基于GIS和人工神经网络预测土地利用变化

土地利用变化预测是土地管理工作中的重要课题。随着社会的发展与进步，土地资源的合理和有效利用变得越来越重要。进行土地利用变化预测时，数据采集和综合分析是重要的工作。介绍了基于地理信息系统(Geographic Information Systems，GIS)技术建立的土地转换模型(LandTransformation Model，LTM)在经过人工神经网络(Artificial Neural Netwoks，ANNs)技术的分析后对土地利用变化预测的基本原理。这种方法充分结合了GIS的空间分析功能和ANNs的信息处理功能，在综合分析影响土地利用变化因素后可以得出较为准确的结论。利用GIS和ANNs技术进行土地利用变化预测不但可以充分利用原有的历史数据，得到清楚的预报因子，还可以综合相关因素分析后得出新的空间数据层作为ANNs的输入数据，通过ANNs的近似人脑的分析能力很好的预测未来土地利用的发展趋势，有利于土地管理和城市规划部门合理安置和有效利用土地资源。

Use GIS and ANN to Forecast Land Use Change

To forecast land use change is important for land use management. With the development and improvement of the society, to use the land resource reasonably and effectively has become more and more important Data collection and integrate analysis are important to forecast land use change. It introduced the based principle of forecasting land use change after using the LTM based on GIS which has been analyzed by ANNs. This given method integrate the function of spatial analysis of GIS and the function of information disposal of ANNs, and elicit more exact result after analyzing factors that impact land use change. Using GIS and ANNs to forecast land use change not only could take good advantage of original data and get explicit predictor variable, but also integrate relative factors to get new spatial data layer as input data for ANNs, and take advantage of the analysis ability resembling the brain of ANNs to forecast the developing trend of land use, which be good for department of land management an d urban plan to use land resource effectively.