4 resultados para Land cover classification

em Digital Archives@Colby


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The South China tiger, Panthera tigris amoyensis, once roamed the greater part of southern China. However, expanding human populations and other anthropogenic effects have resulted in the extinction of the wild population. The Chinese government has expressed interest in a reintroduction program for this species of tigers. Recent studies suggest that the Hupingshan preserve is potentially a good candidate for a tiger reintroduction program. Hupingshan is located on the border of the Hunan and Hubei provinces in Southern China. This study was a preliminary habitat suitability analysis, for the restoration of South China tigers in the Hupingshan reserve, China. ArcGIS 9.0 was used to develop a model that combined roads, railroads, slope, land cover, park classification, and population density. The tiger habitat suitability analysis was performed by weighting and combining the various layers. Preliminary results suggest that the Hupingshan reserve is suitable habitat for the reintroduction of South China tigers.

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The range of the Gray Wolf (Canis lupus), once covering most of North America, has been drastically reduced by an estimated 95% due to habitat loss and extermination by humans. The wolf was extirpated from Maine in the 1800’s. Wolf reintroductions have been suggested for Maine, but there is some debate about how much land is suitable for wolves. I developed a wolf habitat suitability analysis using ArcGIS and data from the Maine Office of GIS and the United States National Atlas. The model incorporates land cover, presence of major roads and railways, conservation land, industrial, non-industrial, and public woodlot ownership, distance from major points of population, deer population, and slope. The model results show areas of high and low wolf suitability in Maine. The model suggests that the best potential habitat for wolves in Maine is situated in the northwest of the state. Possible future reintroductions or natural colonization from other areas would have the highest likelihood of survival in these areas.

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The purpose of this study was to conduct a habitat suitability analysis of the critically endangered Florida panther (Felis concolor coryi) in Florida. We gathered land cover, population and road data from the Florida Geographic Data Library and performed map algebra using ESRI’s ArcGIS to compile a suitable habitat map. We found that there is 20381.7 km² of highly suitable habitat and 557124.4 km² of less desirable but usable habitat for the Florida panther. The highest concentration of highly suitable habitat is in Big Cypress National Park, with smaller patches in Tates Hell State Forest and along the southeast portion of the Panhandle. Due to extensive fragmentation, however, and without establishment of habitat linkages to the existing southern population, there is little chance of survival of additional panther populations in much of northern Florida.

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Moose (Alces alces) are a keystone herbivore in Maine. Because of the large number of rural roads in Maine, there is a high rate of moose-vehicle collisions (MVCs), which is increasing. On-road encounters with animals resulted in 231 fatalities in the United States in 1999. Because of the fatality of MVCs, it is important to know where they are most likely to occur. I used GIS analysis to estimate where future MVCs would occur, factoring in the variables of land cover suitability for moose, distance from water bodies, locations of past MVCs, and speed limits on the roads. I ran four different analyses, each one weighting the variables equally. I also ran a regression to determine if increasing road speed was associated with the increase in the number of MVCs per length of road. There was not a strong positive relationship between the number of MVCs per length of road and the speed limit, but it was interesting to note that there were more MVCs per length of road on 35mph and 40mph roads than on 45, 50, 55 or 65mph roads. Future research on MVCs would benefit from the inclusion of include moose population density and road traffic data.