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Remote Sens. 2014, 6(3), 2393-2407;

Multi-Sensor Imaging and Space-Ground Cross-Validation for 2010 Flood along Indus River, Pakistan

School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK 73019, USA
HyDrometeorology & Remote Sensing (HyDROS) Laboratory and Advanced Radar Research Center, National Weather Center Suite 4600, University of Oklahoma, Norman, OK 73072, USA
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
National Oceanic and Atmospheric Administration/National Severe Storms Laboratory, National Weather Center, Norman, OK 73072, USA
Institute of Geographical Information Systems, National University of Sciences and Technology, Islamabad 44000, Pakistan
Joint Research Centre of the European Commission, Via Fermi 2147, Ispra 21020, Italy
Authors to whom correspondence should be addressed.
Received: 18 December 2013 / Revised: 26 February 2014 / Accepted: 3 March 2014 / Published: 19 March 2014
(This article belongs to the Special Issue Analysis of Remote Sensing Image Data)
Full-Text   |   PDF [1135 KB, uploaded 19 June 2014]


Flood monitoring was conducted using multi-sensor data from space-borne optical, and microwave sensors; with cross-validation by ground-based rain gauges and streamflow stations along the Indus River; Pakistan. First; the optical imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) was processed to delineate the extent of the 2010 flood along Indus River; Pakistan. Moreover; the all-weather all-time capability of higher resolution imagery from the Advanced Synthetic Aperture Radar (ASAR) is used to monitor flooding in the lower Indus river basin. Then a proxy for river discharge from the Advanced Microwave Scanning Radiometer (AMSR-E) aboard NASA’s Aqua satellite and rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) are used to study streamflow time series and precipitation patterns. The AMSR-E detected water surface signal was cross-validated with ground-based river discharge observations at multiple streamflow stations along the main Indus River. A high correlation was found; as indicated by a Pearson correlation coefficient of above 0.8 for the discharge gauge stations located in the southwest of Indus River basin. It is concluded that remote-sensing data integrated from multispectral and microwave sensors could be used to supplement stream gauges in sparsely gauged large basins to monitor and detect floods. View Full-Text
Keywords: flood monitoring; optical sensor; microwave sensors; SAR; image analysis; image classification flood monitoring; optical sensor; microwave sensors; SAR; image analysis; image classification
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Khan, S.I.; Hong, Y.; Gourley, J.J.; Khattak, M.U.; De Groeve, T. Multi-Sensor Imaging and Space-Ground Cross-Validation for 2010 Flood along Indus River, Pakistan. Remote Sens. 2014, 6, 2393-2407.

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