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Digital Image Processing 1
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Case studies of a natural resource and economic development analysis system
John M. Hill, Daniel Flint, Gregory Gladish
Remote Sensing and Image Processing Laboratory
Louisiana State University, Baton Rouge, La 70803, USA
Fran Stetina
NASA, Code 670.1 Goddard Space Flight Center
Greenbelt, MD 20771, USA
Introduction
If economic development planning is to long-term success, then it should take forecasts of socio-economic parameters a potential environmental impacts into consideration. Remote sensing scientists for years have been monitoring and mapping natural resources and manmade features. These studies have also utilized Geographic Information Systems (GIS) to manage these resources. A GIS combines computer hardware and software designed especially to digitally merge and analyze diverse, geo-referenced data sets. The tools used by these natural resource managers can now be applied to planned economic development. This paper described how the authors, preliminary remote sensing scientists, have conducted various development applications using GIS's.
We have found that many economic development specialists, both in government and private industry, use socio-economic data and associated forecasting models to target areas for development. It appears that a combination of spatial data (e.g., natural resources, infrastructure, and political boundaries) and socio-economic data (e.g., income, age, job sector) create a more complete package.
After various economic forecasting models are applied to select potential development regions using socio-economic and industrial parameters, a GIS can be used to further refine more detailed criteria to target specific sites. As an example, a GIS can be used to define transportation distances along various infrastructure networks (e.g., airports, railroads, highways). A GIS can also be used to better depict, and therefore interpret, the spatial distribution of socio economic model generated output by country region or country.
A primary key to being able to facilitate this particular application is to have the computer capability to merge and process data from a wide variety of sources. Relevant databases are usually on different operating systems (computers), while others are in various formats (e.g. vector, raster (satellite imagery) and text files. Often expert systems need to be enveloped to properly collect, format and input the necessary data sets into and appropriate model. The model-generated results then need to be output in an appropriate format (e.g. slides, maps, laser prints, technical reports).
The remainder of this paper will describe three actual economic development planning and marketing projects in which the authors have participated. The first project involved the mapping of natural resources with infrastructure assessment, and the third involved the sitting of geo textile plants along a major river system.
Economic development applications
- Aquaculture Development
The inland fisheries program of the Food and Agricultural Organization (FAO) of the United Nations (UN) wanted to learn how to apply a GIS to aquacultures development. The state of Louisiana, USA, was selected as the study area. Only data of a spatial resolution (e.g. 1 km) which is typical of that sets were digitized and input to the GIS: political boundaries, soil associations, climate (growing days), pars and wildlife refuges, major cities (>50,000 people), and agriculture and aquaculture production statistics. Distributions of aquaculture production (catfish and crawfish) and agricultural production (sorghum and rice) were mapped by reported area (country). Using the GIS, the soil association map was modified to depict (1) topography (flat, hilly, marsh), (2) areas suitable for rolled earth dams (using physical soil properties), and (3) depth to ground water. This project emphasized the usefulness of merging agricultural production statistics (resolution of political units) with such natural resources information as soil types, growing days and topography. Other similar overlays, using the above mentioned data sets, were generated, were generated to better target prioritized areas suitable for aquaculture development activities.
A separate GIS was developed for Franklin Parish, Louisiana, where catfish production is the highest in the state (Kapetsky, et. al 1988). A flood plain map was added to the soil suitability map so that new fish ponds would not be inundated during spring floods. Fig.1 depicts the location of actual catfish farms. The majority of farms are on the most appropriate soil type (A) and are in very close proximity (20 km) to the town where the fish processing plant is infrastructure and associated product/feed transportation costs in preceding economic development applications projects. This approach ha since been successfully applied by Katelsky, et. al (1987) in Costa Rica, China, Thailand and Malaysia.
- Infrastructure Assessment
The second project involved the use of national database to describe the infrastructure of a very low-income region of the United States (Lower Mississippi Delta Region) that is targeted for economic development. The Federal Emergency Management Agency (FEMA) developed the Innovative Emergency Management information system ((IEMIS) (FEMA, 1988). This system not only contains a nationwide database, but it also has integrated near real-time pollution plume and traffic evacuation models. For this particular project, a survey of the region's infrastructure was conducted. The primary data used were U.S highways, interstates, major airports, major rivers, country and state political boundaries, electric power grids, major cities, federal lands, and congressional districts. Overlays of transportation networks (fig. 2) with major river systems indicated that the regions were nearly split in half by the Mississippi River. The western half to the region did not have a north-south interstate system. There were numerous countries with no major transportation networks. These areas were likely to be cut off from the usual flow of commodities and, therefore, less prosperous. An overlay of federally owned lands indicated that some apparently remote countries contained larger portions of national forests and/or parks. These areas may be more appropriate for tourism development.
This infrastructure/natural resource database can be enhanced through the incorporation of human resources information. Socio-economic databases exist which generally have country resolution (National Planning Association). They include such data as income levels, population, job sector (E.g. government industry), race, and age to name a few. Other databases are more oriented toward potential industry selection and these include employment and income multipliers by industry type. For instance, the U.S. Department of Agriculture (USDA), Forest Service, has a model (IMPLAN) for the forest products and associated industries. The national Forest Service's land management activities affect, local regional and national economics (USDA, 1983). The forest service
Purchases goods and services while conducting management activities. This is an economic input to an area. In turn, the resulting forest resources outputs influence market transactions at the local, regional and national levels. This type of input-output analysis attempts to describe the interdependence among product sector. This technique can produce detailed estimates of direct, indirect and induced economic impacts that would result from the implementation of a resource management plan. These databases include forecasting models to project economic development parameters through the year 2000.
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