Evaluation of vegetation cover from IVDN vegetation indexes: possible effects of climate change at Catimbau National Park



The Catimbau National Park (Parna Catimbau) is an environmental conservation unit (CU) created by Decree Law No. 4,340, dated 08/22/2002, in accordance with Federal Law No. 9,985 (SNUC Law). This CU is characterized by being a National Archaeological Heritage by IPHAN and presenting a floristic diversity, which makes it an area of extreme biological importance. However, despite being a region defined by the Ministry of Environment as an integral protection unit, we can see in this area the presence of families and consequent anthropic activities such as agriculture, irrigated production, pastures and other agents that have been contributing to the modification of this Parna. This article aimed to map and evaluate the spectrum-temporal dynamics of the vegetation cover in the Catimbau National Park (PE) area and its possible relationships with climate change, in the period of 2003 and 2016. Remote Sensing techniques such as Normalized Difference Vegetation Index - IVDN, whose values vary in the range of -1 to 1, were applied to the Vegetation study assisted by Landsat 5, TM sensor and Landsat 8, OLI sensor satellite images. The software SPRING was manipulated to create a geographic database and for the development of programming aided by LEGAL in order to correct atmospheric influences, among other parameters. The responses of these analyzes and their respective problematic of the potential contributing factors indicated changes in the vegetation cover with the highest increase for the anthropic area (0.107-0.207) and Soil / Outcrop (0.207-0.307) for the year 2016. These expansions are characteristics of physical, environmental and anthropogenic factors, where they all contribute for hazardous situations in the area. These results indicate the need for social and environmental studies to support environmental management of this conservation unit of the Caatinga biome.


Geoprocessing, Index Vegetation, Environmental Analysis.

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DOI: https://doi.org/10.29150/jhrs.v7.6.p367-377

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Journal of Hyperspectral Remote Sensing - eISSN: 2237-2202