کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5755002 | 1621206 | 2017 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Monthly flooded area classification using low resolution SAR imagery in the Sudd wetland from 2007 to 2011
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
کامپیوتر در علوم زمین
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چکیده انگلیسی
The annual flood cycle of the Sudd wetland in South Sudan plays an important role in the Nile River Basin water balance. The wetland, however, is extensive and sparsely instrumented, which has inhibited credible understanding of regional flooding across space and time. Here we explore the potential to apply low resolution C-band ENVISAT Advanced SAR imagery for remote estimation of Sudd flooded area. Over a five year study period (2007-2011) the time-averaged flooded Sudd area was found to be 18,033Â km2 with an average annual high of 29,702Â km2 in late September and a low of 10,128Â km2 in early May. Annual peak flood area ranges considerably from 19,259Â km2 in 2009 to 36,649Â km2 in 2007, but we found no systematic trend over the five year study period. Derived flood frequency maps identify areas of open water and permanent flooding (12% of total area), seasonal flooding (29%), and intermittent flooding (48%). To evaluate the certainty of our results, we consider their consistency with (1) prior studies, (2) evapotranspiration estimates from the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, (3) watershed storage anomaly estimates from GRACE, (4) supervised classification of open water area using Landsat, and (5) a rough measure of water availability (antecedent precipitation). The analyses show reasonable temporal and spatial consistency with available lines of evidence. We conclude that low resolution C-band SAR imagery shows promise for study of Sudd wetland flood dynamics.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 194, 1 June 2017, Pages 205-218
Journal: Remote Sensing of Environment - Volume 194, 1 June 2017, Pages 205-218
نویسندگان
Daniel C. Wilusz, Benjamin F. Zaitchik, Martha C. Anderson, Christopher R. Hain, M. Tugrul Yilmaz, Iliana E. Mladenova,