the visible spectral region were due to their different leaf chlorophyll concentrations. Field measurements of visible light reflectance were directly related to the tonal responses on infrared color photos of the varietal tree canopies. Consequently, densitometric measurements of the foliage on the infrared color transparency with red-filtered light successfully discriminated among the three varieties. Reflectance measurements with a field spectroradiometer on nine dates the growing season of two wheat varieties, Milam and Penjamo, documented their spectra over the 0.45 to 2.50 micron wavelength interval associated with plant cover and physiological development. An image analyzer system was used to optically planimeter the percentage of soil background, vegetation and shadow in the vertical photographs taken within the FOV of the spectroradiometer on each measurement date.

Wiegand, C. L.↗
NASA NTRS1976

Soil, water, and vegetation conditions in south Texas

The author has identified the following significant results. Software development for a computer-aided crop and soil survey system is nearing completion. Computer-aided variety classification accuracies using LANDSAT-1 MSS data for a 600 hectare citrus farm were 83% for Redblush grapefruit and 91% for oranges. These accuracies indicate that there is good potential for computer-aided inventories of grapefruit and orange citrus orchards with LANDSAT-type MSS data. Mean digital values of clouds differed statistically from those for crop, soil, and water entities, and those for cloud shadows were enough lower than sunlit crop and soil to be distinguishable. The standard errors of estimate for the calibration of computer compatible tape coordinate system (pixel and record) to earth coordinate system (longitude and latitude) for 6 LANDSAT scenes ranged from 0.72 to 1.50 pixels and from 0.58 to 1.75 records.

Wiegand, C. L.↗
NASA NTRS1976

Ground cover estimated from aerial photographs

Estimates of per cent ground cover made by ground observers were compared with independent estimates made on the basis of low-altitude (640-1219 m) aerial photographs of the same fields. Standard statistical simple correlation and linear regression analyses revealed a high correlation between the two estimation methods. In crops such as grain, sorghum, corn, and forage sorghum, in which the broadest part of the leaf canopy is near the top of the plant, there was a tendency to overestimate the per cent ground cover from aerial photographs.

Gerbermann, A. H.↗
NASA NTRS1976

Soil, Water, and Vegetation Conditions in South Texas

The author has identified the following significant results. Reflectance differences between the dead leaves of six crops (corn, cotton, sorghum, sugar cane, citrus, and avocado) and the respective bare soils where the dead leaves were lying on the ground were determined from laboratory spectrophotometric measurements over the 0.5- to 2.5 micron wavelength interval. The largest differences were in the near infrared waveband 0.75- to 1.35 microns. Leaf area index was predicted from plant height, percent ground cover, and plant population for irrigated and nonirrigated grain sorghum fields for the 1975 growing season.

Wiegand, C. L.↗
NASA NTRS1975

Plant, soil, and shadow reflectance components of row crops

Data from the first Earth Resource Technology Satellite (LANDSAT-1) multispectral scanner (MSS) were used to develop three plant canopy models (Kubelka-Munk (K-M), regression, and combined K-M and regression models) for extracting plant, soil, and shadow reflectance components of cropped fields. The combined model gave the best correlation between MSS data and ground truth, by accounting for essentially all of the reflectance of plants, soil, and shadow between crop rows. The principles presented can be used to better forecast crop yield and to estimate acreage.

Richardson, A. J.↗
NASA NTRS1975

Soil, water, and vegetation conditions in south Texas

The author has identified the following significant results. To distinguish dead from live vegetation, spectrophotometrically measured infinite reflectance of dead and live corn (Zea mays L.) leaves were compared over the 0.5 to 2.5 micron waveband. Dead leaf reflectance was reached over the entire 0.5 to 2.5 micron waveband by stacking only two to three leaves. Live leaf reflectance was attained by stacking two leaves for the 0.5 to 0.75 micron waveband (chlorophyll absorption region), eight leaves for the 0.75 to 1.35 micron waveband (near infrared region), and three leaves for the 1.35 to 2.5 micron waveband (water absorption region). LANDSAT-1 MSS digital data for 11 December 1973 overpass were used to estimate the sugar cane acreage in Hidalgo County. The computer aided estimate was 22,100 acres compared with the Texas Crop and Livestock Reporting Service estimate of 20,500 acres for the 1973-'74 crop year. Although there were errors of omission from harvested fields that were identified as bare soil and some citrus and native vegetation that were mistakenly identified as sugar cane, the mapped location of sugar cane fields in the county compared favorably with their location on the thematic map generated by the computer.

Wiegand, C. L.↗
NASA NTRS1975

Soil salinity detection

The author has identified the following significant results. Growth forms and herbage biomass production varied considerably among saline and nonsaline soil range sites in Starr County. Grasses on saline soil sites were shallow-rooted and short whereas on nonsaline sites there was an intermixture of short and midgrass species. Differentiation between primarily undisturbed saline and nonsaline rangelands, in Starr County, is partially possible using film optical density readings from Skylab imagery. Differentiation among eight saline and nonsaline soil sites in Cameron County, using black and white and color film was not possible according to statistical results from both DMRT and correlation analysis. Linear analysis showed that Bendix 24-band MSS data (aircraft) collected at 1700 m and 4800 m, as well as Skylab and LANDSAT-1 MSS data, were significantly correlated to electrical conductivity readings. In Starr County, the best spectral band for detection of saline soil levels, using black and white SO-022 film, was in the 0.6 to 0.7 micron spectral region. In Cameron County, the best spectral bands for detection of saline soil levels were the 2.3 to 2.43 micron, 0.72 to 0.76 micron, 0.69 to 1.75 micron, and 0.7 to 1.1 micron spectral regions.

Wiegand, C. L.↗
NASA NTRS1975

Irrigation scheduling, freeze warning and soil salinity detecting

The author has identified the following significant results. Correlations of multispectral scanner (MSS) digital data differences between vegetated and bare soil areas with salinity levels from the eight saline areas using MSS bands seven and ten in the infrared region were significant. Correlations were derived for Cameron County, Texas. Detection of saline soils may be possible, using either film density readings or multispectral scanner data, when the lower reflectance of vegetation on highly saline soil and the higher reflectance of vegetation on lower saline soil are considered by using film on MSS contrasts between vegetation and bare soil.

Wiegand, C. L.↗
NASA NTRS1975

Pattern recognition of soils and crops from space

An evaluation is conducted of the relative effectiveness of the computer analysis techniques which are commonly employed to extract land use (crop identification) information from digitized aerial photographs. It is found that the minimum distance to the mean (MDM) algorithm and the maximum likelihood ratio (MLR) can both be used for the successful recognition of land-use patterns. The MDM algorithm is slightly more accurate in cases involving the use of three or more variables. The use of the MLR algorithm, however, is preferable in cases in which less than three variables are employed.

Leamer, R. W.↗