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GEOSPATIAL CHARACTERIZATION OF BIODIVERSITY: NEED AND CHALLENGES

机译:生物多样性地理空间表征:需要和挑战

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Explaining the distribution of species and understanding their abundance and spatial distribution at multiple scales using remote sensing and ground based observation have been the central aspect of the meeting of COP10 for achieving CBD 2020 targets. In this respe ct the Biodiveristy Characterization at Landscape Level for India is a milestone in biodiversity study in this country. Satellite remote sensing has been used to derive the spatial extent and vegetation composition patterns. Sensitivity of different multi-scale landscape metrics, species composition, ecosystem uniqueness and diversity in distribution of biological diversity is assessed through customized landscape analysis software to generate the biological richness surface. The uniqueness of the study lies in the creation of baseline geo-spatial data on vegetation types using multi-temporal satellite remote sensing data (IRS LISS III), deriving biological richness based on sp atial landscape analysis and inventory of location specific information about 7964 unique plant species recorded in 20,000 sample plots in India and their status with respect to endemic, threatened and economic/medicinal importance. The results generated will serve as a baseline database for various assessment of the biodiversity for addressing CBD 2020 targets.
机译:用遥感和地面观察解释物种的分布并在多种尺度下了解它们的丰度和空间分布,是COP10会议的中心方面,用于实现CBD 2020目标。在这recape中,CT在印度景观层面的生物传道人表征是该国生物多样性研究中的里程碑。卫星遥感已被用于得出空间范围和植被组成模式。通过定制景观分析软件评估不同多尺度景观度量,物种组成,生态系统唯一性和分布在生物多样性分布中的多样性,以产生生物丰富的表面。研究在于创造使用多时卫星遥感数据(IRS LISS III),推导生物丰富植被类型基线地理空间数据的基础上的具体位置信息SP atial景观分析和库存约7964独特的唯一性植物物种在印度的20,000个样品地块中记录,其地位相对于地方,威胁和经济/药用意义。产生的结果将作为基准数据库,用于各种评估用于解决CBD 2020目标的生物多样性。

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