Evaluation of a segment-based Landsat full-frame approach to crop area estimation
(Previously announced in STAR as N82-20590)
Hixon, M. M.↗
Engineering topics
Bauer, M. E.
Publications and source records attributed to Bauer, M. E..
Field research on the spectral properties of crops and soils, volume 1
The experiment design, data acquisition and preprocessing, data base management, analysis results and development of instrumentation for the AgRISTARS Supporting Research Project, Field Research task are described. Results of several investigations on the spectral reflectance of corn and soybean canopies as influenced by cultural practices, development stage and nitrogen nutrition are reported as well as results of analyses of the spectral properties of crop canopies as a function of canopy geometry, row orientation, sensor view angle and solar illumination angle are presented. The objectives, experiment designs and data acquired in 1980 for field research experiments are described. The development and performance characteristics of a prototype multiband radiometer, data logger, and aerial tower for field research are discussed.
Bauer, M. E.↗
Research in the application of spectral data to crop identification and assessment, volume 2
The development of spectrometry crop development stage models is discussed with emphasis on models for corn and soybeans. One photothermal and four thermal meteorological models are evaluated. Spectral data were investigated as a source of information for crop yield models. Intercepted solar radiation and soil productivity are identified as factors related to yield which can be estimated from spectral data. Several techniques for machine classification of remotely sensed data for crop inventory were evaluated. Early season estimation, training procedures, the relationship of scene characteristics to classification performance, and full frame classification methods were studied. The optimal level for combining area and yield estimates of corn and soybeans is assessed utilizing current technology: digital analysis of LANDSAT MSS data on sample segments to provide area estimates and regression models to provide yield estimates.
Daughtry, C. S. T.↗
Effects of management practices on reflectance of spring wheat canopies
The effects of available soil moisture, planting date, nitrogen fertilization, and cultivar on reflectance of spring wheat (Triticum aestivum L.) canopies were investigated. Spectral measurements were acquired on eight dates throughout the growing season, along with measurements of crop maturity stage, leaf area index, biomass, plant height, percent soil cover, and soil moisture. Planting date and available soil moisture were the primary agronomic factors which affected reflectance of spring wheat canopies from tillering to maturity. Comparisons of treatments indicated that during the seedling and tillering stages planting date was associated with 36 percent and 85 percent of variation in red and near infrared reflectances, respectively. As the wheat headed and matured, less of the variation in reflectance was associated with planting date and more with available soil moisture. By mid July, soil moisture accounted for 73 percent and 69 percent of the variation in reflectance in red and near infrared bands, respectively. Differences in spectral reflectance among treatments were attributed to changes in leaf area index, biomass, and percent soil cover. Cultivar and N fertilization rate were associated with very little of the variation in the reflectance of these canopies.
Daughtry, C. S. T.↗
An assessment of LANDSAT data acquisition history on identification and area estimation of corn and soybeans
Multitemporally registered LANDSAT MSS data from four acquisitions during the 1978 growing season were used in classification of eight sample segments in Iowa and Indiana. The results illustrate that use of LANDSAT acquisition when corn has tasseled is critical, as this is the optimum time for separation of corn and soybeans. An early season acquisition when the summer crops appear as bare soil can be beneficial in reducing the confusion between these two crops and other cover types. A subset of one visible and one infrared band from each date was found to produce results not significantly different from the use of all bands. Selection of a subset of these bands may also be feasible for multitemporal analysis.
Hixson, M. M.↗
Spectral properties of agricultural crops and soils measured from space, aerial, field and laboratory sensors
It is pointed out that in order to develop the full potential of multispectral measurements acquired from satellite or aircraft sensors to monitor, map, and inventory agricultural resources, increased knowledge and understanding of the spectral properties of crops and soils are needed. The present state of knowledge is reviewed, emphasizing current investigations of the multispectral reflectance characteristics of crops and soils as measured from laboratory, field, aerial, and satellite sensor systems. The relationships of important biological and physical characteristics to their spectral properties of crops and soils are discussed. Future research needs are also indicated.
Bauer, M. E.↗
Simulated response of a multispectral scanner over wheat as a function of wavelength and view/illumination directions
Oblique viewing sensors are to be launched in the late 1980's on the Multispectral Resource Sampler, being developed by the U.S. Since the resulting oblique measurements will need to be better understood, the reflectance response with a view angle of wheat, excluding atmospheric effects but simulating the response of a multispectral scanner, is analyzed. Spectra were taken continuously in the wavelength range of 0.45 to 2.4 microns at more than 1200 view/illumination directions with a 20 C spectral radiometer, and data were acquired six meters above four wheat canopies, each at a different stage of growth. The study shows that the canopy reflective response is a function of the illumination angle, the scanner view angle, and the wavelength; and the variation is greater at low solar variations.
Vanderbilt, V. C.↗
An assessment of Landsat data acquisition history on identification and area estimation of corn and soybeans
During the past decade, numerous studies have demonstrated the potential of satellite remote sensing for providing accurate and timely crop area information. This study assessed the impact of Landsat data acquisition history on classification and area estimation accuracy of corn and soybeans. Multitemporally registered Landsat MSS data from four acquisitions during the 1978 growing season were used in classification of eight sample segments in the U.S. Corn Belt. The results illustrate the importance of selecting Landsat acquisitions based on spectral differences in crops at certain growth stages.
Hixson, M. M.↗
Agricultural scene understanding and supporting field research, volume 1
There are no author-identified significant results in this report.
Landgrebe, D. A.↗
Design, implementation, and results of LACIE field research
The capability to acquire, process, and interpret remotely sensed multispectral measurements of the energy reflected and emitted from crops, soils, and other Earth surface features is considered. The LACIE Field Measurements Project is described including project objectives, the experimental approach, the data acquisition program, and selected results based on field data. The key accomplishments and results of the experiment and recommendations for future field research are summarized.
Bauer, M. E.↗
Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach
The effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of LANDSAT MSS data was investigated. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plants. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.
Hixson, M. M.↗
Identification and area estimation of agricultural crops by computer classification of Landsat MSS data
Landsat Multispectral Scanner (MSS) data covering a three-county area in northern Illinois were classified using computer-aided techniques as corn, soybeans, or 'other.' Recognition of test fields was 80% accurate. County estimates of the area of corn and soybeans agreed closely with those made by the USDA. Results of the use of a priori information in classification, techniques to produce unbiased area estimates, and the use of temporal and spatial features for classification are discussed. The extendability, variability, and size of training sets, wavelength band selection, and spectral characteristics of crops were also investigated.
Bauer, M. E.↗
Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach
The author has identified the following significant results. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. Evaluation of four sampling schemes involving different numbers of samples and different size sampling units shows that the precision of the wheat estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling size unit.
Hixson, M.↗
Sampling for area estimation - A comparison of full-frame sampling with the sample segment approach
The objective of this investigation was to evaluate the effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of Landsat MSS data. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.
Hixson, M. M.↗
Multiband radiometer for field research
A multiband radiometer for field research with 8 bands between 0.4 and 12.5 micrometers is described. The data acquisition system will record the results from the radiometer, a precision radiation thermometer, and ancillary sources. The radiometer and data handling systems will be adaptable to helicopter, truck, to tripod platforms; the system will also be suitable for portable hand-held operation. The general characteristics of this system are that it will be (1) inexpensive to acquire, maintain, and operate, (2) simple to calibrate, (3) complete with data handling hardware and software, and (4) well-documented for use by researchers.
Robinson, B. F.↗
Agricultural scene understanding, volume 1
There are no author-identified significant results in this report.
Landgrebe, D. A.↗
Stratification and sample selection for multicrop experiments
The author has identified the following significant results. A stratification was performed and sample segments were selected for an initial investigation of multicrop problems in order to support development and evaluation of procedures for using LACIE and other technologies for the classification of corn and soybeans, to identify factors likely to affect classification performance, and to evaluate problems encountered and techniques which are applicable to the crop estimation problem in foreign countries. Two types of samples, low density and high density, supporting these requirements were selected as research data set for an initial evaluation of technical issues. Looking at the geographic location of the strata, the system appears to be logical and the various segments seem to represent different conditions. This result is supportive not only of the variables and the methodology employed in the stratification, but also of the validity of the data sets employed.
Landgrebe, D. A.↗
Area estimation of crops by digital analysis of Landsat data
The study for which the results are presented had these objectives: (1) to use Landsat data and computer-implemented pattern recognition to classify the major crops from regions encompassing different climates, soils, and crops; (2) to estimate crop areas for counties and states by using crop identification data obtained from the Landsat identifications; and (3) to evaluate the accuracy, precision, and timeliness of crop area estimates obtained from Landsat data. The paper describes the method of developing the training statistics and evaluating the classification accuracy. Landsat MSS data were adequate to accurately identify wheat in Kansas; corn and soybean estimates for Indiana were less accurate. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels.
Bauer, M. E.↗