Spatial - Temporal Analysis of the Use and Land Cover in the Rio da Cruz Micro Basin of the Semi-arid Region of Paraíba, Using Remote Sensing
Denize Monteiro dos Anjos *
Department of Forestry Engineering, Federal University of Campina Grande, Av. Universitária s/n - Bairro Santa Cecília, Patos-PB, 58708-110, Brazil.
Ivonete Alves Bakke
Department of Forestry Engineering, Federal University of Campina Grande, Av. Universitária s/n - Bairro Santa Cecília, Patos-PB, 58708-110, Brazil.
Ewerton Medeiros Simões
Department of Forestry Engineering, Federal University of Campina Grande, Av. Universitária s/n - Bairro Santa Cecília, Patos-PB, 58708-110, Brazil.
Olaf Andreas Bakke
Department of Forestry Engineering, Federal University of Campina Grande, Av. Universitária s/n - Bairro Santa Cecília, Patos-PB, 58708-110, Brazil.
Diógenes Félix da Silva Costa
Department of Forestry Engineering, Federal University of Campina Grande, Av. Universitária s/n - Bairro Santa Cecília, Patos-PB, 58708-110, Brazil.
*Author to whom correspondence should be addressed.
Abstract
The changes that occur in ecosystems are increasingly coming from anthropogenic actions. In microbasins, these changes become more noticeable and can be detected using remote sensing techniques. The Rio da Cruz microbasin, meso-region of Sertão Paraibano. Field visits were made to identify the vegetation cover and forms of land use. Then, satellite images of the three-year rainy and dry periods were used: 2001, 2009 and 2017. The following steps were performed, image processing: pre-processing; processing and post-processing. Seven classes were selected: Arboreal Caatinga, Arboreal Shrub Caatinga, Anthropized Caatinga, Pastures and Agriculture, Rocky Outcrops, Water Bodies and Buildings. The results demonstrated an advance of the antropic action in the areas near the bodies of water. The temporal analysis of the watershed of the River of the Cross allowed to verify the reduction of the Arboreal Caatinga and increase of the Arboreal Shrub Caatinga, Anthropized Caatinga and Pasture and Agriculture areas in the studied years. Remote sensing techniques and knowledge of the microbasin result in relevant information on the use and cover of the land in years of regular precipitation and in conditions of greater precipitation, the arboreal vegetation is overestimated, making it difficult to identify anthropic areas during the rainy season.
Keywords: Caatinga bioma, supervised classification, remote, sensing, satellite images