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Assessment of vegetation status of Sali River basin, a tributary of Damodar River in Bankura District, West Bengal, using satellite data

机译:利用卫星数据评估Sali River盆地萨利河流域植被状况

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Vegetation status of Sali River basin has been evaluated in this study applying the Land-sat 8 data. Here, NDVI, EVI, GI, LAI, PVI, SI, BI and NDMI have been used to assess vegetation status (VS). Indices have been classified into five categories following natural breaks classification method. Apart from BI, all the indices represented higher value in forest cover area. Weights for all the themes and sub-themes were assigned following multi-criteria decision analysis with consistency ratio of 0.0685, and weighted overlay analysis technique had been employed for the assessment of the vegetation status. Very low, low and moderate VS was found mainly over the water body, urban and agricultural area, which is covering more than half of the basin. The rest of the area is covered with high and very high VS, representing fragmented and dense Sal forest and covering 15.81% and 22.88% basin area, respectively. Accuracy assessment and thorough field verification were done with 90.43% classification accuracy. Our result is quite similar to land use land cover map of Bhuvan, ISRO. So, keeping in the view of health of the river basin and vegetation, this area needs urgent attention to control the degradation of vegetation in a scientific way.
机译:在本研究中,萨利河流域的植被状况应用于土地SAT 8数据。这里,NDVI,EVI,GI,LAI,PVI,SI,BI和NDMI用于评估植被状态(VS)。自然破坏分类方法后,指数已被分为五类分类。除BI外,所有指数都代表了森林覆盖区的较高价值。在符合0.0685的一致性比率的多标准决策分析之后分配了所有主题和子主题的重量,并采用了加权覆盖分析技术来评估植被状态。非常低,低于温和的与水体积,城市和农业区,覆盖盆地的一半以上。该地区的其余部分覆盖着高且非常高的VS,分别代表碎片和致密的SAL森林,覆盖15.81%和22.88%的盆地区域。准确评估和彻底的现场验证完成了90.43%的分类准确性。我们的结果与土地使用土地覆盖地图非常相似,伊斯罗人民币。因此,保持河流流域和植被的健康观,这一领域需要紧急关注以科学的方式控制植被的退化。

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