首页> 外文期刊>Journal of Applied Remote Sensing >Coherence-based land cover classification in forested areas of Chattisgarh, Central India, using environmental satellite--advanced synthetic aperture radar data
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Coherence-based land cover classification in forested areas of Chattisgarh, Central India, using environmental satellite--advanced synthetic aperture radar data

机译:使用环境卫星-先进的合成孔径雷达数据,在印度中部查蒂斯加尔森林地区基于连贯性的土地覆盖分类

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摘要

In the present work, the potential of synthetic aperture radar (SAR) interferometric coherence in land cover classification is studied over forested areas of Bilaspur, Chattisgarh, India using Environmental Satellite--Advanced Synthetic Aperture Radar (ENVISAT-ASAR) C-band data. Single look complex (SLC) interferometric pair ASAR data of 24th September 2006 (SLC-1) and 29th October 2006 (SLC-2) covering the study area were acquired and processed to generate backscatter and interferometric coherence images. A false colored composite of coherence, backscatter difference, and mean backscatter was generated and subjected to maximum likelihood classification to delineate major land cover classes of the study area viz., water, barren, agriculture, moist deciduous forest, and sal mixed forests. Accuracy assessment of the classified map is carried out using kappa statistics. Results of the study suggested potential use of ENVISAT-ASAR C-band data in land cover classification of the study area with an overall classification accuracy of 82.5percent, average producer's accuracy of 83.69percent, and average user's accuracy of 81percent. The present study gives a unique scope of SAR data application in land cover classification over the tropical deciduous forest systems of India, which is still waiting for its indigenous SAR system.
机译:在当前工作中,使用环境卫星-先进合成孔径雷达(ENVISAT-ASAR)C波段数据研究了印度查蒂斯加尔邦比拉斯普尔森林地区的合成孔径雷达(SAR)干涉相干在土地覆盖分类中的潜力。采集并处理了覆盖研究区域的2006年9月24日(SLC-1)和2006年10月29日(SLC-2)的单视复杂(SLC)干涉对ASAR数据,并生成了反向散射和干涉相干图像。生成了虚假的连续性,后向散射差异和平均后向散射复合图像,并对其进行了最大似然分类,以描绘研究区域的主要土地覆盖类别,即水,贫瘠,农业,湿润的落叶林和萨尔混交林。使用kappa统计数据对分类地图的准确性进行评估。研究结果表明,ENVISAT-ASAR C波段数据可能在研究区域的土地覆盖分类中使用,总体分类准确度为82.5%,平均生产者准确度为83.69%,平均用户准确度为81%。本研究为印度热带落叶林系统的土地覆被分类中的SAR数据应用提供了独特的范围,印度仍在等待其本地SAR系统。

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