Search NASA⌕ Search

SEARCH · Search NASA

Results for “corn and soybean”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Cropland and Land-Clearing Emission Factors From Firex-AQ

The Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign is a NOAA/NASA interagency intensive study of North American fires that took place from July to September 2019. Agricultural fires were sampled on 7 flights from August 21st to September 3rd, 2019. We present emission factors for gas-phase and aerosol-phase species for the different fuel types identified during the campaign. We discuss the dependence of these emission factors on both fuel type and burning characteristics such as modified combustion efficiency (MCE). We analyze 73 fires encompassing four different agricultural fuels (corn, rice, soybean, wheat) and four different types of land-clearing fuels (grass, slash, pile, shrub). Approximately half of all sampled fires were burning corn agricultural residue. We report emission factors for 118 VOCs, where two thirds of emissions are made up of species with lifetimes against oxidation by OH of less than 12 hours (near-field impacts) and the remainder have longer-lifetimes (far-field impacts). We also include an additional 9 aerosol species, 12 halogenated species, 5 sulfur-containing species, and 22 nitrogen-containing species, including NH3 and NOx. There is a statistically significant difference in MCE between agricultural and land-clearing fires that accounts for some of the differences in emission factors across these fuels. VOCs generally have a strong negative correlation with MCE but with different slopes across fuel types. There is a significant positive relationship between MCE and three gas-phase (NO, NO2, SO2) and two aerosol-phase (pCl, pNH4) species. Many emission factors show additional dependence factors beyond MCE that could be related to fuel composition, fire temperature, soil moisture, or other possible differences in burning conditions. Therefore, important differences in emission factors may result when averaging together different types of agricultural and land-clearing fuels in compilations for use in modeling efforts.

biomass burning↗
NASA NTRS1985

Sources of scattering from vegetation canopies at 10 GHz

High-resolution backscatter measurements were made at X-band, with vertical polarization, and incidence angles of 30 and 50 deg, for winter wheat, soybeans, and corn during the summer of 1984. Plants were observed both under natural conditions and with partial-to-complete defoliation. The resolution volume of the measurement system is better than 20 x 20 x 11.25 cu cm within the entire range of measurements. Results are presented as a radar image, which also provides information on the spatial distribution of the (attenuated) scattering inside the canopy observed under natural conditions. Measured results indicate that: (1) for the full-grown wheat plants, heads are the dominant scatterers at the early heading stage and the ground is the dominant scatterer at the later growth stages; (2) for the soybeans, returns are mostly from the upper 30-cm portion of the plants, and leaves and stems dominate the radar signal at 30 and 50 deg incidence angles, respectively; (3) for the corn plants, leaves are the single dominant scatterers at both angles of incidence; and (4) ground returns are relatively unimportant as they are highly attenuated by the vegetation cover.

Wu, L.-K.↗
NASA NTRS1985

Inclusion of specular reflectance in vegetative canopy models

A detailed comparison of the observed soybeans and corn canopy reflectance with that calculated from three vegetative canopy reflectance models have shown systematic angular deviations. A likely cause of these effects is noninclusion of leaf specular reflectance. In this paper a formulation to calculate the component of canopy specular reflectance as a function of incident solar and view zenith angles, leaf area index, leaf angle distribution, and leaf specular reflectance has been developed. The SAIL model has been modified to include this component and the results are compared with an extensive observational data set on soybeans. It is shown that the systematic differences between the SAIL model and observations dependent on scattering azimuth are removed. An analysis of variance shows model improvement of 30 percent over the uncorrected SAIL model.

Reyna, E.↗
NASA NTRS1981

Application of Computer Axial Tomography (CAT) to measuring crop canopy geometry

The feasibility of using the principles of computer axial topography (CAT) to quantify the structure of crop canopies was investigated because six variables are needed to describe the position-orientation with time of a small piece of canopy foliage. Several cross sections were cut through the foliage of healthy, green corn and soybean canopies in the dent and full pod development stages, respectively. A photograph of each cross section representing the intersection of a plane with the foliage was enlarged and the air-foliage boundaries delineated by the plane were digitized. A computer program was written and used to reconstruct the cross section of the canopy. The approach used in applying optical computer axial tomography to measuring crop canopy geometry shows promise of being able to provide needed geometric information for input data to canopy reflectance models. The difficulty of using the CAT scanner to measure large canopies of crops like corn is discussed and a solution is proposed involving the measurement of plants one at a time.

Bauer, M. E.↗
NASA NTRS1982

Estimating acreage by double sampling using LANDSAT data

Double sampling techniques employing LANDSAT data for estimating the acreage of corn and soybeans was investigated and evaluated. The evaluation was based on estimated costs and correlations between two existing procedures having differing cost/variance characteristics, and included consideration of their individual merits when coupled with a fictional 'perfect' procedure of zero bias and variance. Two features of the analysis are: (1) the simultaneous estimation of two or more crops; and (2) the imposition of linear cost constraints among two or more types of resource. A reasonably realistic operational scenario was postulated. The costs were estimated from current experience with the measurement procedures involved, and the correlations were estimated from a set of 39 LACIE-type sample segments located in the U.S. Corn Belt. For a fixed variance of the estimate, double sampling with the two existing LANDSAT measurement procedures can result in a 25% or 50% cost reduction. Double sampling which included the fictional perfect procedure results in a more cost effective combination when it is used with the lower cost/higher variance representative of the existing procedures.

Pont, F.↗
NASA NTRS1984

Modeling the backscattering and transmission properties of vegetation canopies

Experimental measurements of canopy attenuation at 10.2 GHz (X-band) for canopies of wheat and soybeans, experimental observations of the effect upon the microwave backscattering coefficient (sigma) of free water in a vegetation canopy, and experimental measurements of sigma (10.2 GHz, 50 deg, VV and VH polarization) of 30 agricultural fields over the growing season of each crop are discussed. The measurements of the canopy attenuation through wheat independently determined the attenuation resulting from the wheat heads and that from the stalks. An experiment conducted to simulate the effects of rain or dew on sigma showed that sigma increases by about 3 dB as a result of spraying a vegetation canopy with water. The temporal observations of sigma for the 30 agricultural fields (10 each of wheat, corn, and soybeans) indicated fields of the same crop type exhibits similar temporal patterns. Models previously reported were tested using these multitemporal sigma data, and a new model for each crop type was developed and tested. The new models proved to be superior to the previous ones.

Allen, C. T.↗
NASA NTRS1972

A study of the utilization of ERTS-A data from the Wabash River Basin. An early analysis of ERTS-1 data

The author has identified the following significant results. A classification of a portion of frame E-1016-16050 CCT was completed using the LARSYS software. The categories: row crops (corn or soybeans), forest and woodland areas, diverted acres of pastureland or nonproductive grassland areas, water (rivers), clouds, and cloud shadows, were represented by one or more spectral classes. The results of this classification are significant in that they show potential for accurate identification and delineation of forested and agricultural areas using automatic data handling techniques.

Landgrebe, D. A.↗
NASA NTRS1972

Potential benefits of remote sensing: Theoretical framework and empirical estimate

A theoretical framwork is outlined for estimating social returns from research and application of remote sensing. The approximate dollar magnitude is given of a particular application of remote sensing, namely estimates of corn production, soybeans, and wheat. Finally, some comments are made on the limitations of this procedure and on the implications of results.

Eisgruber, L. M.↗
NASA NTRS1973

Identification of agricultural crops by computer processing of ERTS MSS data

Quantitative evaluation of computer-processed ERTS MSS data classifications has shown that major crop species (corn and soybeans) can be accurately identified. The classifications of satellite data over a 2000 square mile area not only covered more than 100 times the area previously covered using aircraft, but also yielded improved results through the use of temporal and spatial data in addition to the spectral information. Furthermore, training sets could be extended over far larger areas than was ever possible with aircraft scanner data. And, preliminary comparisons of acreage estimates from ERTS data and ground-based systems agreed well. The results demonstrate the potential utility of this technology for obtaining crop production information.

Bauer, M. E.↗
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

The CITARS effort by the environmental research institute of Michigan

The objectives of the research task for crop identification technology assessment for remote sensing are outlined. Data gathered by the Landsat 1 multispectral scanner over the U.S. Corn Belt during 1973 is described, and procedures for recognition processing of the data is discussed in detail. The major crops of prime interest were corn and soybeans; they were recognized with different levels of accuracy throughout the growing season, but particularly during late August. Wheat was the major crop of interest in early June.

Malila, W. A.↗
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 NTRS1975

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.↗
NASA NTRS1974

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.↗
NASA NTRS1975

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.↗
NASA NTRS1975

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.↗
NASA NTRS1977

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.↗