Assessing the Evolution in Remotely Sensed Vegetation Index Using Image Processing Techniques

NATALIA V. REVOLLO; NOELIA REVOLLO; M. ANDREA HUAMANTINCO CISNEROS; CLAUDIO A. DELRIEUX; CINTIA PICCOLO

ANUáRIO DO INSTITUTO DE GEOCIêNCIAS

UFRJ/CCMN

Año: 2019 vol. 3 p. 27 - 41

0101-9759

Vegetation has a substantial role as an indicator of anthropic effects, specifcally in cases where urban planningis required. This is especially the case in the management of coastal cities, where vegetation exerts several effects thatheighten the quality of life (alleviation of unpleasant weather conditions, mitigation of erosion, aesthetics, among others).For this reason, there is an increased interest in the development of automated tools for studying the temporal and spatialevolution of the vegetation cover in wide urban areas, with an adequate spatial and temporal resolution.We present an automated image processing workflow for computing the variation of vegetation cover using anypublicly available satellite imagery (ASTER, SPOT, LANDSAT, MODIS, among others) and a set of image processingalgorithms specifcally developed. The automatic processing methodology was developed to evaluate the spatial andtemporal evolution of vegetation cover, including the Normalized Difference Vegetation Index (NDVI), the vegetationcover percentage and the vegetation variation. A prior urban area digitalization is required.The methodology was applied in Monte Hermoso city, Argentina. The vegetation cover per city block was computed and three transects over the city were outlined to evaluate the changes in NDVI values. This allows the computation of several information products, like NDVI profles, vegetation variation assessment, and classifcation of cityareas regarding vegetation. The information is available in GIS-readable formats, making it useful as support for urbanplanning decisions