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Remote Sens. 2014, 6(3), 2393-2407; doi:10.3390/rs6032393

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

1,2,* , 1,2,3,* , 4
1 School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK 73019, USA 2 HyDrometeorology & Remote Sensing (HyDROS) Laboratory and Advanced Radar Research Center, National Weather Center Suite 4600, University of Oklahoma, Norman, OK 73072, USA 3 State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China 4 National Oceanic and Atmospheric Administration/National Severe Storms Laboratory, National Weather Center, Norman, OK 73072, USA 5 Institute of Geographical Information Systems, National University of Sciences and Technology, Islamabad 44000, Pakistan 6 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)
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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.
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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