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Banana orchard inventory using IRS LISS sensors

机译:使用IRS LISS传感器的香蕉果园库存

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摘要

Banana is one of the major crops of India with increasing export potential. It is important to estimate the production and acreage of the crop. Thus, the present study was carried out to evolve a suitable methodology for estimating banana acreage. Area estimation methodology was devised around the fact that unlike other crops, the time of plantation of banana is different for different farmers as per their local practices or conditions. Thus in order to capture the peak signatures, biowindow of 6 months was considered, its NDVI pattern studied and the optimum two months were considered when banana could be distinguished from other competing crops. The final area of banana for the particular growing cycle was computed by integrating the areas of these two months using LISS Ⅲ data with spatial resolution of 23m. Estimated banana acreage in the three districts were 11857Ha, 15202ha and 11373Ha for Bharuch, Anand and Vadodara respectively with corresponding accuracy of 91.8%, 90% and 88.16%. Study further compared the use of LISS IV data of 5.8m spatial resolution for estimation of banana using object based as well as per-pixel classification and the results were compared with statistical reports for both the approaches. In the current paper we depict the various methodologies to accurately estimate the banana acreage.
机译:香蕉是印度主要农作物之一,出口潜力不断增加。估算作物的产量和播种面积很重要。因此,进行了本研究以发展用于估计香蕉种植面积的合适方法。围绕以下事实设计了面积估算方法:与其他农作物不同,香蕉种植​​的时间因地区农民的当地习惯或条件而异。因此,为了捕获峰值特征,考虑了6个月的生物窗,研究了其NDVI模式,并考虑了将香蕉与其他竞争作物区分开来的最佳两个月。通过使用空间分辨率为23m的LISSⅢ数据对这两个月的面积进行积分,可以计算出特定生长周期的香蕉最终面积。估计三个地区的Bharuch,Anand和Vadodara的香蕉种植面积分别为11857公顷,15202公顷和11373公顷,相应的准确度分别为91.8%,90%和88.16%。研究进一步比较了使用5.8m空间分辨率的LISS IV数据进行基于对象以及按像素分类的香蕉估计,并将结果与​​两种方法的统计报告进行了比较。在当前的论文中,我们描述了各种方法来准确估算香蕉种植面积。

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