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Evaluating MODIS-vegetation continuous field products to assess tree cover change and forest fragmentation in India: a multi-scale satellite remote sensing approach

机译:评估mODIs植被连续野外产品,以评估印度的树木覆盖变化和森林破碎:多尺度卫星遥感方法

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摘要

Monitoring the changes in forest-cover and understanding the dynamics of the forest is becoming increasingly important for the sustainable management of forest ecosystems. This paper uses temporal MODIS Vegetation Continuous Field (MODIS-VCF) to monitor the tree cover change in the Indian region over a period of 6 years (2000–2005). Pixel-based linear regression model is developed to identify rate of deforestation and fragmentation at landscape level. The regression parameters viz., slope, offset and variance are used to identify threshold between forest and non-forest classes. The classification algorithm resulted into change area, no change area, positive change and negative changes. MODIS-VCF raw product of 2005 was validated using the field data and showed a coefficient of determination (R2 = 0.85) between percent tree cover and individual plot wise canopy cover information. The results were overlaid with UNEP protected area boundary. On a long-term basis, the forest cover change was monitored using medium spatial resolution (Landsat and IRS) satellite data to identify the rate of deforestation and fragmentation at landscape level. The developed approach is efficient and effective for regional monitoring of forest cover change. It could be automated for regular usage and monitoring.
机译:监测森林覆盖率的变化并了解森林的动态对森林生态系统的可持续管理变得越来越重要。本文使用时态MODIS植被连续场(MODIS-VCF)监测印度地区6年(2000-2005年)树木的覆盖变化。开发了基于像素的线性回归模型,以识别景观级别的森林砍伐和破碎率。回归参数即斜率,偏移量和方差用于确定森林和非森林类别之间的阈值。分类算法分为变化区域,无变化区域,正变化和负变化。 2005年的MODIS-VCF原始产品使用现场数据进行了验证,并显示出树木覆盖率百分比与各个图块机盖信息之间的确定系数(R2 = 0.85)。结果被环境署保护区边界覆盖。从长远来看,使用中等空间分辨率(Landsat和IRS)卫星数据监测森林覆盖率变化,以识别景观水平上的森林砍伐和破碎率。所开发的方法对于森林覆盖变化的区域监测是有效的。它可以自动进行常规使用和监视。

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