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首页> 外文会议>International Society for Photogrammetry and Remote Sensing Bhopal Workshop Earth Observation for Terrestrial Ecosystem >ANALYSIS OF SPATIO-TEMPORAL PATTERNS OF LEAF AREA INDEX IN DIFFERENT FOREST TYPES OF INDIA USING HIGH TEMPORAL REMOTE SENSING DATA
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ANALYSIS OF SPATIO-TEMPORAL PATTERNS OF LEAF AREA INDEX IN DIFFERENT FOREST TYPES OF INDIA USING HIGH TEMPORAL REMOTE SENSING DATA

机译：使用高时遥感数据分析不同森林类型的不同森林类型叶面积指数的时空模式

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Knowledge of temporal variations of Leaf Area Index (LAI) aids in understanding the climate-vegetation interaction of different vegetative systems. This information is amenable from high temporal remote sensing data. India has around 78.37 million hectare, accounting for 23.84% of the geographic area of the country under forest/tree cover. India has a diverse set of vegetation types ranging from tropical evergreen to dry deciduous. We present a detailed spatio-temporal and inter-seasonal analysis of LAI patterns in different forest types of India using MODIS 8-day composites global LAI/fPAR product for the year 2005 at 1-km spatial resolution. A fore st cover mask was generated using SPOT 1-km landuse/landcover classification over the Indian region. The range of estimated LAI varied from 0.1-6.9 among the different forest types. Maximum LAI was observed in tropical evergreen forests in North-Eastern region a nd Western Ghats. Low LAI was observed in Central Indian region due to predominance of dry deciduous forests. The spatial patterns of seasonal variations detected that for most of the forest types, the peak LAI values were observed during September and October months of the autumn season in contrast to minimum LAI during summer season. The mean LAI and standard deviation for each 8-day LAI composite were also computed and mean monthly LAI profiles were derived for each forest type classified on the basis of their geographical locations. These results are useful indicators for detailed understanding of phenological sequence and may also serve as important inputs for deriving bioclimatic indices for different forest types of India.
机译：了解叶面积指数（LAI）艾滋病的时间变化，了解不同营养系统的气候 - 植被相互作用。此信息可从高时遥感数据可供选择。印度在森林/树木封面下拥有约7837万公顷，占该国地理区域的23.84％。印度拥有各种各样的植被类型，从热带常青树到干燥的落叶。我们在2005年的2005年以1公里的空间分辨率为2005年全球LAI / FPAR产品提供了不同森林类型的Lai模式的详细时态和季节性分析。在印度地区使用现货1千米地兰德/地图分类，产生了前盖掩模。估计的LAI范围从不同森林类型中的0.1-6.9变化。在东北地区的热带常绿森林中观察到最大LAI在ND Western Ghats。由于干燥的落叶林的优势，在中部印度地区观察到低莱。季节性变化的空间模式检测到，对于大多数森林类型，秋季季节的9月和十月月份的峰值值与夏季的最低赖相比，观察到荔枝价值。每个8天Lai复合材料的平均赖和标准偏差也被计算，并且为基于其地理位置分类的每个森林类型来源的平均赖曲面。这些结果是有用指标，用于详细了解鉴效序列，也可以作为导出不同森林类型印度的生物恐资指标的重要输入。

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