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

REVOLLO SARMIENTO, G. NOELIA; PICCOLO, MARÍA CINTIA; REVOLLO SARMIENTO, NATALIA V.; DELRIEUX, CLAUDIO A.; HUAMANTINCO CISNEROS, MARÍA ANDREA

ANUáRIO DO INSTITUTO DE GEOCIêNCIAS

UFRJ / CCMN, Centro de Ciências Matemáticas e da Natureza, Instituto de Geociências

Lugar: Rio de Janeiro; Año: 2019 vol. 42 p. 27 - 41

0101-9759

Vegetation has a substantial role as an indicator of anthropic effects, specifically incases where urban planning is required. This is especially the case in the management ofcoastal cities, where vegetation exerts several effects that heighten 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 forstudying the temporal and spatial evolution of the vegetation cover in wide urban areas, withan adequate spatial and temporal resolution.We present an automated image processing workflow for computing the variation ofvegetation cover using any publicly available satellite imagery (ASTER, SPOT, LANDSAT,MODIS, among others) and a set of image processing algorithms specifically developed. Theautomatic processing methodology was developed to evaluate the spatial and temporalevolution of vegetation cover, including the Normalized Difference Vegetation Index(NDVI), the vegetation cover percentage and the vegetation variation. A prior urban areadigitalization is required.The methodology was applied in Monte Hermoso city, Argentina. The vegetationcover per city block was computed and three transects over the city were outlined to evaluatethe changes in NDVI values. This allows the computation of several information products,like NDVI profiles, vegetation variation assessment, and classification of city areas regardingvegetation. The information is available in GIS-readable formats, making it useful as supportfor urban planning decisions.