Use of ENVISAT ASAR Global Monitoring Mode to complement optical data in the mapping of rapid broad-scale flooding in Pakistan

Abstract

Abstract. Envisat ASAR Global Monitoring Mode (GM) data are used to produce maps of the extent of the flooding in Pakistan which are made available to the rapid response effort within 24 h of acquisition. The high temporal frequency and independence of the data from cloud-free skies makes GM data a viable tool for mapping flood waters during those periods where optical satellite data are unavailable, which may be crucial to rapid response disaster planning, where thousands of lives are affected. Image differencing techniques are used, with pre-flood baseline image backscatter values being deducted from target values to eliminate regions with a permanent flood-like radar response due to volume scattering and attenuation, and to highlight the low response caused by specular reflection by open flood water. The effect of local incidence angle on the received signal is mitigated by ensuring that the deducted image is acquired from the same orbit track as the target image. Poor separability of the water class with land in areas beyond the river channels is tackled using a region-growing algorithm which seeks threshold-conformance from seed pixels at the center of the river channels. The resultant mapped extents are tested against MODIS SWIR data where available, with encouraging results.

Mapeo de áreas inundadas utilizando imágenes de radar TanDEM-X en Acapulco de Juárez, Guerrero-México

“…Diversos trabajos se enfocan en la generación de algoritmos semi-automatizados para delinear inundaciones mayores, mediante la detección de cambios basados en el comportamiento estadístico de la retrodispersión de la señal (Barstch et al, 2008;O'Grady et al, 2011;Hostache et al, 2012;Clement et al, 2017). Del mismo modo, otros métodos integran el análisis textural y la identificación de límites en la frecuencia del histograma para la segmentación de las áreas inundadas (Pradhan et al, 2014;Nazir et al, 2015;Mason et al, 2016).…”

The Use of Sentinel-1 Time-Series Data to Improve Flood Monitoring in Arid Areas

“…These methods are capable of extracting the flood extent if there is a significant contrast between water and non-water areas in the SAR data. However, the classification result may be related to overestimations if non-water areas have a similar low backscatter as open water surfaces [17][18][19][20][21]. This is mainly the case in arid regions, where sand surfaces are characterized as water look-alike areas.…”

Flood Mapping Using Synthetic Aperture Radar: A Case Study of Ramsar Flash Flood

“…The C-SAR can obtain night imagery and detecting small movement on the ground, which makes it useful for land and sea monitoring. As Synthetic Aperture Radar (SAR) can provide frequent observations is particularly useful for flood mapping (Alsdorf et al, 2007;Mertes, 2002;Ward et al, 2014) due to its capability to monitor land in any weather conditions (Franceschetti and Lanari, 1999;Marzano et al, 2011;Schumann et al, 2009) and also in night-time (O'Grady et al, 2011;Waisurasingha et al, 2007;Wilson and Rashid, 2005).…”