Year: 2005
Type: article
Abstract: This paper provides spatial and georeferenced information related to the susceptibility to desertification of several areas of the Northeast of Brazil. We aim to test the usefulness of spatial analysis methodologies to capture spatial-temporal heterogeneity from environmental gradients, for the assessment of desertification process at Remote Sensing data. In this sense, the analysis and integration of geo-environmental variables and the creation of environmental indicators associated with the development of the desertification process was performed, based on the use of spatial modeling procedures applied to data from the semi-arid portion of the Northeastern Brazil region. A set of sixteen-year period of Landsat 5-TM and Landsat 7 ETM+ images were explored for vegetation and soil study and local analysis of association and variability of spectral data were performed. The integration of the georeferenced data, related to these indicators, allowed the identification of five different levels of susceptibility to desertification (very high, high, moderate, low and very low), and the geographic domain of each class. Based on the analysis of the dynamics of the vegetation cover and on the evaluation of field data, we can establish that the main results refer that there is a decrease of the biomass at the region, associated either with the dense caatinga vegetation areas, but more important, with the scrub and degraded areas. From an environmental perspective, the decreasing biomass level associated with scrub and degraded areas are according to the negative feedbacks of the desertification process. Considering the last ten-year periods of comparisons, the spatial variances leave almost different, which means that heterogeneity pattern, is increasing very considerably. This fact means an explicit expansion of spatial heterogeneity of the desertification landscapes, during the last years. KeyWords: Desertification, Environmental Indicators, Environmental Analysis, Susceptibility, Geoprocessing, Geographic Information Systems (GIS), Spatial Modeling, Semi-arid, Northeastern region, Seridó, Rio Grande do Norte, Brazil.
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
SDGs: Life on land, Climate action
Open Access status: green
OpenAlex ID: W17429577