Remote sensing for resources development and environmental management: Remote sensing for resources development and environmental management

damen, m. c. j.

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Multivolume work

Persistent identifier:: 856342815

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856342815

Language:: English

Additional Notes:: Volume 1-3 erschienen von 1986-1988

Editor:: Damen, M. C. J.

Document type:: Multivolume work

Volume

Persistent identifier:: 856641294

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Scope:: IX Seiten, Seiten 551-956

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A,. A. Balkema

Identifier (digital):: 856641294

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(26,7,2)

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Damen, M. C. J.

Editor:: International Society for Photogrammetry and Remote Sensing, Commission of Photographic and Remote Sensing Data

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: 8 Geo-information systems. Chairman: J. J. Nossin

Write comment:: Wegen zu enger Bindung kommt es teilweise im Original zu Textverlust.

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: Soils an important component in a digital geographic information system. Carlos R. Valenzuela, Marion F. Baumgardner & Terry L. Phillips

Document type:: Multivolume work

Structure type:: Chapter

939 the estimated Liability for g the cropping r a "standard ries data and gle year and Is. This last 1 in comparing ield model for onditions or items. As an vid ed b etween for sugar cane - 1981 for a t. Catherine s reported low sting problems , 1979. Yield rigation and i, 1985. MULBUD Centre for 1ian Nations 1 Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 Soils an important component in a digital geographic information system Carlos R.Valenzuela*, Marion F.Baumgardner & Terry L.Phillips Purdue University, Laboratory for Applications of Remote Sensing, West Lafayette, Ind, USA * Present address: ITC, Enschede, Netherlands ABSTRACT: There is an increasing use of digital geographic information systems to meet the demand for specific accurate and rapid information of our resources. The degree of usefulness of this information depends on the accessibility and efficiency of the methods utilized for input, storage, analysis, and retrieval of informatio The demand for accurate and rapid soil information is growing in our society, thus the element soil, because se of its importance, is one of the basic components of a complete geographic information system. The Indiana soil association map at a scale 1:500,000 was digitized, projected to an Albers equal-area map projection, rasterized, and stored in a geo-referenced database created for the state of Indiana, U.S.A. Using the digital soils data stored in the geo-referenced database, new sets of data were generated by changing the coding of the soil associations or by combining two or more of these new generated products. Among the new digital data sets generated from the soils data are: Prime agricultural lands, Potential erosion, Dominant drainage, Dominant relief, average Corn yields. 1 GENERAL TAT, A Micro n, Management, ic Research iversity, East ser's Guide to tion System - lichigan State Lgan. The complexity and increasing volumes of available information, and the demand for the storage, analysis and display of large quantities of environmental data, has led in recent years, to rapid development in the application of computers to environmental and natural resources data handling and the creation of sophisti cated information systems (Tomlinson et al., 1976). Effective utilization of large spatial data volumes is dependant upon the existance of an efficient geogra phic handling and processing system that will trans form these data into usable information. The major tool for handling spatial data is the geographic infor mation system (Marble and Peuquet, 1983). Increasingly data of all types are being collected and converted to digital format. Extensive digital geographically orien ted databases are being developed, and automated spa tial information systems are used for storage, retrie val, manipulation, analysis, and display of information (Tom and Miller, 1974; Power, 1975; Knapp, 1978; Jerie et al., 1980; Anderson and Bernal, 1983). A digital geographic information system (GIS) is a computerized system designed to stored, process and analyse spatial data and their corresponding attribu te information. Advances in computer technology and techniques have made it possible to integrate a wide range of information (Gribbs, 1984). Technological advances have increased input techniques, storage, a- nalysis and retrieval capabilities. Furthermore, there has been a reduction in costs and an increase in ac cessibility, so that a larger user community has been developed (Moellering, 1982). Geographic information systems have provided planners with a readily accessi ble source of objective earth science related facts, and an inexpensive, rapid and flexible tool for combi ning these facts with various other products to create decision alternatives (van Driel, 1975; Stow and Estes, 1981; Stoner, 1982). A digital GIS is an information system which has as its primary source of input a base composed of data referenced by geographic coordinates and in which a major part of the processing is done with a digital computer (Kennedy and Meyers, 1977). It basically performs the following major functions: a) Data in put, b) Data storage and retrieval, c) Data manipu lation, and d) Data output (Tomlinson et al., 1976; Knapp, 1978; Nagy and Wegle, 1978; Jerie et al. , 1980; Marble and Peuquet, 1983; Bartlocci et al., 1983; Va lenzuela, 1985). Basic information on the location, quantity and a- vailability of natural resources is indispensable for planning more retionally their development, use and/or conservation. The demand for specific, accurate, and rapid soil information is growing in our modern socie ty. Soils, because of their importance in agricul tural and non-agricultural matters, and their inherent relationships with other environmental resources are a basic and fundamental component of any complete geo graphic information system. Johnson (1975) points out that the conventional pre paration of soil interpretive maps combining informa tion of the soil resource with other resource informa tion are excessively expensive, especially if various source maps have to be converted to a common scale and if the interpretive requirements are complex. Automatic data processing systems have create inmen- se opportunities for storing and disseminating soil data (Bertelli, 1979). As the demand for interpretive maps increases, computers are used to speedup and cut down costs of the process (Bertelli, 1966; Shields, 1976; Bertelli, 1979; Miller and Nichols, 1979; Bie, 1980; Santini et al., 1983; Valenzuela, 1985). The national Soil Handbook of the USDA Soil conser vation Service (1983), indicates that the use of com puter generated interpretive soil maps is encouraged where the soil survey has been digitized because they cost less than maps prepared by other means. The objective of this study was to evaluate the sig nificance of the element soils in the overall context of a digital geographic information system. 2 METHODOLOGY The digital geographic information system developed at the Laboratory for Applications of Remote Sensing of Purdue University, basically consists of five ma jor subsystems: a) input subsystem, b) database sub system, c) management subsystem, d) modeling and ana lysis subsystem, and e) output subsystem. A simpli fied schematic configuration of the system is illus trated in Figure 1. The soil association map of Indiana, USA, was pre pared by the Indiana Soil Survey Staff of the United States Department of Agriculture Soil Conservation Service and Purdue University Agricultural Experiment

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