Abstract
BackgroundRemote sensing technology provides detailed spectral and thermal images of the earth's surface from which surrogate ecological indicators of complex processes can be measured.MethodsRemote sensing data were overlaid onto georeferenced entomological and human ecological data randomly sampled during April and May 2001 in the cities of Kisumu (population ≈ 320,000) and Malindi (population ≈ 81,000), Kenya. Grid cells of 270 meters × 270 meters were used to generate spatial sampling units for each city for the collection of entomological and human ecological field-based data. Multispectral Thermal Imager (MTI) satellite data in the visible spectrum at five meter resolution were acquired for Kisumu and Malindi during February and March 2001, respectively. The MTI data were fit and aggregated to the 270 meter × 270 meter grid cells used in field-based sampling using a geographic information system. The normalized difference vegetation index (NDVI) was calculated and scaled from MTI data for selected grid cells. Regression analysis was used to assess associations between NDVI values and entomological and human ecological variables at the grid cell level.ResultsMultivariate linear regression showed that as household density increased, mean grid cell NDVI decreased (global F-test = 9.81, df 3,72, P-value = <0.01; adjusted R2 = 0.26). Given household density, the number of potential anopheline larval habitats per grid cell also increased with increasing values of mean grid cell NDVI (global F-test = 14.29, df 3,36, P-value = <0.01; adjusted R2 = 0.51).ConclusionsNDVI values obtained from MTI data were successfully overlaid onto georeferenced entomological and human ecological data spatially sampled at a scale of 270 meters × 270 meters. Results demonstrate that NDVI at such a scale was sufficient to describe variations in entomological and human ecological parameters across both cities.
Highlights
Introduction to Survey SamplingNewbury Park: Sage Publications 1983.26
The high normalized difference vegetation index (NDVI) value detected for images A and C are expected, as both sites are in residential areas with high levels of vegetation
The level of error associated with the registration process and Trimble global positioning system (GPS) collected data points may be such that the true site is 0 to 15 meters from the swimming pool
Summary
Introduction to Survey SamplingNewbury Park: Sage Publications 1983.26. Grimm NB, Grove M, Pickett STA, Redman CL: Integrated approaches to long-term studies of urban ecological systems. High resolution passive remote sensing systems, such as the Multispectral Thermal Imager (MTI) satellite, provide detailed spectral and thermal images of the earth's surface from which surrogate ecological indicators of complex processes can be measured [8]. Such remote sensing systems may, prove to be useful in assessing ecological changes within vast, highly heterogeneous urban areas. The scarcity of resources, coupled with the need for regular surveillance, requires the development of novel methods for the collection and analysis of ecological data
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