Resource Mapping

Resource mapping refers to the cartographic depiction of natural resources such as land, water, soil, minerals, forests, biological species, wind power, and so on. Thus, the phrase refers to the process of acquiring, analyzing, representing, and presenting information about the geographic distributions of these resources. The resulting resource maps visualize the spatial variation of the resources being mapped and are a means to analyze and store such information. The spatial variation information is fundamental to inventorying, monitoring, and modeling the resources; therefore, mapping is usually a key operation in resource management, conservation, use, and planning. Resource mapping is a routine practice in many governmental and nongovernmental agencies or organizations.

The history of resource mapping may be as long as the history of the map itself. It is not hard to imagine that our ancestors used graphics to indicate the locations of water sources or to keep records of the sizes and shapes of lands. An example of modern resource mapping is the Canada Land Inventory of 1963–1995. This project was a massive effort begun by the Canadian government in the 1950s to identify the nation's land resources as well as their existing and potential uses. What makes this project particularly significant is that it developed the first geographic information system (GIS), the Canada Geographic Information System (CGIS). The development of this system was motivated by the need to accurately and quickly measure land areas.

Nowadays, modern geospatial information technologies, including GIS, remote sensing, and the global positioning system (GPS), have revolutionized the process and output of resource mapping. Remote sensing may provide data that are both spatially and temporally detailed and often cover vast areas and long time spans. A GPS can accurately and precisely associate ground sample data with remotely sensed data, so that models can be built to translate the data obtained through remote sensing, for example, a vegetation index, into the information about resources, for example, vegetation type. A GIS is the platform and tool to integrate all kinds of data, build and run models, and design and create the final maps.

Figure 1 shows a map generated through the integration of these modern technologies. The map shows the spatial distribution of biomass resources that are usable for energy production in Guangdong Province, China. The calculation of the amount of usable biomass at each location started with remotely sensed data, including MODIS/Terra and LandSet. The remotely sensed data were processed in a GIS by a series of physical, biological, economic, and ecological models built based on ground samples (located by a GPS) and the literature, to derive the usable biomass value at each location and generate the map. With this biomass information and the information about a road network (also shown in the map), further modeling can be performed to evaluate the feasibility of establishing biomass electric power plants in this area and locate optimal locations for such plants based on transportation costs.

Besides the adoption of the modern spatial information technologies, another trend in today's resource mapping is the shift from vector to raster format to store, represent, or display spatial data in digital form. The data for today's resource mapping, as exemplified by remotely sensed data and digital elevation models (DEMs, which are being increasingly derived from remotely sensed data), are increasingly available in raster rather than vector format. The implication of this data format change is more profound than simply how the data are organized and stored. The capability of raster data to accommodate high resolutions in both spatial and attribute aspects facilitates the representations of continuities in both geographical and parameter spaces, which in turn facilitates the application of new modeling methods, such as fuzzy (continuous) classification, in resource mapping. In fuzzy classification, an object can belong to more than one class and is not required to be fully typical of a predefined class. For those resources that change continuously over Earth's surface (e.g., vegetation and soil), raster mapping using fuzzy classification usually preserves more information and better reflects human knowledge than the traditional vector mapping using crisp classification. Raster mapping using fuzzy classification not only changes the way people generate and interpret resource maps but may also change the way they represent the knowledge of the [Page 2455]resources that they want to include in the maps. Specifically, with vector mapping using crisp classification, our focus would be on where to draw the boundary between two classes, whereas in raster mapping using fuzzy classification, our focus would be on what the most typical features are for a given class. The influence of this fundamental change in spatial data management on resource mapping remains to be seen.

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