6 resultados para Land cover classification

em Repositório Alice (Acesso Livre à Informação Científica da Embrapa / Repository Open Access to Scientific Information from Embrapa)


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We studied the Paraíba do Sul river watershed , São Paulo state (PSWSP), Southeastern Brazil, in order to assess the land use and cover (LULC) and their implication s to the amount of carbon (C) stored in the forest cover between the years 1985 and 2015. Th e region covers a n area of 1,395,975 ha . We used images made by the Operational Land Imager (OLI) sensor (OLI/Landsat - 8) to produce mappings , and image segmentation techniques to produce vectors with homogeneous characteristics. The training samples and the samples used for classification and validation were collected from the segmented image. To quantify the C stocked in aboveground live biomass (AGLB) , we used an indirect method and applied literature - based reference values. The recovery of 205,690 ha of a secondary Native Forest (NF) after 1985 sequestered 9.7 Tg (Teragram) of C . Considering the whole NF area (455,232 ha), the amount of C accumulated al ong the whole watershed was 3 5 .5 Tg , and the whole Eucalyptus crop (EU) area (113,600 ha) sequester ed 4. 4 Tg of C. Thus, the total amount of C sequestered in the whole watershed (NF + EU) was 3 9 . 9 Tg of C or 1 45 . 6 Tg of CO 2 , and the NF areas were responsible for the large st C stock at the watershed (8 9 %). Therefore , the increase of the NF cover contribut es positively to the reduction of CO 2 concentration in the atmosphere, and Reducing Emissions from Deforestation and Forest Degradation (REDD + ) may become one of the most promising compensation mechanisms for the farmers who increased forest cover at their farms.

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Understanding spatial patterns of land use and land cover is essential for studies addressing biodiversity, climate change and environmental modeling as well as for the design and monitoring of land use policies. The aim of this study was to create a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008. Deforestation data from and uses were mapped with Landsat-5/TM images analysed with techniques, such as linear spectral mixture model, threshold slicing and visual interpretation, aided by temporal information extracted from NDVI MODIS time series. The result is a high spatial resolution of land use and land cover map of the entire Brazilian Legal Amazon for the year 2008 and corresponding calculation of area occupied by different land use classes. The results showed that the four classes of Pasture covered 62% of the deforested areas of the Brazilian Legal Amazon, followed by Secondary Vegetation with 21%. The area occupied by Annual Agriculture covered less than 5% of deforested areas; the remaining areas were distributed among six other land use classes. The maps generated from this project ? called TerraClass - are available at INPE?s web site (http://www.inpe.br/cra/projetos_pesquisas/terraclass2008.php)

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Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.

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The current study approaches the sugarcane culture expansion in Southwestern Goiás, especially in Mineiros, Quirinópolis and Rio Verde counties, which represent different times and responses to this process. The current logistics structure and future prospects for sugarcane and its derivatives transportation are studied at national level with emphasis to the aforementioned micro-region. Maps showing land use and land cover in three different years were generated from Landsat TM-5 satellite images and they were used to analyze the dynamics of changes in land use and in land cover. The region is marked by strong and rapid growth in the agricultural sector and its sugar-energy industry has been expanding in recent years, although with different aspects among its counties. Since it is a promising region in this sector, due to the favorable soil and weather conditions to the crop, the region requires more investment and planning in logistics to ensure production flow and to make it stronger within domestic and foreign markets.

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Soils formed in high mountainous regions in southern Brazil are characterized by great accumulation of organic matter (OM) in the surface horizons and variation in the degree of development. We hypothesized that soil properties and genesis are influenced by the interaction of parent materials and climate factors, which differ depending on the location along the altitudinal gradient. The goal of this study was to characterize and classify the soil, evaluate soil distribution, and determine the interactive effects of soil-forming factors in the subtropical mountain regions in Santa Catarina state. Soil samples were collected in areas known for wine production, for a total of 38 modal profiles. Based on morphological, physical, and chemical properties, soils were evaluated for pedogenesis and classified according to the Brazilian System of Soil Classification, with equivalent classes in the World Reference Basis (WRB). The results indicated that pedogenesis was strongly influenced by the parent material, weather, and relief. In the areas where basic effusive rocks (basalt) were observed, there was formation of extensive areas of clayey soils with reddish color and higher iron oxide contents. There was a predominance of Nitossolos Vermelhos and Háplicos (Nitisols), Latossolos Vermelhos (Ferralsols), and Cambissolos Háplicos (Cambisols), highlighting the pedogenetic processes of eluviation, illuviation of clay, and latosolization in conditions of year-long, large-volume, well-distributed rainfall and stability of land forms. In areas with acid effusive rocks (rhyodacites), medial or clayey soils were observed with lower iron oxide content, invariably acidic, and with low base content. For these soils, relief promoted substantial removal of material, resulting in intense rejuvenation, with a predominance of Cambissolos Háplicos (Cambisols) and lesser occurrence of Nitossolos Brunos (Nitisols) and Neossolos Litólicos (Leptosols). Soils formed from sedimentary rocks also tended to be more acidic, but with higher sand content, and the soils identified were Cambissolos Háplicos and Húmicos (Cambisols). Cluster analysis separated the soil profiles into three groups: the first and largest was formed by profiles originating from sedimentary rocks and rhyodacites; the second, smaller group was formed by four profiles in the Água Doce region (acidic rocks); and the third was formed by profiles derived from basalt. Discriminant analysis was effective in grouping soil classes. Thus, the study highlighted the importance of geology in the formation of soils in this landscape associated with climate and relief.