Search NASA⌕ Search

SEARCH · Search NASA

Results for “corn”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

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.↗

Multi-aspect techniques in remote sensing

Multi-aspect techniques, which use multispectral scanner information collected from two or more different view angles for each spatial element, are discussed. Empirical recognition results obtained with various combinations of information channels are presented. Theoretical calculations of multi-aspect reflectances of corn fields also are analyzed and compared with empirical data. Also presented is a brief comparison between recognition processing and scene attribute estimation techniques for extracting information from multispectral scanner data. One method for improving information extraction by employing a post-recognition attribute estimation procedure is suggested.

Malila, W. A.↗

Radar response to vegetation

Active microwave measurements of vegetation backscatter were conducted to determine the utility of radar in mapping soil moisture through vegetation and mapping crop types. Using a truck-mounted boom, spectral response data were obtained for four crop types (corn, milo, soybeans, and alfalfa) over the 4-8 GHz frequency band, at incidence angles of 0 to 70 degrees in 10-degree steps, and for all four linear polarization combinations. Based on a total of 125 data sets covering a wide range of soil moisture, content, system design criteria are proposed for each of the aforementioned objectives. Quantitative soil moisture determination was best achieved at the lower frequency end of the 4-8 GHz band using HH polarized waves in the 5- to 15-degree incidence angle range. A combination of low and high frequency measurements are suggested for classifying crop types. For crop discrimination, a dual-frequency dual-polarization (VV and cross) system operating at incidence angles above 40 degrees is suggested.

Ulaby, F. T.↗

Vegetation and soil backscatter over the 4-18 GHz region

Using an FM-CW radar mounted atop a truck-mounted boom, 4-8 GHz backscatter spectral data was gathered during the 1972 growing season at incidence angles of 0-70 deg in 10 deg steps for each of the four linear polarization combinations. The data covers four mature crop types (corn, milo, soybeans and alfalfa) and bare ground taken under a wide range of soil and plant moisture contents. To insure statistical representation of the results, measurements were conducted over 147 fields corresponding to a total of about 50,000 data points. During 1973, a higher frequency version of the above system was used to collect additional data over the 8-18 GHz frequency region. This paper presents a summary of the results and suggests design criteria for future radar remote sensing missions.

Ulaby, F. T.↗

Trace elements by instrumental neutron activation analysis for pollution monitoring

Methods and technology were developed to analyze 1000 samples/yr of coal and other pollution-related samples. The complete trace element analysis of 20-24 samples/wk averaged 3-3.5 man-hours/sample. The computerized data reduction scheme could identify and report data on as many as 56 elements. In addition to coal, samples of fly ash, bottom ash, crude oil, fuel oil, residual oil, gasoline, jet fuel, kerosene, filtered air particulates, ore, stack scrubber water, clam tissue, crab shells, river sediment and water, and corn were analyzed. Precision of the method was plus or minus 25% based on all elements reported in coal and other sample matrices. Overall accuracy was estimated at 50%.

Sheibley, D. W.↗

Radar response to vegetation. II - 8-18 GHz band

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 8-18 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.↗

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.↗

Crop Identification Technolgy Assessment for Remote Sensing (CITARS). Volume 1: Task design plan

A plan for quantifying the crop identification performances resulting from the remote identification of corn, soybeans, and wheat is described. Steps for the conversion of multispectral data tapes to classification results are specified. The crop identification performances resulting from the use of several basic types of automatic data processing techniques are compared and examined for significant differences. The techniques are evaluated also for changes in geographic location, time of the year, management practices, and other physical factors. The results of the Crop Identification Technology Assessment for Remote Sensing task will be applied extensively in the Large Area Crop Inventory Experiment.

Hall, F. G.↗

Crop Identification Technology Assessment for Remote Sensing (CITARS)

The results of classifications and experiments performed for the Crop Identification Technology Assessment for Remote Sensing (CITARS) project are summarized. Fifteen data sets were classified using two analysis procedures. One procedure used class weights while the other assumed equal probabilities of occurrence for all classes. In addition, 20 data sets were classified using training statistics from another segment or date. The results of both the local and non-local classifications in terms of classification and proportion estimation are presented. Several additional experiments are described which were performed to provide additional understanding of the CITARS results. These experiments investigated alternative analysis procedures, training set selection and size, effects of multitemporal registration, the spectral discriminability of corn, soybeans, and other, and analysis of aircraft multispectral data.

Bauer, M. E.↗

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.↗

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.↗

Results from the crop identification technology assessment for remote sensing /CITARS/ project

The CITARS (Crop Identification Technology Assessment for Remote Sensing) task design, objectives, and results are reviewed along with relevant conclusions and recommendations. The principal assessment concern crop identification performance for corn and soybeans in six sites in Illinois and Indiana. Use of quantitative measures of classification performance and statistical evaluations of the results have been important parts of the technology assessment. Relation of crop and sensor characteristics is discussed. Factors affecting crop identification performance are identified as crop maturity and site characteristics, type of single-date automatic data processing procedure used for local recognition, nonlocal recognition with and without processing for extension of recognition signatures, and use of multidate or multitemporal data. In particular, the probability of correct classification of field center pixels is not well correlated and thus is not a reliable indicator of proportion estimation performance.

Bizzell, R. M.↗

Ultraprecise thermal expansion measurements of seven low expansion materials

We summarize a large number of ultraprecise thermal expansion measurements made on seven different low expansivity materials. Expansion coefficients in the -150-300 C temperature range are shown for Owens-Illinois Cer-Vit C-101, Corning ULE 7971 (titanium silicate) and fused silica 7940, Heraeus-Schott Zerodur low-expansion material and Homosil fused silica, Universal Cyclops Invar LR-35, and Simonds Saw and Steel Super Invar.

Berthold, J. W., III↗

Economic evaluation of crop acreage estimation by multispectral remote sensing

The author has identified the following significant results. Photointerpretation of S190A and S190B imagery showed significantly better resolution with the S190B system. A small tendancy to underestimate acreage was observed. This averaged 6 percent and varied with field size. The S190B system had adequate resolution for acreage measurement but the color film did not provide adequate contrast to allow detailed classification of ground cover from imagery of a single date. In total 78 percent of the fields were correctly classified but with 56 percent correct for the major crop, corn.

Manderscheid, L. V.↗

Investigation of LANDSAT follow-on thematic mapper spatial, radiometric and spectral resolution

The author has identified the following significant results. Fine resolution M7 multispectral scanner data collected during the Corn Blight Watch Experiment in 1971 served as the basis for this study. Different locations and times of year were studied. Definite improvement using 30-40 meter spatial resolution over present LANDSAT 1 resolution and over 50-60 meter resolution was observed, using crop area mensuration as the measure. Simulation studies carried out to extrapolate the empirical results to a range of field size distributions confirmed this effect, showing the improvement to be most pronounced for field sizes of 1-4 hectares. Radiometric sensitivity study showed significant degradation of crop classification accuracy immediately upon relaxation from the nominally specified values of 0.5% noise equivalent reflectance. This was especially the case for data which were spectrally similar such as that collected early in the growing season and also when attempting to accomplish crop stress detection.

Nalepka, R. F.↗

Crop identification and area estimation over large geographic areas using LANDSAT MSS data

The author has identified the following significant results. LANDSAT MSS data was adequate to accurately identify wheat in Kansas; corn and soybean estimates in Indiana were less accurate. Computer-aided analysis techniques were effectively used to extract crop identification information from LANDSAT data. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels. Training statistics were successfully extended from one county to other counties having similar crops and soils if the training areas sampled the total variation of the area to be classified.

Bauer, M. E.↗

Interpretation of Pennsylvania agricultural land use from ERTS-1 data

The author has identified the following significant results. To study the complex agricultural patterns in Pennsylvania, a portion of an ERTS scene was selected for detailed analysis. Various photographic products were made and were found to be only of limited value. This necessitated the digital processing of the ERTS data. Using an unsupervised classification procedure, it was possible to delineate the following categories: (1) forest land with a northern aspect, (2) forest land with a southern aspect, (3) valley trees, (4) wheat, (5) corn, (6) alfalfa, grass, pasture, (7) disturbed land, (8) builtup land, (9) strip mines, and (10) water. These land use categories were delineated at a scale of approximately 1:20,000 on the line printer output. Land use delineations were also made using the General Electric IMAGE 100 interactive analysis system.

Mcmurtry, G. J.↗

Agreste programme. Part 2: French test sites

The author has identified the following significant results. Results show that the available timber is decreasing after 1980. This comes from the corn extension program. Timber volume evaluations are given by biometrical connections between the mean surface of poplar crowns in a plantation and the mean circumference of the same trees taken at 1.30 m. LANDSAT imagery was found sufficient for large field discrimination, but small parcels like market-gardens are not discernible. Discrete operators were used to smooth, sharpen, or detect edges of digital pictures.

Flouzat, G.↗