Full text: Remote sensing for resources development and environmental management (Volume 2)

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Centre for 
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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. 
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ser's Guide to 
tion System - 
lichigan State 
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. 
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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