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Analysis of land use and land cover change in Kiskatinaw River Watershed: A remote sensing, gis modeling approach.

机译:Kiskatinaw河流域的土地利用和土地覆被变化分析:遥感,GIS和建模方法。

摘要

This thesis study was conducted to capture the land use and land cover (LULC) change dynamics in Kiskatinaw River Watershed, BC, Canada. A combination of remote sensing, GIS and modeling approach was utilized for this purpose. Landsat TM and ETM+ satellite images of the years 1984, 1999 and 2010 were analyzed using object oriented image classification technique to produce LULC maps and detect the associated changes. The dynamic nature of different forest types, increase in built-up area and significant depletion of wetlands were found to be notable among the detected LULC changes. Thereafter, a multi-layer perception neural network technique was used to model transition potentials of various LULC types, which was later realized with a Markov Chain land use model to predict future changes. The integration of advanced satellite remote sensing tools and neural network aided Markov Chain modeling was illustrated to be an effective means for LULC change detection and prediction in Kiskatinaw River Watershed. --Leaf ii.
机译:进行了本论文研究,以捕获加拿大不列颠哥伦比亚省基斯卡塔诺河流域的土地利用和土地覆被(LULC)变化动态。为此,结合了遥感,GIS和建模方法。使用面向对象的图像分类技术对1984、1999和2010年的Landsat TM和ETM +卫星图像进行了分析,以生成LULC地图并检测相关的变化。在检测到的土地利用,土地利用变化中发现,不同森林类型的动态性质,建成面积的增加和湿地的大量枯竭是值得注意的。此后,使用多层感知神经网络技术对各种LULC类型的转换电位进行建模,随后通过马尔可夫链土地利用模型实现了这种潜力,以预测未来的变化。先进的卫星遥感工具和神经网络辅助的马尔可夫链模型的集成被说明是在基斯喀纳托河流域进行LULC变化检测和预测的有效手段。 -叶ii。

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  • 年度 2014
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