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Multiscale Hydrologic Remote Sensing: Perspectives and Applications
extents can provide objective information for flood control and hazard mitigation
(Smith 1997; Brakenridge and Anderson 2003; Brakenridge et al. 2003). A good
example could include the orbital sensors, such as the moderate resolution imaging spectroradiometer (MODIS), which provide reliable data to help detect floods
in regions where no other means are available for flood monitoring (Brakenridge
2006; Brakenridge et al. 2007). Such data, with global coverage and frequent observations of the region of interest after certain processing, could potentially provide
timely information on the areal extent of flooding. To date, satellite images have
become practical tools for development of rapid and cost-effective methods for
hydrologic predictions of floods in poorly or even ungauged river basins around
the globe, regardless of political boundaries. It has been demonstrated that orbital
remote sensing technologies can be used for mapping of river inundation, and these
advances have shown a great potential to directly or indirectly measure runoff
(Birkett et al. 2002; Brakenridge 2006).
The use of satellite imagery for flood mapping began with the use of the
Landsat Thematic Mapper (France and Hedges 1986), the Landsat Multispectral
Scanner (France and Hedges 1986), the Satellite Pour l’Observation de la Terre
(Jensen et al. 1986; Watson 1991; Blasco et al. 1992), the Advanced Very High
Resolution Radiometer (Xiao and Chen 1987; Barton and Bathols 1989; Gale and
Bainbridge 1990; Rasid and Pramanik 1993; Sandholt et al. 2003), the advanced
spaceborne thermal emission and reflection radiometer (ASTER), the MODIS, and
the Landsat-7 sensors (Wang 2004; Wang et al. 2002; Stancalie et al. 2004). For a
comprehensive review on extraction of flood extents and surface water levels from
various satellite sensors, please refer to the literature (Watson 1991; Smith 1997;
Puech and Raclot 2002).
Satellite remote sensing data have emerged as a viable alternative as well as a
supplement to in situ observations due to their capability to cover vast ungauged
regions. Microwave satellite data can be effectively used for flood monitoring
without regard to the cloud cover. The spatial resolution of the data at a 10-km
grid scale, such as the Advanced Microwave Scanning Radiometer for the Earth
observing system microwave data, is relatively coarse for flood mapping. Satellite
radar imagery proved invaluable in mapping flood extents (Horritt 2000; Horritt
and Bates 2002; Schumann et al. 2007). Flooding maps derived from synthetic
aperture radar (SAR) sensors were used as a result to validate hydraulic models
(Horritt et al. 2007; Di Baldassarre et al. 2009). Limitations of this process were
noted though, and examples include SAR’s inability to detect flooding in urban
areas, inaccurate image calibration that leads to geometric and radiometric distortions, difficulties for data processing, and low temporal resolution with a revisit
time of 35 days (Schumann et al. 2007). Contrary to spaceborne microwave data,
visible/infrared sensors aboard the MODIS Terra satellite can detect floods with
relatively high spatial (30-m ASTER and 250-m MODIS) and temporal (daily if it
is clear sky) resolution around the globe. In the past decade, noticeable efforts were
made to investigate the potential for using flood inundation maps derived from
optical remote sensing sensors to validate the performance of hydrologic models
in sparsely or ungauged river basins (Brakenridge 2006; Brakenridge et al. 2007).
Khan et al. (2011a) emphasized the use of the iterative self-organizing data analysis
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
extents can provide objective information for flood control and hazard mitigation
(Smith 1997; Brakenridge and Anderson 2003; Brakenridge et al. 2003). A good
example could include the orbital sensors, such as the moderate resolution imaging spectroradiometer (MODIS), which provide reliable data to help detect floods
in regions where no other means are available for flood monitoring (Brakenridge
2006; Brakenridge et al. 2007). Such data, with global coverage and frequent observations of the region of interest after certain processing, could potentially provide
timely information on the areal extent of flooding. To date, satellite images have
become practical tools for development of rapid and cost-effective methods for
hydrologic predictions of floods in poorly or even ungauged river basins around
the globe, regardless of political boundaries. It has been demonstrated that orbital
remote sensing technologies can be used for mapping of river inundation, and these
advances have shown a great potential to directly or indirectly measure runoff
(Birkett et al. 2002; Brakenridge 2006).
The use of satellite imagery for flood mapping began with the use of the
Landsat Thematic Mapper (France and Hedges 1986), the Landsat Multispectral
Scanner (France and Hedges 1986), the Satellite Pour l’Observation de la Terre
(Jensen et al. 1986; Watson 1991; Blasco et al. 1992), the Advanced Very High
Resolution Radiometer (Xiao and Chen 1987; Barton and Bathols 1989; Gale and
Bainbridge 1990; Rasid and Pramanik 1993; Sandholt et al. 2003), the advanced
spaceborne thermal emission and reflection radiometer (ASTER), the MODIS, and
the Landsat-7 sensors (Wang 2004; Wang et al. 2002; Stancalie et al. 2004). For a
comprehensive review on extraction of flood extents and surface water levels from
various satellite sensors, please refer to the literature (Watson 1991; Smith 1997;
Puech and Raclot 2002).
Satellite remote sensing data have emerged as a viable alternative as well as a
supplement to in situ observations due to their capability to cover vast ungauged
regions. Microwave satellite data can be effectively used for flood monitoring
without regard to the cloud cover. The spatial resolution of the data at a 10-km
grid scale, such as the Advanced Microwave Scanning Radiometer for the Earth
observing system microwave data, is relatively coarse for flood mapping. Satellite
radar imagery proved invaluable in mapping flood extents (Horritt 2000; Horritt
and Bates 2002; Schumann et al. 2007). Flooding maps derived from synthetic
aperture radar (SAR) sensors were used as a result to validate hydraulic models
(Horritt et al. 2007; Di Baldassarre et al. 2009). Limitations of this process were
noted though, and examples include SAR’s inability to detect flooding in urban
areas, inaccurate image calibration that leads to geometric and radiometric distortions, difficulties for data processing, and low temporal resolution with a revisit
time of 35 days (Schumann et al. 2007). Contrary to spaceborne microwave data,
visible/infrared sensors aboard the MODIS Terra satellite can detect floods with
relatively high spatial (30-m ASTER and 250-m MODIS) and temporal (daily if it
is clear sky) resolution around the globe. In the past decade, noticeable efforts were
made to investigate the potential for using flood inundation maps derived from
optical remote sensing sensors to validate the performance of hydrologic models
in sparsely or ungauged river basins (Brakenridge 2006; Brakenridge et al. 2007).
Khan et al. (2011a) emphasized the use of the iterative self-organizing data analysis