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首页> 外文会议>Asian Conference on Remote Sensing >FOREST TREE ANALYSIS AT GUNUNG BASOR RESERVE FOREST BASED ON SPOT IMAGES
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FOREST TREE ANALYSIS AT GUNUNG BASOR RESERVE FOREST BASED ON SPOT IMAGES

机译：基于现货图像的Gunung Bador Reserve林的森林树分析

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Forests are the most important ecosystems and carbon pool, imparting with ecological offering and show a significant function in economic advantages. However, in present years, with the economic development and fast populace increase, global forests are going through a sequence of threats, which is sharp declined in forest range, biodiversity damage and degradation in environmental and biological system. Forest resource analysis and monitoring are drastically essential to explore and prevent climate change, ecological degradation and environmental loss. Forest canopy cover is relatively critical parameter that being evaluated in forest analysis and forest inventory. This study is to evolve a systematic framework for Forest Canopy Density (FCD) in tropical rainforests that gives significant in forest regulatory, microclimate changing and soil conditions. FCD model components are based on few of indexes, which are advanced vegetation, bare soil and canopy shadow. The final results of Forest Canopy Density (FCD) for each classes which consist of 30% very dense, 37.3% moderately dense, 18.2% low forest, 8.2% shrub and 6.3% non-forest. The highest value of r is 0.94 which was between FCD and AVI. This research study propose novel method to use high-resolution satellite images. Remote sensing has been plausible to be able to assess the forest structure and large area biomass in a way that is more accurate at relatively low cost. SPOT images provide better outcomes when categorizing variables of forest standoff and forest cover, as they have greater spatial resolution. Hence, SPOT-7 making it ideal for applications for forest analysis.
机译：森林是最重要的生态系统和碳库，赋予生态产品，并在经济优势中表现出重大功能。然而，在目前，随着经济发展和快速的民众增加，全球森林正在经历一系列威胁，森林范围，生物多样性损害和环境和生物制度的退化急剧下降。森林资源分析和监测急剧探索和防止气候变化，生态退化和环境损失至关重要。森林冠层封面是森林分析和森林库存中评估的相对关键参数。本研究是在热带雨林中对森林冠层密度（FCD）的系统框架在森林监管，微气密变化和土壤条件下显着。 FCD模型组件基于少数索引，这是先进的植被，裸土壤和树冠阴影。每种课程的森林冠层密度（FCD）的最终结果，该阶段由30％非常致密，37.3％，18.2％低森林，8.2％灌木和6.3％的非森林。 R的最高值为FCD和AVI之间的0.94。该研究研究提出了使用高分辨率卫星图像的新方法。遥感已经合理地能够以更准确的成本更准确的方式评估森林结构和大面积生物量。当森林宿舍和森林覆盖的变量有更大的空间分辨率时，现货图像提供更好的结果。因此，SPOT-7使其成为森林分析应用的理想选择。

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