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Multiscale Hydrologic Remote Sensing: Perspectives and Applications
11.3.2 Satellite ReMote SenSing data
In this study, we used both MODIS and ASTER images in support of flood inundation mapping. MODIS instruments onboard the NASA Terra and Aqua satellites
offer a unique combination of near-global daily coverage with acceptable spatial
resolution. These capabilities are being utilized for flood monitoring at a regional
and global scale. Smith (1997), Brakenridge and Anderson (2003), and Brakenridge
et al. (2003) demonstrated that MODIS data can be used to distinguish between
flooded and nonflooded areas with suitable spatial resolution. This can be very crucial in regions where no other means of flood monitoring are available. NASA’s
Goddard Space Flight Center, through the rapid response system, processes and displays images in near real time or within 2–4 h of retrieval. MODIS rapid-response
data are available from Terra and Aqua in near real time at http://rapidfire.sci.gsfc
.nasa.gov/. This system, initially developed for fire hazard detection and monitoring, can be utilized for flood detection throughout the globe. Several spectral bands
at spatial resolutions of approximately 250 and 500 m are appropriate for accurate
discrimination of water from land. Excluding the effects of cloud cover, there is also
global coverage on a near-daily basis.
One important piece of technology to note is ASTER, which is an imaging instrument flying on the Terra satellite launched in December 1999 as part of NASA’s
Earth Observing System. ASTER is also a cooperative effort between NASA, Japan’s
Ministry of Economy, Trade and Industry, and Japan’s Earth Remote Sensing Data
Analysis Center. ASTER is an advanced multispectral imager with high spatial,
spectral, and radiometric resolution. The ASTER instrument covers a wide spectral
region, from visible to thermal infrared, with 14 spectral bands. It has a total of 14
bands in visible to near-infrared (VNIR), shortwave-infrared (SWIR), and thermalinfrared (TIR) wavelengths. The ground resolutions of the VNIR, SWIR, and TIR
images are 15, 30, and 90 m, respectively (Fujisada et al. 1998; Yamaguchi et al.
1998). Data from this sensor can be acquired on demand from the Land Processes
Distributed Active Archive Center at the Earth Resources Observation Systems Data
Center managed by the United States Geological Survey, with the standard hierarchical data format (http://LPDAAC.usgs.gov). In this study, we followed the strategies for flood inundation mapping and inundation extent investigation based on
the techniques developed by the Dartmouth Flood Observatory (DFO; http://www
. dartmouth.edu/~floods/).
11.3.3 data foR the hydRologic Model
The key remote sensing data sets, which enable the development of a distributed
hydrologic model in the Nzoia subbasin, include the following:
1. The digital elevation data from SRTM (Rabus et al. 2003; http://www2
.jpl.nasa.gov/srtm/) and SRTM-derived hydrologic parameter files of
HydroSHEDS (Lehner et al. 2008).
2. The rainfall data from the TRMM-based multisatellite precipitation analysis 3B42 real time (TMPA 3B42RT) operating in near real time (Huffman
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
11.3.2 Satellite ReMote SenSing data
In this study, we used both MODIS and ASTER images in support of flood inundation mapping. MODIS instruments onboard the NASA Terra and Aqua satellites
offer a unique combination of near-global daily coverage with acceptable spatial
resolution. These capabilities are being utilized for flood monitoring at a regional
and global scale. Smith (1997), Brakenridge and Anderson (2003), and Brakenridge
et al. (2003) demonstrated that MODIS data can be used to distinguish between
flooded and nonflooded areas with suitable spatial resolution. This can be very crucial in regions where no other means of flood monitoring are available. NASA’s
Goddard Space Flight Center, through the rapid response system, processes and displays images in near real time or within 2–4 h of retrieval. MODIS rapid-response
data are available from Terra and Aqua in near real time at http://rapidfire.sci.gsfc
.nasa.gov/. This system, initially developed for fire hazard detection and monitoring, can be utilized for flood detection throughout the globe. Several spectral bands
at spatial resolutions of approximately 250 and 500 m are appropriate for accurate
discrimination of water from land. Excluding the effects of cloud cover, there is also
global coverage on a near-daily basis.
One important piece of technology to note is ASTER, which is an imaging instrument flying on the Terra satellite launched in December 1999 as part of NASA’s
Earth Observing System. ASTER is also a cooperative effort between NASA, Japan’s
Ministry of Economy, Trade and Industry, and Japan’s Earth Remote Sensing Data
Analysis Center. ASTER is an advanced multispectral imager with high spatial,
spectral, and radiometric resolution. The ASTER instrument covers a wide spectral
region, from visible to thermal infrared, with 14 spectral bands. It has a total of 14
bands in visible to near-infrared (VNIR), shortwave-infrared (SWIR), and thermalinfrared (TIR) wavelengths. The ground resolutions of the VNIR, SWIR, and TIR
images are 15, 30, and 90 m, respectively (Fujisada et al. 1998; Yamaguchi et al.
1998). Data from this sensor can be acquired on demand from the Land Processes
Distributed Active Archive Center at the Earth Resources Observation Systems Data
Center managed by the United States Geological Survey, with the standard hierarchical data format (http://LPDAAC.usgs.gov). In this study, we followed the strategies for flood inundation mapping and inundation extent investigation based on
the techniques developed by the Dartmouth Flood Observatory (DFO; http://www
. dartmouth.edu/~floods/).
11.3.3 data foR the hydRologic Model
The key remote sensing data sets, which enable the development of a distributed
hydrologic model in the Nzoia subbasin, include the following:
1. The digital elevation data from SRTM (Rabus et al. 2003; http://www2
.jpl.nasa.gov/srtm/) and SRTM-derived hydrologic parameter files of
HydroSHEDS (Lehner et al. 2008).
2. The rainfall data from the TRMM-based multisatellite precipitation analysis 3B42 real time (TMPA 3B42RT) operating in near real time (Huffman