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首页> 外文期刊>Journal of the Indian Society of Remote Sensing >Study on the Utility of IRS-P6 AWiFS SWIR Band for Crop Discrimination and Classification
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Study on the Utility of IRS-P6 AWiFS SWIR Band for Crop Discrimination and Classification

机译:IRS-P6 AWiFS SWIR波段在作物识别和分类中的应用研究

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摘要

This present study was conducted to find out the usefulness of SWIR (Short Wave Infra Red) band data in AWiFS (Advanced Wide Field Sensor) sensor of Resources at 1, for the discrimination of different Rabi season crops (rabi rice, groundnut and vegetables) and other vegetations of the undivided Cuttack district of Orissa state. Four dates multi-spectral AWiFS data during the period from 10 December 2003 to 2 May 2004 were used. The analysis was carried out using various multivariate statistics and classification approaches. Principal Component Analysis (PCA) and separability measures were used for selection of best bands for crop discrimination. The analysis showed that, for discrimination of the crops in the study area, NIR was found to be the best band, followed by SWIR and Red. The results of the supervised MXL classification showed that inclusion of SWIR band increased the overall accuracy and kappa coefficient. The 'Three Band Ratio' index, which incorporated Red, NIR and SWIR bands, showed improved discrimination in the multi-date dataset classification, compared to other SWIR based indices.
机译:进行本研究的目的是找出资源1的AWiFS(高级宽场传感器)传感器中的SWIR(短波红外)波段数据对于区分不同拉比季节农作物(rabi米,花生和蔬菜)的有用性和奥里萨邦未分割的Cuttack区的其他植被。使用了2003年12月10日至2004年5月2日期间的四个日期的多光谱AWiFS数据。使用各种多元统计和分类方法进行了分析。主成分分析(PCA)和可分离性措施被用于选择最佳的作物区分谱带。分析表明,为了区分研究区域的农作物,NIR被认为是最佳波段,其次是SWIR和Red。监督的MXL分类结果表明,包含SWIR波段可提高整体准确性和kappa系数。与其他基于SWIR的索引相比,结合了Red,NIR和SWIR频段的“三带比率”索引显示了在多日期数据集分类中更好的区分度。

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