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首页> 外文期刊>American Journal of Remote Sensing >GIS and Logit Regression Model Applications in Land Use/Land Cover Change and Distribution in Usangu Catchment
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GIS and Logit Regression Model Applications in Land Use/Land Cover Change and Distribution in Usangu Catchment

机译：GIS和Logit回归模型在乌桑古流域土地利用/覆盖变化和分布中的应用

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This study applied time series analysis to examine land use/land cover (LULC) change and distribution in Usangu watershed and multinomial logistic regression in the GIS environment to model the influence of the related driving factors. Historical land use/cover data of the watershed were extracted from the 2000, 2006 and 2013 Landsat images using GIS and remote sensing data processing and analysis techniques. Data was analyzed using ArcMap 10.1, ERDAS Imagine, SPSS and IDRISI Selva software. Eight factors likely to influence LULC change and LULC distribution were assessed. These include elevation, slope, distance from roads, distance from rivers networks, population density, Normalized Vegetation Index (NDVI), annual rainfall and soil types. Results show that LULC changes are mainly influenced by variations in annual rainfall, population density and distance from road networks. LULC distribution is determined mainly by terrain and edaphic factors namely elevation, slope and soil types. NDVI does not influence LULC change nor determine the LULC distribution, but can be used to show concentration of LULC types on a landscape. Combination of GIS, remote sensing and statistical analysis capabilities are powerful tools for assessing and model processes of land use change and their underlying causes in terms of time and space. It is concluded that ingeniously integration of remote sensing, GIS application combined with multi-source spatial data analysis give great possibility of quantifying and explaining the temporal and spatial LULC changes and distribution in a given watershed.
机译：这项研究应用时间序列分析来检查Usangu流域的土地利用/土地覆盖（LULC）变化和分布以及GIS环境中的多项Logistic回归，以建模相关驱动因素的影响。利用GIS和遥感数据处理与分析技术从2000年，2006年和2013年的Landsat影像中提取了该流域的历史土地利用/覆盖数据。使用ArcMap 10.1，ERDAS Imagine，SPSS和IDRISI Selva软件分析数据。评估了可能影响LULC变化和LULC分布的八个因素。这些因素包括海拔，坡度，距道路的距离，距河网的距离，人口密度，标准化植被指数（NDVI），年降雨量和土壤类型。结果表明，LULC的变化主要受年降雨量，人口密度和距道路网距离的影响。 LULC分布主要取决于地形和地理因素，即海拔，坡度和土壤类型。 NDVI不会影响LULC的变化，也不会确定LULC的分布，但是可以用来显示景观上LULC类型的集中度。 GIS，遥感和统计分析功能的组合是评估和建模土地利用变化过程及其时空原因的强大工具。结论是，将遥感，GIS应用与多源空间数据分析巧妙地集成在一起，给定量和解释给定流域中时空LULC的变化和分布提供了很大的可能性。

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