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THE IMPACT OF FOREST FIRE ON FOREST COVER TYPES IN MONGOLIA

机译:森林火灾对蒙古森林覆盖类型的影响

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The objective of this study was the impact of forest fire on forest cover types. This study has identified non-forest and forest area that has seven forest class are included with cedar, pine, larch, birch, birch-pine mixed, birch-larch mixed and cedar-larch mixed, additionally, remote sensing imagery is applied. In contrast, Landsat imagery has been used several classification approaches. Moreover, the current classification has developments in segmentation and object-oriented techniques offer the suitable analysis to classify satellite data. In the object-oriented classification approach, images cluster to homogenous area as forest types by suitable parameters in some level. The accuracy analysis revealed that overall accuracy showed a good accuracy of determination (86.33 percent in 2000 and 93.75 percent in 2011) with regard to identify of the forest cover and type. Furthermore, these results suggest that the Landsat TM and ETM+ data can reliable detect the forest type based upon the segmentation and object-oriented techniques. In generally, our study area is high-risky region to forest fires. It is higher influence to forest cover and tree species and other ecosystems. Overall, wildfire of impact results showed that 25239 ha of forests were changed to burnt area and 52603 ha forests were changed to grassland.
机译:本研究的目的是森林火灾对森林覆盖类型的影响。本研究确定了雪松,松树,落叶松,桦木,桦木混合,桦木混合和雪松落叶松混合的雪松,松树,落叶松,桦木,混合和雪松混合的非森林阶级。相比之下,Landsat Imagery已经使用了几种分类方法。此外,当前分类具有分割和面向对象技术的开发,提供了对分类卫星数据的合适分析。在面向对象的分类方法中,通过合适的参数在某种程度上通过合适的参数将簇聚类为林类型。准确性分析表明,关于森林覆盖和类型,总体准确性显示出良好的测定准确性(2000年2000年的86.33%和93.75%)。此外,这些结果表明Landsat TM和ETM +数据可以基于基于分割和面向对象的技术来可靠地检测林型。通常,我们的研究区是森林火灾的高危地区。对森林覆盖和树种和其他生态系统的影响较高。总体而言,影响结果的野火表明,25239公顷的森林被改变为烧焦的地区,52603只森林被改为草原。

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