TY  - CONF
AU  - Alemu, Henok
AU  - Velpuri, N.M.
AU  - Senay, Gabriel B.
AU  - Angerer, J.
A2  - San Francisco, Calif.
ED  - in
PY  - 2011//
TI  - A multi-index approach to delineate surface water bodies in the pastoral regions of Mali using ASTER imagery [abs.]
T2  - abstract number H21F-1196
BT  - Fall Meeting
VL  - Fall Meeting Abstracts
PB  - American Geophysical Union
CY  - Washington, D.C.
KW  - Africa
KW  - area
KW  - ASTER
KW  - band
KW  - bands
KW  - conference abstracts
KW  - data
KW  - dynamics
KW  - early warning
KW  - East Africa
KW  - hydrologic modeling
KW  - identification
KW  - image
KW  - imagery
KW  - livestock
KW  - Mali
KW  - map
KW  - migration
KW  - modeling
KW  - monitoring
KW  - NDWI
KW  - Normalized Difference Water Index
KW  - research
KW  - resolution
KW  - resources
KW  - satellite
KW  - satellite data
KW  - spatial
KW  - spatial distribution
KW  - spatial resolution
KW  - spectral band
KW  - surface water
KW  - temporal
KW  - trend
KW  - warning system
KW  - water
KW  - water bodies
KW  - water index
KW  - water level
KW  - water resource
N2  - Information on the location and availability of water resources is a day-to-day challenge for pastoralists in the Sahelian region of Mali. They move seasonally along their migration corridors in search for water and forage. Satellite data can be used to map the spatial and temporal dynamics of these water resources. In this work, ASTER imagery is selected for its high (15 m) spatial resolution and suitable spectral bands for water body identification. Our research indicates that as most of the waterholes of interest in the study area are very shallow and heavily sediment-laden, using only one of those commonly used water identification indices such as the Simple Band Ratio (SBR), or the Normalized Difference Water Index (NDWI) alone does not help in effectively characterizing all the surface water bodies in the region. As a result, we used four different spectral indices to identify surface water features: (i) Simple Band Ratio (SBR), (ii) Normalized Difference Water Index (NDWI), (iii) Modified Normalized Difference Water Index (MNDWI), and (iv) the Mean Absolute Deviation (MAD) to identify and delineate surface water bodies using 91 ASTER images. Initial results indicate that the SBR method identified 17 waterholes while the NDWI 18, the MNDWI 36, and the MAD method identified 28 waterholes. However, by combining the results from the four aforementioned spectral indices following a multi-index approach, 89 waterholes that were previously unidentified by a single approach alone were identified. Furthermore, our analysis indicates that the SBR and the NDWI methods identify relatively clearer waterholes better (29% of the waterholes), whereas MNDWI and MAD proved to be good indices for identifying sediment-laden waterholes. Identifying the location and spatial distribution of surface water bodies is the first step towards monitoring their seasonal dynamics using a hydrologic modeling system, similar to an existing setup for east Africa (http://watermon.tamu.edu/). Seasonal trends in relative surface water levels are one of the most important inputs in the livestock early warning system (LEWS) along with forage and livestock market prices.
SN  - http://www.agu.org/meetings/fm11/waisfm11adv.html
UR  - http://www.agu.org/meetings/fm11/waisfm11adv.html
N1  - exported from refbase (http://eros.usgs.gov/refbase/show.php?record=23329), last updated on Fri, 21 Sep 2012 11:59:54 -0500
ID  - Alemu_etal2011
ER  -