Title of article :
Classification of ponds from high-spatial resolution remote sensing: Application to Rift Valley Fever epidemics in Senegal
Author/Authors :
Lacaux، نويسنده , , J.P. and Tourre، نويسنده , , Y.M. and Vignolles، نويسنده , , C. and Ndione، نويسنده , , J.A. and Lafaye، نويسنده , , M.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2007
Pages :
9
From page :
66
To page :
74
Abstract :
During the rainy season the abundance of mosquitoes over the Ferlo region (Senegal) is linked to dynamic, vegetation cover and turbidity of temporary and relatively small ponds. The latter create a variable environment where mosquitoes can thrive and thus contribute to diffusion and transmission of diseases such as the Rift Valley Fever (RVF, with Aedes vexans arabiensis and Culex poicilipes mosquitoes) in the Ferlo. The small size and complex distribution of ponds require the use of high-spatial resolution satellite images for adequate detection. Here the use of SPOT-5 images (10 m-resolution) allows for detailed assessment of spatio-temporal evolution of ponds, through two new indices: i.e., the Normalized Difference Pond Index (NDPI), and the Normalized Difference Turbidity Index (NDTI). Small ponds less than 0.5 ha dominate whatever the time period. For example they represent nearly 65% of the total ponds during the peak of the rainy season, up to 90% at the end of the same season. Moreover, another product is proposed: the Zone Potentially Occupied by Mosquitoes (ZPOM). During the apex of the summer monsoon, it is found that RVF mosquitoes occupy 25% of the Ferlo region, while only 0.9% of the same area is covered by ponds. Overlapping areas occupied by grazing cattle and mosquitoes, enhance RVF virus transmission. The remotely sensed operational indices and products presented here are meant to better understand the mechanisms at stake and to contribute to the development of early warning systems in a changing climate and environment.
Keywords :
Senegal , Aedes , Remote sensing , Culex , Rift Valley Fever , ponds
Journal title :
Remote Sensing of Environment
Serial Year :
2007
Journal title :
Remote Sensing of Environment
Record number :
1575009
Link To Document :
بازگشت