Multitemporal analysis for monitoring land cover and use is an important tool for understanding the evolutionary dynamics of a region, assisting the knowledge on the environmental reality. This study aimed at mapping the land cover classes of the Barra Seca River basin, in northern Espírito Santo, obtained using the Bhattacharya algorithm supervised classification in 1985, 1996, 2006 and 2016. The land use and occupation map allowed characterizing quantitatively the areas identified in the basin map in 10 classes as follows water bodies, agriculture and grasses, dense tree cover, sparse tree cover, exposed soil, wetlands, urban areas, rocky outcrops, shade, and clouds. The landscape maps were obtained using the Patch Analyst extension. In the studied time interval, the land use and occupation in the basin changed little, with areas dominated mostly by agriculture and grasslands, followed by forests while the basin vegetation area also remained mostly unchanged. However, the quantitative analysis using landscape metrics indicates an increasing fragmentation and edge effect in the Barra Seca River basin.
Multitemporal spatial analysis for monitoring land cover and use is an important tool for understanding the evolutionary dynamics of a certain region. This study aims at determining and using landscape ecology indices to map and analyze the forest landscape structure in the Barra Seca River basin, an area of 2,216.56 km 2 , in northern Espírito Santo, in 1985, 1996, 2006 and 2016. The forest patches composing the landscape were isolated and classified by area size using remote sensing techniques by supervised classification and the Bhattacharya algorithm. The landscape metrics and indices in the Patch Analyst extension and
The Atlantic Forest is intensely fragmented and this fragmentation process has caused an expressive increase of forest remnants and, consequently, increased edge effect with different physical-biological intensities in the transition areas between the patch and the matrix. This study used landscape metrics to understand and analyze how different edge effect distances affect the structure of the forest landscape in the Barra Seca River basin (ES), in 1985, 1996, 2006 and 2016. Remote sensing images were processed and using the Bhattacharya algorithm with supervised classification, the forest patches of the study area were classified and isolated. Landscape ecology metrics were computed with Patch Analyst and V-Late 2 Beta extensions. The forest patches were divided into four size classes as follows smaller than 5 ha (C1); between 5 and 10 ha (C2); between 10 and 100 ha (C3); and over 100 ha (C4). The edge effect simulation using landscape metrics was performed using the edge effect distances of 20, 40, 60, 80, 100, 140, and 200 m. Forest fragmentation increased between 1985 and 2016 while the number of patches greater than 100 ha decreased. Currently, the basin landscape consists mainly of small patches, which have larger relative areas affected by edge effect while many patches smaller than 10 ha are completely dominated by edge effect for distances greater than 60 meters. The edge effect simulation for different distances allowed verifying the intensification of the edge effect on the forest patches of the Barra Seca River basin.
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