73 research outputs found
Supplemental Material - Cutting Down Trees Does not Build Prosperity: On the Continued Decoupling of Amazon Deforestation and Economic Development in 21st Century Brazil
No full textSupplemental Material for Cutting Down Trees Does not Build Prosperity: On the Continued Decoupling of Amazon Deforestation and Economic Development in 21st Century Brazil by Darren Norris, Terciane Sabadini Carvalho, Angela M. Guerrero, Maria Isabel Sobral Escada, Ane Alencar, Liz Kimbrough, and Rhett A. Butler in Tropical Conservation Science</p
Supplemental Material - Cutting Down Trees Does not Build Prosperity: On the Continued Decoupling of Amazon Deforestation and Economic Development in 21st Century Brazil
No full textSupplemental Material for Cutting Down Trees Does not Build Prosperity: On the Continued Decoupling of Amazon Deforestation and Economic Development in 21st Century Brazil by Darren Norris, Terciane Sabadini Carvalho, Angela M. Guerrero, Maria Isabel Sobral Escada, Ane Alencar, Liz Kimbrough, and Rhett A. Butler in Tropical Conservation Science</p
Análise do uso e cobertura da terra associados à atividades extrativistas e à agricultura de pequena escala: a região do Baixo Tocantins, PA
No full textThis study presents the results of the research on the production systems related to land use in the municipalities of Mocajuba, Cametá and part of Baião and Moju, in the State of Pará, with emphasis on small scale systems and agroforestry. These systems can be seen as alternatives for the sustainable use of the forest and are of great importance for the regional economy, but still not visible to the planning of the territory and the public policies. Land use and land cover monitoring systems from INPE, which use satellite data, such as Landsat, provide data since 2004. However, due to the spatial resolution of these sensors, the land use and land cover categories small-scale agriculture and agroforestry activities are poorly detected. Thus, the objective of this work was to develop a methodology to classify these areas. The economics of the area are strongly based on the production of açaí, however, the occurrence areas of the açaí are generally not mapped, since they present similar spectral responses to the areas of primary and / or secondary forest coverage. For this reason, complementary data for the mapping of this system are necessary, such as the limits of floodplain areas, where potentially occur the açaí trees. In this work, we tested in a pilot area, images from the PAN10/CBERS and OLI/Landsat satellites for the year 2016 and three classification algorithms, image slicing obtained with the Linear Spectral Mixing Model, one classifier per pixel (MaxVer) and another by regions (Bhattacharya). The following classes were mapped: Forests, Hydrography, Non-forest, Advanced Secondary Vegetation (VSA), Inicial Secondary Vegetation (VSI) and Others. The best result was the PAN10/CBERS image with TerraClass methodology with Kappa index 0.80, however, due to the high cloud cover in the images of the year 2016, the slicing and the OLI/Landsat image were used, with indexes of correctness 92% for VSA, 84% for VSI and 97% for Others. The...Este trabalho apresenta os resultados da pesquisa sobre os sistemas de produção relacionados com uso da terra dos municípios de Mocajuba, Cametá e parte de Baião e Moju, no Estado do Pará, tendo como ênfase os sistemas de pequena escala e os agroflorestais. Estes sistemas podem ser vistos como alternativas para o uso sustentável da floresta e são de grande importância para a economia regional, mas ainda pouco visíveis ao planejamento do território e às políticas públicas. Os sistemas de monitoramento do uso e cobertura da terra da Amazônia do INPE, que utilizam de dados de satélite, como os do Landsat, fornecem dados desde 2004. Porém, devido a resolução espacial destes sensores, as categorias de uso e cobertura da terra relativas à agricultura de pequena escala e às atividades agroflorestais são pouco detectadas. Assim, o objetivo deste trabalho foi desenvolver uma metodologia para classificar estas áreas. A economia da área se baseia fortemente na produção do açaí, porém, as áreas de ocorrência do açaí, em geral não são mapeadas, pois apresentam respostas espectrais semelhantes às áreas de cobertura florestal primária e/ou secundária. Por essa razão, dados complementares para o mapeamento desse sistema são necessários, como os limites de áreas de várzeas, onde potencialmente ocorrem os açaizeiros. Neste trabalho, testamos em uma área piloto, imagens provenientes dos satélites PAN10/CBERS e OLI/Landsat para o ano de 2016 e três algoritmos de classificação, fatiamento de imagens obtidas com o Modelo Linear de Mistura Espectral, um classificador por pixel (MaxVer) e outro por regiões (Bhattacharya). As seguintes classes foram mapeadas: Florestas, Hidrografia, Não-floresta, Vegetação Secundária Avançada (VSA), Vegetação Secundária Inicial (VSI) e Outros. O melhor resultado foi a imagem PAN10/CBERS com metodologia do TerraClass com índice Kappa 0,80, entretanto, devido a alta cobertura de..
Landsat and Sentinel-2 based analysis of land use in the Brazilian Amazon: The agricultural frontier of Novo Progresso
No full textDer Amazonas befindet sich im Wandel. Seine Regenwälder sind zunehmend durch die expandierende Landwirtschaft bedroht. Brandrodungen und die meist extensive Weidewirtschaft verantworten großflächige Ökosystemschäden und hohe Treibhausgasemissionen. Erdbeobachtungssysteme wie die Landsat und Sentinel-2 Satelliten ermöglichen eine großflächige Analyse dieser Entwicklungen und sind unerlässlich zur Evaluierung von Maßnahmen zum Schutze des Amazonas. Allerdings sind in den Kerntropen Fernerkundungsanalysen aufgrund des Bewölkungsgrades sehr herausfordernd. Diese Arbeit zielt daher auf eine verbesserte Erkennung landwirtschaftlicher Prozesse, wie sie an Entwaldungsfronten und speziell in der Region Novo Progresso, Pará, Brasilien, typisch sind. Dazu wurde zunächst der EO Time Series Explorer entwickelt, um verschiedene Dimensionen dichter Multisensorzeitserien interaktiv zur Erstellung von Referenzdaten in Wert zu setzen. Mit den Clear Observation Sequences (COS) wurde darauf basierend ein neuer Ansatz zur Erfassung hoch-dynamischer landwirtschaftlicher Prozesse entwickelt, etwa Feuer mit geringer Brandlast oder Bodenbearbeitungsmaßnahmen. Darauf aufbauend wurde schließlich der Landnutzungswandel in der Region Novo Progresso zwischen 2014 und 2020 untersucht. Die Ergebnisse zeigen einen alarmierenden Anstieg der Entwaldung und eine Zunahme landwirtschaftlicher Feuer seit der Präsidentschaft von Jair Bolsonaro. Differenziert nach Landnutzungszonen und Betriebsgrößen wird deutlich, dass Schutzgebiete weniger wirksam sind und insbesondere größere Landwirtschaftsbetriebe die Entwaldung vorantreiben. Diese Arbeit zeigt den hohen Wert einer synergetischen Nutzung unterschiedlicher Satellitenzeitserien für die fernerkundliche Analyse landwirtschaftlicher Prozesse. Eine weitere Verdichtung der Zeitserien mit räumlich und spektral höherauflösenden Sensoren bietet weiteres Verbesserungspotential bei der Beschreibung landwirtschaftlicher Dynamiken.The Amazon is in transition, and its rainforests are increasingly threatened by agricultural expansion. A slash-and-burn agriculture and mostly extensive cattle grazing are responsible for large-scale ecosystem damage and high levels of greenhouse gas emission. Earth observation systems such as the Landsat and Sentinel-2 satellites enable large-scale analysis of these developments and are essential for evaluating measures to protect the Amazon. However, cloud cover makes remote sensing analysis challenging in the core tropics. The present work aims to improve the detection of agricultural processes typical of deforestation frontiers, focusing specifically on the Novo Progresso region, Pará, Brazil. To that end, the EO Time Series Explorer was developed to interactively visualize the different dimensions of dense multi-sensor time series and to create reference data. Based on this software tool, the Clear Observation Sequences (COS) approach was developed to capture highly dynamic agricultural processes such as low-load fires or tillage operations. Finally, the investigation of land-use changes in the Novo Progresso region between 2014 and 2020 shows an alarming increase in deforestation and agricultural fires since Jair Bolsonaro’s accession to the presidency. Analysis by land-use zone and property size shows that protected areas have become less effective and that larger properties are driving deforestation. This work demonstrates the value of synergistic use of satellite time series for remote sensing analysis of agricultural processes. Further densification of time series using higher spatial and spectral resolution sensors promises to further improve the description of agricultural dynamics
Indicadores para a compartimentação da paisagem em unidades de ocupação em uma região de fronteira agrícola em Rondônia
No full textThis work investigates the partitioning of space in areas of recent colonization in Rondônia, Brazilian Amazônia, based on the history of occupation and geomorphological characteristics. Such partitionings of the space can bring about a better understanding of the roles of the deforestation actors, and the effects of their action in landscape transformation. Visual interpretation of satellite imagery, cluster analysis and spatial auto-correlation analysis are used to characterize homogeneous areas.Pages: 585-58
Detecção e Classificação de padrões da Degradação Florestal na Amazônia por meio de banco de dados celular
No full textForest degradation is a threat looms over Amazon forest. Detection and Recognition of Forest Degradation patterns are important to address forest state. This study presents the asset of application of a novel free system for spatial data mining, called GeoDMA, for distinguishing patterns in forest degradation in Brazilian Amazon. Types were related to progressive events of decreasing forest canopy. An analysis of land cover dynamic, from satellite image time series, is also showed. Method was based on cell database construction, landscape metrics and data mining techniques. Cell-based classification, provided by GeoDMA, proved to be useful in distinguishing forest degradation patterns. Errors were mostly caused by spatial and spectral resolution constraints of Landsat images (30m) than to the rules used to perform classification. Cell data base construction with resolution of 1km2 was suitable to represent forest degradation typologies. However, we recommend future studies to test finer resolution. Time analyses interval of three years between series data was not appropriate to represent land cover dynamics. Fast transition between forest and clear-cut requires analysis at annual-basis to better determine and detect forest degradation and their trajectories. Patterns have found to São Félix do Xingu may not be enough to represent all the patterns one can distinguish in Amazon region.Pages: 3397-340
Effects of Deforestation over the Cerrado Landscape: A Study in the Bahia Frontier
No full textThe losses in the Brazilian Cerrado raise the need to understand the border regions between human activities and Cerrado remnants. This work aims to answer the questions: How does the landscape change in a deforestation area in the Brazilian Cerrado, and where do the losses of native Cerrado occur in the landscape context? We chose the Cerrado of Bahia, an area of the agricultural frontier, and used landscape metrics, and land use and land cover data from 2013 and 2020, to quantify the changes in the landscape. We built a typology of landscape patterns to classify and characterize the Cerrado landscapes, based on the landscape metrics, and land use and land cover data from TerraClass Cerrado 2013. From these parameters, a decision tree classifier enabled the classification of the landscape types. Then, we used the yearly deforestation data from PRODES Cerrado to obtain the native cover and the landscape metrics for 2020. The predominant landscape in 2013 was the Intermediate Stage of Fragmentation (32.53%), followed by the Initial Stage of Fragmentation (31.26%), Consolidated Pasture (16.4%), Consolidated Agriculture (9.78%), Mixed Landscapes (5.59%) and Native Cerrado (4.70%). The continuous Cerrado borders on areas in an initial and intermediate stage of fragmentation, putting pressure on the native area. The losses in native cover do not occur in consolidated landscapes or inside the continuous Cerrado. Instead, there is a process of vegetation conversion over the landscapes in the initial and intermediate stages of fragmentation, and landscapes where the matrix is heterogeneous. These factors signal the need to preserve the contiguous fragments of Cerrado
Data Mining Using NDVI Time Series Applied to Change Detection
No full textQuantifying and monitoring woody cover distribution in semiarid regions is challenging, due to their scattered distribution. Data mining has been widely used with remote sensing data for the information extraction of spectral and temporal data in the analysis of change detection. The main objective of this study was to characterize the land cover and use over the 2000–2010 time period for the Brazilian Caatinga seasonal biome using a temporal Normalized Difference Vegetation Index (NDVI) series and Geographic Object-Based Image Analysis (GEOBIA). For each of the target years NDVI images were derived from a Moderate Resolution Imaging Spectroradiometer (MODIS, MOD13Q1, at a 250 m spatial and 16-day temporal scale) sensor during the dry season to predict wood cover in the municipality of Buriti dos Montes, in the state of Piaui in the north-east region of Brazil (H13V09 tile). The images were automatically pre-processed and the GEOBIA approach was performed for image segmentation, spatial and spectral attribute extraction and labelling according to the following legend, tree cover (TC) and cropland/grass (CG), to obtain a classification using the decision tree supervised algorithm. Our results showed that the approach using GEOBIA presented a Kappa index of 0.58 and global accuracy (GA) of 0.81% and showed better accuracy for the tree cover. Finally, we recommend new studies adding others parameters strongly related to the vegetation of semiarid regions
HAND TERRAIN DESCRIPTOR FOR REGIONAL SCALE MAPPING OF AMAZON TERRA FIRME ECO-HYDROLOGICAL UNITS
No full textThe HAND (Height Above the Nearest Drainage), a quantitative topographic descriptor, is used to classify terrain in a manner that is related to local soil water conditions, providing hydrological meaning to the SRTM DEM. In this paper, we compare performance of using the HAND grid instead of the SRTM DEM for classifying, at regional scale (19 000 000 km2), drainage conditions of terra firme environment (plateau, slope, ecotone and waterlogged) in the Eastern Amazon, Brazil. Additionally, we emphasize the need to attenuate the canopy effects of the SRTM DEM for the boundary between forested and deforested areas, in order to produce coherent data for hydrological modeling
Dinâmica de padrões de mudança de uso e cobertura da terra na região do Distrito Florestal Sustentável da BR-163
No full textThe objective of this study is to analyze the relationship between land cover dynamic in regions with different occupation stages of the agricultural frontier in the Sustainable Forest District of BR-163 (SFD) for the period of 1997 to 2008. The analysis were performed based on temporal evolution of deforestation patterns for 1997, 2000, 2003 and 2007, and secondary vegetation analysis from 2000 to 2008. We described six different deforestation pattern associated to different occupation process. We worked with cells of 10 X 10 km and we used data mining techniques and landscape metrics, to detect deforestation patterns. We grouped the deforestation patterns in four groups according to the trajectories presented by them in the analysis period. The frontier stage typology proposed by Diniz in 2002 was confronted with our results. The author typology showed to be useful but the results showed that it is necessary to make some adaptations and adjust to represent the process identified in the study area.Pages: 6152-616
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