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Object oriented extraction of wetlands based on synergistic use of multispectral and microwave remote sensing data

机译:基于多光谱和微波遥感数据协同使用的湿地面向对象提取

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摘要

The Tibetan Plateau (TP) is identified as a global climate change hotspot due to its relevance for the Asian monsoon circulation system. Glacial melt and receding permafrost indicate significant changes within this climate system. Spatio-temporal information is required to gain a better understanding of the interactions of system components and ongoing processes. By numerous studies, Earth Observation data analysis has been shown as being a suitable tool which enables to monitor mid- and long-term environmental changes. A new object oriented classification approach which is based on synergies between the optical remote sensing products and SAR data was developed for automatic and seasonal-adaptive extraction of parameters for wetland area derivation and characterization. It was shown that the derived parameters are important indicators for environmental change analyses. The developed method is appropriate to monitor wetland responses with high temporal and spatial resolution according to climate change and human impacts within large regions like the TP.
机译:青藏高原(TP)因其与亚洲季风环流系统的相关性而被确定为全球气候变化热点。冰川融化和多年冻土退去表明该气候系统发生了重大变化。需要时空信息以更好地了解系统组件和正在进行的过程之间的相互作用。通过大量研究,地球观测数据分析已被证明是监测中长期环境变化的合适工具。开发了一种基于光学遥感产品和SAR数据协同作用的面向对象的新分类方法,用于自动和季节性自适应提取湿地面积推导和表征的参数。结果表明,导出的参数是环境变化分析的重要指标。所开发的方法适用于根据气候变化和人类对TP等大区域内的影响,以高的时空分辨率监测湿地响应。

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