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Remote Sensing Retrieval of Soil Moisture in the Wetland Area of a Flood Plain-a case study of Honghe National Nature Reserve

机译:洪水平原湿地地区土壤水分遥感检索 - 以红河国家自然保护区为例

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Soil moisture is an important indicator for wetland degradation. It is significant to do research on spatial and time variability of soil moisture and on how to monitor soil moisture by remote sensing in wetland, which is still a lack of research at present. In this paper, the Honghe National Nature Reserve is taken as an example. After analyzing all kinds of information about soil moisture reversion and comparing different quantitative remote sensing models, we introduce Ts/NDVI model and rectify it by many monitoring data to adapt to the soil moisture retrieving in the wetland study area. Supported by Landsat TM data and other high-resolution data, we inverse the factors (e.g. the vegetation index, the surface temperature, the albedo and so on) needed in the model by remote sensing techniques. And further on, the process of soil moisture is modulated and described quantitavely. Then we use the new model to monitor soil moisture in Honghe National Nature Reserve in June、July、 August and September of 2008. Based on the monitoring data of some typical fields, the retrieved information is validated and the result show that the model is very well to obtain the depth soil moisture in wetland. The results of this study show that the improved T_s/EVI space can extract more accurate spatial/temporal distribution of soil moisture information in wetland. It is useful for the quantitative investigation of the four typical growing season's soil moisture variations as well as analysis of habitat characteristics of the humidity gradient.
机译:土壤水分是湿地降解的重要指标。对土壤湿度的空间和时间变异性以及如何通过湿地遥感监测土壤水分的研究是重要的,目前仍然是缺乏研究。本文以红河国家自然保护区为例。在分析有关土壤湿度逆转的各种信息并比较不同的定量遥感模型后,我们介绍了TS / NDVI模型,并通过许多监测数据来纠正,以适应湿地研究区域的土壤水分检测。通过LANDSAT TM数据和其他高分辨率数据支持,我们通过遥感技术致电模型中所需的因素(例如植被指数,表面温度,ALBEDO等)。此外,QualiTavely调节和描述土壤水分的过程。然后我们使用新模型在2008年6月,8月和9月在2008年6月监测了红河国家自然保护区的土壤水分。根据一些典型字段的监测数据,验证了检索的信息,结果表明该模型非常很好地获得湿地的深度土壤水分。本研究的结果表明,改进的T_S / EVI空间可以在湿地中提取更准确的土壤水分信息的空间/时间分布。它对于对典型生长季节的土壤水分变化的定量调查以及湿度梯度的栖息地特征分析是有用的。

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