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At least 505 records · Page 28

The status of parametric studies in radar agriculture

Outlined is an information system based on the use of remote sensor data and the design, testing, and implementation of interpretation keys for agriculture. The task of crop identification from radar imagery emphasizes dichotomous keys and the effects of frequency, angular and other microwave dependencies of crops for use in discrimination. A mosaic is formulated from imagery and used to study acres in wheat for spread of circular irrigation, spread of crops, and other phenomena.

Morain, S. A.↗

Radar monitoring of agricultural land use - Some problems and potentials at the local level.

A study was made of some of the changing land use practices in a small area of the American Winter Wheat Belt as they might relate to remote sensing. In addition, interviews were conducted with farmers and local country agents in order to determine some of the needs regarding land use and farming practices as perceived by these people. A list of elements of land use is given which provides potential variables and parameters to be considered in interpreting radar imagery. The results of interviews provide a better concept of what potential remote sensing users at the primary level need and want.

Henderson, F. M.↗

Variables in automatic classification over extended remote sensing test sites.

Four major causes of variation in response of multispectral scanner data were examined utilizing data from two large test sites. In one case, data throughout a 70-mile flightline was automatically classified with a high degree of accuracy (98%), utilizing training samples from a single small segment of the data. In the second case, spectral data for wheat and other cover types were calibrated and utilized to train the computer, resulting in data up to 90 miles away being classified with an acceptable degree of accuracy (91%), although significant changes in solar illumination and ground cover conditions existed.

Hoffer, R. M.↗

Kansas environmental and resource study: A Great Plains model, tasks 1-6

There are no author identified significant results in this report. Environmental and resources investigations in Kansas utilizing ERTS-1 imagery are summarized for the following areas: (1) use of feature extraction techniqued for texture context information in ERTS imagery; (2) interpretation and automatic image enhancement; (3) water use, production, and disease detection and predictions for wheat; (4) ERTS-1 agricultural statistics; (5) monitoring fresh water resources; and (6) ground pattern analysis in the Great Plains.

Haralick, R. M.↗

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.↗

Flexible DCP interface

The author has identified the following significant results. A user of an ERTS data collection system must supply the sensors and signal conditioning interface. The electronic interface must be compatible with the NASA-furnished data collection platform (DCP). A universal signal conditioning system for use with a wide range of environmental sensors is described. The interface is environmentally and electronically compatible with the DCP and has operated satisfactorily for a complete winter wheat growing season in Kansas.

Kanemasu, E. T.↗

Improvements in estimating proportions of objects from multispectral data

Methods for estimating proportions of objects and materials imaged within the instantaneous field of view of a multispectral sensor were developed further. Improvements in the basic proportion estimation algorithm were devised as well as improved alien object detection procedures. Also, a simplified signature set analysis scheme was introduced for determining the adequacy of signature set geometry for satisfactory proportion estimation. Averaging procedures used in conjunction with the mixtures algorithm were examined theoretically and applied to artificially generated multispectral data. A computationally simpler estimator was considered and found unsatisfactory. Experiments conducted to find a suitable procedure for setting the alien object threshold yielded little definitive result. Mixtures procedures were used on a limited amount of ERTS data to estimate wheat proportion in selected areas. Results were unsatisfactory, partly because of the ill-conditioned nature of the pure signature set.

Horwitz, H. M.↗

Quality of signatures

Three conclusions are drawn on the usability, inherent variations, and noise aspects of the spectral signatures processed from data collected by the Field Signature Acquisition System (FSAS). Conclusions are based on the spectral data collected from winter wheat of the 1972/73 season, grown at Texas A and M University, College Station, Texas.

Kan, E. P. F.↗

Introduction

The author has identified the following significant results. The objectives of the investigation were: (1) to evaluate the effect of water stress, disease, and leaf area on the reflectance characteristics of wheat; (2) to evaluate disease losses in terms of yield and water use; and (3) to predict disease severity and economic loss.

Source record↗

Flexible DCP interface

The author has identified the following significant results. A user of an ERTS data collection system (DCS) must supply the sensors and signal-conditioning interface. The electronic interface must be compatible with the NASA-furnished data collection platform. A universal signal-conditioning system for use with a wide range of environmental sensors is described. The interface is environmentally and electronically compatible with the DCP and has operated satisfactorily for a complete winter wheat growing season in Kansas.

Kanemasu, E. T.↗

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.↗

Mapping soils, crops, and rangelands by machine analysis of multitemporal ERTS-1 data

ERTS-1 data, obtained during the period 25 August 1972 to 5 September 1973 over a range of test sites in the Central United States, have been used for identifying and mapping differences in soil patterns, species and conditions of cultivated crops, and conditions of rangelands. Multispectral scanner data from multiple ERTS passes over certain test sites have provided the opportunity to study temporal changes in the scene. Multispectral classifications delineating soils boundaries in different test sites compared well with existing soil association maps prepared by conventional means. Spectral analysis of ERTS data was used to identify, maps, and make areal measurements of wheat in western Kansas. Multispectral analysis of ERTS-1 data provided patterns in rangelands which can be related to soils differences, range management practices, and the extent of infestation of grasslands by mesquite (prosopis fuliflora) and juniper (juniperus spp.).

Baumgardner, M. F.↗

Affine transformations from aerial photos to computer compatible tapes

During the development of a project to estimate wheat production, it became necessary to pull data, corresponding to particular fields in a test site, off an ERTS computer compatible tape. Aerial photographs and topographic maps were on hand for the test site. A method was devised, using an affine transformation, to relate the aerial photographs or topographic maps to the tapes. One can thereby access data on the tape corresponding to regions covered by only a few pixels. The theory can be used for the registration of two tapes for the same area and for the geometric correction of images.

Peet, F. G.↗

LACIE ADP/PI joint case study: ADP analysis guidelines

The procedure is described which was used to train automatic data processing (ADP) analysts to process ERTS 1 imagery from a 5 nm by 6 nm area in Delisle, Canada, and to estimate wheat acreage using training fields provided by photointerpreters. The exercise also served to evaluate and test current large area crop inventory experiment (LACIE) procedures.

Minter, T. C.↗

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.↗

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.↗

Methods of extending signatures and training without ground information

Methods of performing signature extension, using LANDSAT-1 data, are explored. The emphasis is on improving the performance and cost-effectiveness of large area wheat surveys. Two methods were developed: ASC, and MASC. Two methods, Ratio, and RADIFF, previously used with aircraft data were adapted to and tested on LANDSAT-1 data. An investigation into the sources and nature of between scene data variations was included. Initial investigations into the selection of training fields without in situ ground truth were undertaken.

Henderson, R. G.↗