توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱SAR–BASED INDICES ANALYSIS FOR DAMAGE ASSESSMENT DUE TO EARTHQUAKE
نویسنده(ها): ، ،
اطلاعات انتشار: ششمین کنفرانس بین المللی زلزله شناسی و مهندسی زلزله، سال
تعداد صفحات: ۸
The purpose of this study is to assess the capability of SAR remote sensing data and its relevant techniques for damage detection in urban areas and monitor the deformation due to the earthquake. The case study of this research is the 2005 Qeshm earthquake. The data used are pre–seismic and co–seismic pairs of Envisat RADAR images in ascending and descending orbits. In this study pre and co–seismic coherence, intensity and correlation coefficient of intensity maps were calculated from the related interferograms and SAR SLC images. In order to represent the damage categories, a number of indices were necessary to be defined based on the pre and co–seismic coherence and correlation maps. The indices were calculated as differences between the pairs. The analysis of the maps showed that the increase in damaged areas resulted in decrease of their corresponding coherence values as opposed to the intensity values which increased when the damage increased.<\div>

۲Surface soil moisture retrieval using a regression method applied on polarimetric SAR images
نویسنده(ها): ، ،
اطلاعات انتشار: ششمین کنفرانس بین المللی پیشرفتهای علوم و تکنولوژی، سال
تعداد صفحات: ۸
Soil moisture plays a critical role in many hydrological processes including infiltration, evaporation, and runoff. Satellite–based passive microwave sensors are sensitive to soil moisture content, (Cashiona et al., 2005), but the spatial resolution of these sensors is much lower than visible\infrared (VIS\IR) satellite data. However, soil moisture estimates from VIS\IR sensors usually require surface micro–meteorological and atmospheric information that is not routinely available. To overcome these problems, radar remote sensing technology has been widely used for soil moisture retrieving because of its capability to operate in all weather conditions (Xiao et al., 2005). This study is concerned with retrieving percentage of soil moisture content using polarimetric PALSAR data in Iran. Scattering matrix decomposition has been used to find optimum features that have higher correlation with soil moisture content. Therefore, a regression based method has been used to estimate the soil moisture content based on these features. According to the validation, as expected, the retrieved soil moistures were consistent with those of field measurements. It can be concluded in this study that proposed method is appropriate in mapping soil moisture content as a suitable alternative to sparsely distributed meteorological stations measurements.<\div>
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