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Significant results obtained from ERTS-1 observations of agriculture, forestry, and range resources are summarized. Four major parts are covered: (1) crop classification and mensuration; (2) timber and range resources survey and classification; (3) soil survey and mapping; and (4) subdiscipline areas.
The contouring of 8-13.5 micrometer thermal data collected over a forestry site in Virginia is described. The data were collected at an altitude of 1000 ft above terrain on November 4, 1970. The site was covered on three approximately parallel lines. The purpose of the contouring was to attempt to delineate pine trees attacked by southern pine bark beetle, and to map other important terrain categories. Special processing steps were required to achieve the correct aspect ratio of the thermal data. The reference for the correction procedure was color infrared photography. Data form and quality are given, processing steps are outlined, a brief interpretation of results is given, and conclusion are presented.
The necessary elements to perform global inventories of agriculture, forestry, and range resources are being brought together through the use of satellites, sensors, computers, mathematics, and phenomenology. Results of ERTS-1 applications in these areas, as well as soil mapping, are described.
The economic value of ERS information in the resource management area of extensive use of living resources, forestry, wildlife, and rangeland, is determined. Timber and forage resources are quantitatively evaluated. It is shown that these resources have economic value in the tens of billions of dollars, but the economic benefits of improved management of the forests and rangelands are not limited to efficiency in the production of these commercial resources. Multiple-use values including watershed, wildlife, and recreation are also involved.
Computer classifications into seven and ten classes of two areas in central Oregon of interest to geology and forestry demonstrate the extraction of information from ERTS-1 data. The area around Newberry Caldera was classified into basalt, rhyolite obsidian, pumice flats, Newberry pumice, ponderosa pine, lodgepole pine, and water classes. The area around Mt. Washington was classified into two basalts, three forest, two clearcut, burn, snow, and water classes. Both also include an unclassified category. Significant details that cannot be extracted from photographic reconstitutions of the data emerge from these classifications, such as moraine locations and paleowind directions. Spectral signatures for the various rocks are comparable to those published elsewhere.
The feasibility of using microwave systems in agriculture, forestry, range, and soil moisture measurements was studied. Theory and preliminary results show the feasibility of measuring moisture status in the soil. For vegetational resources, crop identification for inventory and for yield and production estimates is most feasible. Apart from moisture- and water-related phenomena, microwave systems are also used to record structural and spatial data related to crops and forests.
A computer approach for mapping mixed forest features (i.e., types, classes) from computer classification maps is discussed. Mixed features such as mixed softwood/hardwood stands are treated as admixtures of softwood and hardwood areas. Large-area mixed features are identified and small-area features neglected when the nominal size of a mixed feature can be specified. The computer program merges small isolated areas into surrounding areas by the iterative manipulation of the postprocessing algorithm that eliminates small connected sets. For a forestry application, computer-classified LANDSAT multispectral scanner data of the Sam Houston National Forest were used to demonstrate the proposed approach. The technique was successful in cleaning the salt-and-pepper appearance of multiclass classification maps and in mapping admixtures of softwood areas and hardwood areas. However, the computer-mapped mixed areas matched very poorly with the ground truth because of inadequate resolution and inappropriate definition of mixed features.
The typical steps in the analysis of remotely sensed data for a forestry applications example are simulated. The example uses numerically-oriented pattern recognition techniques and emphasizes man-machine interaction.
The Forestry Applications Project has been directed towards solving the problem of meeting informational needs of the resource managers utilizing remote sensing data sources including satellite data, conventional aerial photography, and direct measurement on the ground in such combinations as needed to best achieve these goals. It is recognized that sampling plays an important role in generating relevant information for managing large geographic populations. The central problem, therefore, is to define the kind and amount of sampling and the place of remote sensing data sources in that sampling system to do the best possible job of meeting the manager's informational needs.
The actual and the desirable roles of remote sensing in dealing with current forestry issues, such as national forest policy, supply and demand for forest products and competing demands for forest land are discussed. Topics covered include wood shortage, regional timber inventories, forests in tropical and temperate zones, Skylab photography, forest management and protection, available biomass studies, and monitoring.
The results of a study of the uses of helicopters in agriculture and forestry in the United States are discussed. Comparisons with agricultural airplanes are made in terms of costs of aerial application to the growers. An analysis of cost drivers and potential improvements to helicopters that will lower costs is presented. Future trends are discussed, and recommendations for research are outlined. Operational safety hazards and accident records are examined, and problem areas are identified. Areas where research and development are needed to provide opportunities for lowering costs while increasing productivity are analyzed.
The utilization of satellite remote sensing in forestry is reviewed with emphasis on studies performed for the Brazilian Amazon Region. Timber identification, deforestation, and pasture degradation after deforestation are discussed.
The utilization of LANDSAT data in forestry inventories in California is summarized. Problems in selecting meaningful classification systems, utilization of supervised or unsupervised classification systems, and data smoothing are discussed.
A synopsis of a forum addressing the use of LANDSAT data in forestry is given. Broad inventory studies, clear-cut monitoring, and insect and disease detection were among the subject areas discussed. Concerns regarding the vailability of data, cloud cover, resolution and classification accuracy, and product format were expressed by foresters.
Power Pack II provides an economical means of moving a power source into remote roadless forest areas. It was developed by Prof. Miles and his associates, working in cooperation with the University of California's Department of Forestry. The team combined its own design of an all-terrain vehicle with a suspension system based on the NASA load equalization technology. Result is an intermediate-sized unit which carries a power source and the powered tools to perform a variety of forest management tasks which cannot be done economically with current equipment. Power Pack II can traverse very rough terrain and climb a 60 degree slope; any one of the wheels can move easily over an obstacle larger than itself. Work is being done on a more advanced Power Pack III.
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Interpretation of remote sensing data for evaluating range resources
Analysis of vegetation and related earth resources from remote sensing applications of space photography