Monitoring of Brazilian Deciduous Seasonal Forest by Remote Sensing

Abstract

Among the many characteristics that the Brazilian territory possesses, one precisely excel: the mentioned country hosts the second biggest forest resource of the planet, corresponding for approximately 10% of the total amount of global forest resources. In that scenario, the Seasonally Dry Tropical Forests (SDTF) perform the second less expressive forest type in Brazil, being situated mostly in non-forested biomes, such as Savannas and Scrublands. Thus, its conservation must rely on its correct identification, which becomes difficult because the SDTF areas are generally classified as other vegetation types. Therefore, the present study aimed to perform the land cover-land use monitoring for the years of 2007 and 2016 of the continuous area North of Minas Gerais - South Piauí, with the purpose of evaluating the current situation of Brazilian SDTFs and assessing the main drivers that affect its deforestation and natural regeneration. As a result, the study verified that the significant increase in crop areas and spatial mobility of parturelands contributed decisively for the changes presented by vegetation formations. HOWEVER, such drivers played differentiated roles in losses/gains. Especially, it was concluded that the changes in which deciduous forests have undergone were explained particularly by pasture. The other types of vegetation were also impacted by this class, but with a more incisive participation of the crops. Key-words: Mapping, Deciduous Forests, Remote Sensing, GIS.

Surface temperature behavior in view of the conversion of tropical dry forest into anthropic uses, northern Minas Gerais–Brazil

“…Changes in the land use and land cover context for the domain of TDFs have been reported by several authors [ 23 , 24 , 36 ]. Dupin et al [ 23 ] indicated that between 2000 and 2015 there was a net loss in the order of 3302 km 2 .…”

“…The study area comprises the southern sector of the ecoregions: Caatinga and Brazilian Atlantic dry forests, two of the 56 ecoregions that compose the Tropical and subtropical broadleaf dry forest biome–neotropic realm ( Fig 1 ). Such area was chosen mainly by 1) possessing historic of TDFs conversion to anthropic uses [ 23 , 24 ], 2) status of nature imperiled in the categorization scheme of levels of protection for ecoregions presented by Dinerstein et al [ 2 ], 3) compose two of the four most extended ecoregions areas of TDFs in the neotropics, 4) encompassing areas with a high level of annual carbon sequestration [ 25 ]. In view of those criteria, the north of the state of Minas Gerais was taken as an area of investigation, being situated between latitudes 14° and 18°S, longitudes 46° and 42W°.…”

“…For the spatial representation of anthropic and natural domains, we used the products provided by Rocha et al [ 24 ], derived from the mapping of land uses and land cover between the north of the state of Minas Gerais and the south of Piauí (the northeast portion of Brazil) for 2007 and 2016. To map the forests in this portion of Brazil, the authors used the MOD13Q1 products (250 meters spatial resolution) from the MODIS sensor [ 29 ].…”

“…The modeling was done from supervised classification with the decision tree algorithm [ 30 ]. Based on validation processes, the authors obtained an overall accuracy of 89.40% and a kappa coefficient of 86.79% [ 24 ].…”

“…Originally, the mapping by Rocha et al [ 24 ] has six classes (TDFs, crops, pastures, urban areas, water bodies, and other vegetation), however, for our study, only three were used (TDFs, crops, and pastures). Rocha et al [ 24 ] obtained commission and omission errors for the land use and land cover classes, in which TDFs had 15% and 26.84%, pastureland 28% and 19.86%, and crops 6.4% and 3.14%, respectively.…”