Flood monitoring and mapping using passive microwave remote sensing in Namibia

Groeve, Tom De

doi:10.1080/19475701003648085

Cited by 94 publications

(67 citation statements)

References 4 publications

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“…Note that from 2013 the system has been providing the merged product TRMM/AMSR2; however, this period is out of our scope. In the GFDS system, the microwave signal (s) is defined as the ratio between the measurement over wet pixel (M) and the measurement over a 7 pixel × 7 pixel array of background calibration (C) pixel, known as the M / C ratio De Groeve, 2010). Better discharge signal values may be achieved when the measurement pixel is centred over a river reach and no hydraulic structures are present (Moffitt et al, 2011).…”

Section: Satellite-derived Datamentioning

confidence: 99%

Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors

Revilla-Romero

Thielen

Salamon

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. One of the main challenges for global hydrological modelling is the limited availability of observational data for calibration and model verification. This is particularly the case for real-time applications. This problem could potentially be overcome if discharge measurements based on satellite data were sufficiently accurate to substitute for groundbased measurements. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System for converting the flood detection signal into river discharge values.The study uses data for 322 river measurement locations in Africa, Asia, Europe, North America and South America. Satellite discharge measurements were calibrated for these sites and a validation analysis with in situ discharge was performed. The locations with very good performance will be used in a future project where satellite discharge measurements are obtained on a daily basis to fill the gaps where real-time ground observations are not available. These include several international river locations in Africa: the Niger, Volta and Zambezi rivers.Analysis of the potential factors affecting the satellite signal was based on a classification decision tree (random forest) and showed that mean discharge, climatic region, land cover and upstream catchment area are the dominant variables which determine good or poor performance of the measurement sites. In general terms, higher skill scores were obtained for locations with one or more of the following characteristics: a river width higher than 1 km; a large floodplain area and in flooded forest, a potential flooded area greater than 40 %; sparse vegetation, croplands or grasslands and closed to open and open forest; leaf area index > 2; tropical climatic area; and without hydraulic infrastructures. Also, locations where river ice cover is seasonally present obtained higher skill scores. This work provides guidance on the best locations and limitations for estimating discharge values from these daily satellite signals.

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Section: Satellite-derived Datamentioning

confidence: 99%

Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors

Revilla-Romero

Thielen

Salamon

et al. 2014

Hydrol. Earth Syst. Sci.

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“…Countering this, its use of microwave radiation allows water to be visible despite cloud cover -something that is a severe problem when examining the surface within the Visible or Near InfraRed (VNIR) wavelengths. A recent study of flood detection using data from AMSR-E over Namibia produced positive results, with the majority of flood events being correctly identified and mapped (De Groeve, 2010). Additionally, satellite constellations such as COSMO-SkyMed allow for the analysis of flood events at high spatial resolution (Boni et al, 2008;Pierdicca et al, 2010;Hahmann et al, 2008).…”

Section: Introductionmentioning

confidence: 91%

Rapid response flood detection using the MSG geostationary satellite

Proud

Fensholt

Rasmussen

et al. 2011

International Journal of Applied Earth Observation and Geoinfor

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“…The passive microwave sensor detected water surface signal (M/C ratio) is an indirect means for river water surface change [2]. The Global Flood Detection System (GFDS) of the Joint Research Centre of the European Commission (http://old.gdacs.org/flooddetection/overview.aspx) and River Watch 2 (http://floodobservatory.colorado.edu/DischargeAccess.html) are using this technique for global flood detection [23,24]. The AMSR-E based discharge measurements monitors water surface signals at more than 10,000 monitoring areas in different river basins throughout Africa, Asia, America and Europe.…”

Section: Microwave Remote Sensing For Flood Detectionmentioning

confidence: 99%

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

et al. 2014

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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 OPEN ACCESSRemote Sens. 2014, 6 2394 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.

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Flood monitoring and mapping using passive microwave remote sensing in Namibia

Cited by 94 publications

References 4 publications

Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors

Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors

Rapid response flood detection using the MSG geostationary satellite

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

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