TCC - Engenharia Agrícola e Ambiental (Sede)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/430
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Resultados da Pesquisa
Item Identificação operacional de áreas com potencial de regeneração e/ou recuperação vegetal nas mesorregiões Sertão e São Francisco pernambucano(2023-07-17) Gouveia, José Rafael Ferreira de; Nascimento, Cristina Rodrigues; http://lattes.cnpq.br/9289129949520610; http://lattes.cnpq.br/5471553264542605Fire has been used for many years in Brazil, serving for various purposes. However, if handled wrongly, it can cause fires with immense damage to the environment. The Sertão and São Francisco Pernambucano mesoregions are susceptible to the occurrence of fires, since the predominant biome is the Caatinga, semi-arid climate and low rainfall. This article aims to characterize and quantify hot spots and operationally identify fires in the mentioned mesoregions in the period from 2014 to 2020, in the driest months of the year, as well as the power of plant regeneration. The images from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board the TERRA platform, products MOD14A1, MOD09GQ, MOD13Q1 and MOD09Q1 were used in order to characterize the areas affected by hot spots, analyze the Normalized Difference Vegetation Index (NDVI) and implement a script on the Google Earth Engine (GEE) platform for the operational identification of areas with potential for plant regeneration. Results show an increasing behavior in the number of hot spots, with a reduction in the year 2020. The year 2019 had the highest number of regenerated areas, with 37. The script proved to be effective with minimum hits of 56%, being in mostly greater than 75%. In addition, the maximum errors were 25% of omission in October 2020 and 43.75% of commission in September 2016. In this sense, the techniques employed were able to detect the regions affected by the fires, as well as their potential for plant regeneration.Item Dinâmica espaço-temporal da cobertura vegetal, das queimadas e da expansão da bovinocultura na bacia leiteira do estado de Pernambuco usando Landsat-8 e MapBiomas(2022-12-12) Melo, Maria Vitória Neves de; Almeida, Gledson Luiz Pontes de; http://lattes.cnpq.br/2328849810614673; http://lattes.cnpq.br/8193771315370090The semi-arid is responsible for about 58% of the effective herd in the Brazilian Northeast region (NEB), however, there are local and meteorological factors that limit the semi-arid region. The objective was to evaluate the space-time dynamics of vegetation cover through the Soil-Adjusted Vegetation Index (SAVI) and Pasture Plant Coefficient (CVP) via Landsat-8/OLI images processed in the cloud on Google Earth Engine (GEE), measuring the scenarios of burned areas and characterizing the expansion of cattle farming in the dairy basin in the state of Pernambuco through land use and cover (LULC) and its impacts on the Caatinga Biome. The study region comprises the 23 municipalities that produce the most milk in the state, between 2016 and 2021, divided into dry and rainy seasons. The Vegetation Indexes were processed in the GEE and the spatialization of the rain was made through the Climate Hazards Group InfraRed Precipitation with Station data (CRHIRPS) and both data were submitted to descriptive statistics. LULC thematic maps and burned areas were processed in QGIS software. Thus, it was observed that in the dry and rainy period from 2016 to 2020, there was average precipitation of 77.98 mm and 331.19 mm, respectively. In the rainy season of 2016, less precipitation was observed when compared to the other years of the study, as it was the period that was influenced by the great droughts that preceded the year in question. As for the vegetation indices in the dry period, the SAVI presented lower spectral responses throughout the study period, as a result of low precipitation in the region and the rainy season with high biomass activity with values above 0.78. The SAVI and CVP showed medium to high variability. The burned areas showed that anthropic activities in some sectors of the basin caused the change in the LULC, resulting in degradation processes, even in regions with greater precipitation. Therefore, it is concluded that the analysis of the products CHIRPS, SAVI, CVP associated with the descriptive statistics and the maps of the LULC and burned area, was efficient for the space-time characterization of the expansion of cattle farming in the dairy basin of the state of Pernambuco throughout the study period.