Assessing optical earth observation systems for mapping and monitoring temporary ponds in arid areas

Abstract

Remote sensing methods for locating and monitoring temporary ponds over large areas in arid lands were tested on a study site in Northern Senegal. Three main results are presented, validated with field data and intended to highlight different spectral, spatial and temporal characteristics of the methods: (1) Among several water indices tested, two Middle Infrared-based indices (MNDWIModified Normalized Difference Water Index and NDWI1Normalized Difference Water Index) are found to be most efficient; (2) an objective method is given prescribing the necessary sensor spatial resolution in terms of minimal detected pond area; and (3) the potential of multi-temporal MODIS imagery for tracking the filling phases of small ponds is illustrated. These results should assist in epidemiological studies of vector-borne diseases that develop around these ponds, but also more generally for land and water management and preservation of threatened ecosystems in arid areas

The potential for remote sensing and hydrologic modelling to assess the spatio-temporal dynamics of ponds in the Ferlo Region (Senegal)

“…Generally, the limits of these ponds are delineated by a belt of trees which corresponds to the maximum water extension. Most of the ponds in the study area are small (33% of ponds with an area less than 1000 m 2 and 64% with less than 2600 m 2 ), with the smallest one covering only 74 m 2 and the largest one, Barkedji, covering ∼347 400 m 2 (Soti et al, 2009). The larger ponds are located in the main stream of the Ferlo valley and the smaller ones generally outside.…”

“…In arid areas, the potential of time series from coarse-scale satellites images like NOAA-AVHRR (Verdin, 1996), SPOT-Vegetation (Haas et al, 2006) or Terra-MODIS (Moderate Resolution Imaging Spectroradiometer) to survey large ponds and lakes at a broad spatial scale was demonstrated. Nevertheless, in the Sahel region, the spatial resolution of those sensors is inappropriate (Soti et al, 2009) for identifying water bodies with a surface area of less than 170 000 m 2 (Soti et al, 2009), which is the case for most of the ponds there. Recently, it was shown that the new generation of high and very high spatial resolution remote sensing data (Landsat Enhanced Thematic Mapper, SPOT5 and Quickbird images) is suitable for the detailed mapping of temporary water bodies at a local scale (Liebe et al, 2005;Lacaux et al, 2007;Soti et al, 2009).…”

“…Nevertheless, in the Sahel region, the spatial resolution of those sensors is inappropriate (Soti et al, 2009) for identifying water bodies with a surface area of less than 170 000 m 2 (Soti et al, 2009), which is the case for most of the ponds there. Recently, it was shown that the new generation of high and very high spatial resolution remote sensing data (Landsat Enhanced Thematic Mapper, SPOT5 and Quickbird images) is suitable for the detailed mapping of temporary water bodies at a local scale (Liebe et al, 2005;Lacaux et al, 2007;Soti et al, 2009). The potential of radar satellite images (Annor et al, 2009;Di Baldassarre et al, 2009;) for water body inventory have also been improved, with the advantage of being independent of cloud cover (Horritt et al, 2001;Herold et al, 2004).…”

Fine-scale mapping of vector habitats using very high resolution satellite imagery: a liver fluke case-study

“…vegetation or water, to enhance classification results. Based on information gathered from other studies on water bodies (Lillesand et al, 2004;Soti et al, 2009Soti et al, , 2010Wolf, 2010), the following indices were created and explored in view of SWB delineation: the normalised difference water index (NDWI) = (coastal blue -NIR2) / (coastal blue + NIR2), the standing water index (SWI) = (blue -NIR1)/(blue + NIR1) and the normalized difference vegetation index (NDVI) = (NIR1 -red) / NIR1 + red). These indices, together with the hue (red, green, blue) transformation, were incorporated in the analysis.…”

“…spatial resolution of <5 m, has made it possible to acquire spatial accuracy at sub-meter scales thereby allowing the detection of water bodies that cover only a few m 2 . However, few initiatives have been undertaken to monitor SWBs using VHR satellite imagery (Dambach et al, 2009;Soti et al, 2009;Soti et al, 2010). Many studies use the freely available Landsat imagery (about 30-m resolution) and medium (20 m to 100 m) or coarse (>100 m) resolution imagery (Fuentes et al, 2001;Malone et al, 2001;Guo et al, 2005;Daniel et al, 2006;de Castro et al, 2006;Estallo et al, 2012).…”