Towards an operational daily soil moisutre index derived from combination of MODIS, ASAR and AMSR-E data

C. Notarnicola, B. Ventura, L. Pasolli, F. D. Giuseppe, M. Zebisch
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Abstract

This work aims at deriving a methodology for calculation of a soil moisture index based on the apparent thermal inertia (ATI) approach. For the processing, MODIS images have been exploited which have a higher resolution (1 km) if compared with METEOSAT images and are suitable for the ATI calculation. Furthermore, the approach considers the soil moisture estimates derived from SAR sensors and use them to calibrate the information coming from the optical data. The main advantage of this approach is to transform a soil moisture index derived from optical images in soil moisture values by using a comparison between spatial distributed data. In order to make the calibration more robust and consider the variability from different areas, three main test sites have been chosen located in Italian regions with different meteorological and landscape characteristics. In case of anomalous values due to the not appropriate acquisition time, AMSRE soil moisture data are used as prior information in order to improve the estimates.
基于MODIS、ASAR和AMSR-E数据的可操作日土壤湿度指数
本工作旨在推导一种基于表观热惯性(ATI)方法计算土壤湿度指数的方法。在处理过程中,利用了MODIS图像,与METEOSAT图像相比,MODIS图像具有更高的分辨率(1 km),适合ATI计算。此外,该方法考虑了来自SAR传感器的土壤湿度估算值,并使用它们来校准来自光学数据的信息。该方法的主要优点是利用空间分布数据之间的比较,将由光学图像导出的土壤水分指数转换为土壤水分值。为了使校准更加稳健,并考虑不同地区的可变性,我们选择了三个主要的试验点,它们位于意大利具有不同气象和景观特征的地区。对于由于采集时间不合适而出现的异常值,利用AMSRE土壤水分数据作为先验信息,改进估算结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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