Applications to earth resources
Remote sensing technology applications to such diverse areas as agriculture, range and forestry; land use; mineral resources; water resources; marine resources; and the environment are discussed.
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Remote sensing technology applications to such diverse areas as agriculture, range and forestry; land use; mineral resources; water resources; marine resources; and the environment are discussed.
The transfer of LANDSAT remote sensing technology from the research sector to user operational applications requires demonstration of the utility and accuracy of LANDSAT data in solving real problems. This report describes such a demonstration project in the area of water resources, specifically the estimation of non-point source pollutant loads. Non-point source pollutants were estimated from land cover data from LANDSAT images. Classification accuracies for three small watersheds were above 95%. Land cover was converted to pollutant loads for a fourth watershed through the use of coefficients relating significant pollutants to land use and storm runoff volume. These data were input into a simulator model which simulated runoff from average rainfall. The result was the estimation of monthly expected pollutant loads for the 17 subbasins comprising the Magothy watershed.
The Seasat-A program has been initiated as a 'proof-of-concept' mission to evaluate the effectiveness of remotely sensing oceanology and related meteorological phenomena from a satellite platform in space utilizing sensors developed on previous space and aircraft test programs. The sensors include three active microwave sensors; a radar altimeter, a windfield scatterometer, and a synthetic aperture radar. A passive scanning multifrequency microwave radiometer, visual and infrared radiometer are also included. All weather, day-night measurements of sea surface temperature, surface wind speed/direction and sea state and directional wave spectra will be made. Two key programs are planned for data utilization with users during the mission. Foremost is a program with the commercial ocean community to test the utility of Seasat-A data and to begin the transfer of ocean remote sensing technology to the civil sector. A second program is a solicitation of investigations, led by NOAA, to involve the ocean science community in a series of scientific investigations.
The Large Area Crop Inventory Experiment (LACIE) is a 'proof of concept' project designed to demonstrate the applicability of remote sensing technology to the global monitoring of wheat. This paper discusses the need for more timely and reliable monitoring of food and fiber supplies, reviews the monitoring systems currently utilized by the USDA and United Nations Food and Agriculture Organization in the United States and in foreign countries, and elucidates the fundamentals involved in assessing the impact of variable weather and economic conditions on wheat acreage, yield, and production. The experiment's approach to production monitoring is described briefly, and its status is reviewed as of the conclusion of 2 years of successful operation. Examples of acreage and yield monitoring in the Soviet Union are used to illustrate the experiment's approach.
The role of research in the educational setting is discussed. Curriculum developments for integrating teaching and research are described. Remote sensing technology is used as an example of bridging the gap between research and application. Recommendations are presented for strengthing research groups.
Several problems within Great Lakes, coastal, and continental shelf water were selected and organized under the topical headings of Productivity, Sedimentation, Water Dynamics, Eutrophication, and Hazardous Substances. The measurements required in the study of each of the problems were identified. An assessment was made of the present capability and the potential of remote sensing to make these measurements. The relevant remote-sensing technology for each of these classifications was discussed and needed advancements indicated.
A review of grain quality indicators and measurement methods was conducted in order to assess the feasibility of using remote sensing technology to develop a continuous monitoring system for use during grain transfer operations. Most detection methods were found to be too slow or too expensive to be incorporated into the normal inspection procedure of a grain elevator on a continuous basis. Two indicators, moisture content and broken corn and foreign material, show potential for automation and are of an economic value. A microprocessor based system which utilizes commercially available electronic moisture meter was developed and tested. A method for automating BCFM measurement is described. A complete system description is presented along with performance test results.
Remote sensing technology providing St. Regis with an independent operational system and having LANDSAT data as a significant and viable contributor was documented and transferred. Primary emphasis was placed on documenting developmental LARSYS (LARSYSDV) software modules. Timelines and a short description of the software documentation process is given.
Remote sensing users from the 14 western states explained their diverse applications of LANDSAT data, discussed operational goals, and exchanged problems and solutions. In addition, conference participants stressed the need for increased cooperation among state and local governments, private industry, and universities to aid NASA's objective of transferring to user agencies the ability to operationally use remote sensing technology for resource and environmental quality management.
A syllabus and training materials prepared and used in a series of one-day workshops to introduce modern remote sensing technology to selected groups of professional personnel in Vermont are described. Success in using computer compatible tapes, LANDSAT imagery and aerial photographs is reported for the following applications: (1) mapping defoliation of hardwood forests by tent caterpillar and gypsy moth; (2) differentiating conifer species; (3) mapping ground cover of major lake and pond watersheds; (4) inventorying and locating artificially regenerated conifer forest stands; (5) mapping water quality; (6) ascertaining the boat population to quantify recreational activity on lakes and waterways; and (7) identifying potential aquaculture sites.
A user's manual for the classification component of the FY-81 U.S. Corn and Soybean Pilot Experiment in the Foreign Commodity Production Forecasting Project of AgRISTARS is presented. This experiment is one of several major experiments in AgRISTARS designed to measure and advance the remote sensing technologies for cropland inventory. The classification procedure discussed is designed to produce segment proportion estimates for corn and soybeans in the U.S. Corn Belt (Iowa, Indiana, and Illinois) using LANDSAT data. The estimates are produced by an integrated Analyst/Machine procedure. The Analyst selects acquisitions, participates in stratification, and assigns crop labels to selected samples. In concert with the Analyst, the machine digitally preprocesses LANDSAT data to remove external effects, stratifies the data into field like units and into spectrally similar groups, statistically samples the data for Analyst labeling, and combines the labeled samples into a final estimate.
Specific case studies undertaken to demonstrate the usefulness of remote sensing technology to resource managers in California are highlighted. Applications discussed include the mapping and quantization of wildland fire fuels in Mendocino and Shasta Counties as well as in the Central Valley; the development of a digital spectral/terrain data set for Colusa County; the Forsythe Planning Experiment to maximize the usefulness of inputs from LANDSAT and geographic information systems to county planning in Mendocino County; the development of a digital data bank for Big Basin State Park in Santa Cruz County; the detection of salinity related cotton canopy reflectance differences in the Central Valley; and the surveying of avocado acreage and that of other fruits and nut crops in Southern California. Special studies include the interpretability of high altitude, large format photography of forested areas for coordinated resource planning using U-2 photographs of the NASA Bucks Lake Forestry test site in the Plumas National Forest in the Sierra Nevada Mountains.
The interactions and support functions required between the early warning/crop condition assessment (EW/CCA) project and soil moisture (SM) project are defined. The EW Project aims to develop, test and evaluate techniques and procedures for adapting remote sensing technology to provide early warning of events and the timely assessment of those factors which affect the quality and quantity of production of economically important crops. Those techniques to augment and reinforce the current assessment activities are to be developed to improve the definition of the relationship between the plant(s) and its environment. This assessment and evaluation will certainly include the need for soil moisture measurement and estimation. The SM Project aims to develop, test, and evaluate techniques and procedures to measure or predict soil moisture in the root zone using both contact and remote sensors.
The applicability of LANDSAT remote sensing technology to the detection of a wheat-leaf-rust epidemic in Sonora, Mexico, during 1977 was investigated. LANDSAT data acquired during crop years 1975-76 and 1976-77 were clustered, classified, and analyzed in order to detect agricultural changes. Analysis of 1977 data indicates a significant proportion of the identified wheat is stressed (potentially rust-infected). Additional analyses show a significant increase in fallowing during the year, as well as a substantial decrease in reservoir levels in the Sonora agricultural region. Ground observations are required to substantiate these analyses. The possibility exists that heat-rust is not LANDSAT detectable and that the clusters identified as containing stressed signatures represent different varieties of wheat or perhaps nonwheat crops.
Remote sensing methodology developed for the Nationwide Forestry Applications Program utilize computer data processing procedures for performing inventories from satellite imagery. The Ten-Ecosystem Study (TES) was developed to test the processing procedures in an intermediate-sized application study. The results of TES indicate that LANDSAT multispectral imagery and associated automatic data processing techniques can be used to distinguish softwood, hardwood, grassland, and water and make inventory of these classes with an accuracy of 70 percent or better. The technical problems encountered during the TES and the solutions and insights to these problems are discussed. The TES experience is useful in planning subsequent inventories utilizing remote sensing technology.
Satellite remote sensing technology is overviewed with particular emphasis on the present and planned LANDSAT satellite systems. Satellite-borne instrumentation and their capabilities are discussed including multispectral scanners, return beam vidicons, the thermal inertia mapper, and STEREOSAT instrumentation.
Oregon State University's Environmental Remote Sensing Applications Laboratory (ERSAL) has six full-time researchers with expertise in a variety of biological, Earth, atmospheric and computer sciences as well as image interpretation and statistical techniques. The primary emphasis of the ERSAL research and demonstration program is the development and application of remote sensing technology in operational resource management programs. LANDSAT multi-spectral, multi-date digital data and imagery are utilized in concert with high altitude NASA-acquired photography, low altitude ERSAL-acquired photography, and field observations and data to provide customized, inexpensive and useful final products. Synopses are given of 9 applications projects conducted in Oregon.
The roles and activities of NASA and the National Conference of State Legislatures in fostering remote sensing technology utilization by the states and in promoting interstate communication and cooperation are reviewed. The reduction and interpretation of LANDSAT MSS and aerial reconnaissance data for resources management and environment assessment are described as well as resource information systems, and the value of SEASAT synthetic aperture radar and LANDSAT 4 data.