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AUTOMATED ALGORITHM FOR EXTRACTION OF WETLANDS FROM IRS RESOURCESAT LISS III DATA

机译:来自IRS Resourcesat的湿地自动化算法Liss III数据

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摘要

Wetlands play significant role in maintaining the ecological balance of both biotic and abiotic life in coastal and inland environments. Hence, understanding of their occurrence, spatial extent of change in wetland environment is very important and can be monitored using satellite remote sensing technique. The extraction of wetland features using remote sensing has so far been carried out using visual/ hybrid digital analysis techniques, which is time consuming. To monitor the wetland and their features at National/ Sta te level, there is a need for the development of automated technique for the extraction of wetland features. A knowledge based algorithm has been developed using hierarchical decision tree approach for automated extraction of wetland features such as surface water spread, wet area, turbidity a nd wet vegetation including aquatic for pre and post monsoon period. The results obtained for Chhattisgarh, India using the automated technique has been found to be satisfactory, when compared with hybrid digital/visu al analysis technique.
机译:湿地在维持沿海和内陆环境中的生物和非生物生活的生态平衡方面发挥着重要作用。因此,理解其发生,湿地环境变化的空间程度非常重要,并且可以使用卫星遥感技术监测。到目前为止,使用遥感的湿地特征提取使用可视化/混合数字分析技术进行,这是耗时的。为了在国家/地区/地区/地区/地区/地区监测湿地及其特色,需要开发湿地特征的自动化技术。已经使用分层决策树方法开发了一种知识的算法,用于自动提取湿地特征,如地表水扩散,湿地区,浊度A ND湿植被,包括前后季后赛。与混合数字/ VISU AL分析技术相比,已发现使用自动化技术的Chhattisgarh,印度使用自动化技术获得的结果。

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