Remote‐sensing image mining: detecting agents of land‐use change in tropical forest areas

Silva, Marcelino Pereira dos Santos; Câmara, Gilberto; Escada, Maria Isabel Sobral; Souza, Ricardo Cartaxo Modesto de

doi:10.1080/01431160801950634

Cited by 43 publications

(14 citation statements)

References 31 publications

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“…The methodology of this study was based on Silva et al (2008b), Gavlak et al (2011), andSaito et. al.…”

Section: Methodological Proceduresmentioning

confidence: 99%

“…Considering the deforestation spatial database of the Brazilian Amazon Rainforest Monitoring Program by Satellite (PRODES), many studies have been conducted in the Amazon (ESCADA, 2003;BATISTELLA e MORAN, 2005;SILVA et al, 2008b;SAITO et al, 2011;MAURANO et al, 2019), aiming to analyze typological patterns of deforestation via remote sensing images, relating them to landscape ecology metrics and evolutionary stages of human occupation. These studies agree that the substitution of the open and dense ombrophilous forest in the Amazon is associated with different processes of change in land use and ownership, human occupation of private property in rural areas, and appropriation of natural capital by transnational companies.…”

Section: Deforestation Patterns and Stages Of The Southern Amazon Agr...mentioning

confidence: 99%

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Deforestation patterns and stages of the Southern Amazon agricultural frontier

Linhares

Monteiro

Bastos

2023

R. Agrogeoambiental

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From 1980 to 2020, the Paciá River Drainage Basin (BHRP – Bacia Hidrográfica do Rio Paciá), located in the Southern Amazon agricultural frontier, underwent an accelerated process of change in human land use and occupation. This study aimed to identify and analyze deforestation patterns, relating them to landscape metrics and the stages of expansion of the agricultural frontier. The methodology was based on the following phases: 1) organizational structure of GIS (Geographic Information System) modeling; 2) mapping and classification of deforestation patterns; 3) mapping of the expansion stages of the agricultural frontier. Diffuse and geometric patterns represented 72.5% of the polygons analyzed, corresponding to 15.64% of deforestation. However, linear and consolidated patterns, which referred to 12.5% of the polygons, represented 65.5% of the deforested areas in the BHRP. The spatial arrangements of deforestation polygons are associated with two evolutionary stages of the Amazon agricultural frontier: permanent/consolidated, which is located along the Transamazon highway, and pioneer/diffuse, located along the banks of rural roads and the main course of the Paciá River.

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“…The methodology of this study was based on Silva et al (2008b), Gavlak et al (2011), andSaito et. al.…”

Section: Methodological Proceduresmentioning

confidence: 99%

Section: Deforestation Patterns and Stages Of The Southern Amazon Agr...mentioning

confidence: 99%

Deforestation patterns and stages of the Southern Amazon agricultural frontier

Linhares

Monteiro

Bastos

2023

R. Agrogeoambiental

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“…Similar to ORV-created roads in National Forests in the US, the impact of "unofficial" (i.e., illegal) roads may be greater than official roads [68,69]. Brazil's National Institute for Space Research (INPE) hosts a website with Landsat images and software ("SPRING") which allows researchers to quickly identify areas of the Amazon where high rates of "unofficial" (i.e., illegal) roads are encroaching on pristine forest areas, so that these areas can be officially protected [70,71].…”

Section: Emerging Opportunities For Policy Applicationsmentioning

confidence: 99%

Use of Remote Sensing to Support Forest and Wetlands Policies in the USA

Mayer

Lopez

2011

Remote Sensing

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Abstract:The use of remote sensing for environmental policy development is now quite common and well-documented, as images from remote sensing platforms are often used to focus attention on emerging environmental issues and spur debate on potential policy solutions. However, its use in policy implementation and evaluation has not been examined in much detail. Here we examine the use of remote sensing to support the implementation and enforcement of policies regarding the conservation of forests and wetlands in the USA. Specifically, we focus on the "Roadless Rule" and "Travel Management Rules" as enforced by the US Department of Agriculture Forest Service on national forests, and the "No Net Loss" policy and Clean Water Act for wetlands on public and private lands, as enforced by the US Environmental Protection Agency and the US Army Corps of Engineers. We discuss several national and regional examples of how remote sensing for forest and wetland conservation has been effectively integrated with policy decisions, along with barriers to further integration. Some of these barriers are financial and technical (such as the lack of data at scales appropriate to policy enforcement), while others are political.

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“…Technologies such as remote sensing and Geographic Information Systems (GIS) facilitates observations on the surface of the earth, since satellite-derived information is a digital computer-based source of information, allowing the combination of physical, biological and socio-economic data to analyze landscapes and ecosystems, enabling to assess changes and impacts (Revenga 2005). Remote sensing images have been widely used as data sources to classify land cover, and to assess how different types of activities have affected natural landscapes over time (Silva et al 2008;Jiang et al 2018). Moreover, the classi cation of images has been used to analyze the accuracy of areas covered by water related to the installation of hydroelectric power plants (Cochrane et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Assessing Land Use and Land Cover Change in the Volta Grande Do Xingu (Pará – Brazil) Between 2000 and 2017

Affonso

Mandai

Portella

et al. 2021

Preprint

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This study aims to assess the land use and land cover change through the use of three pixel-based methods of image classification (Mahalanobis, Maximum Likelihood, and Minimum Distance) in the region of Volta Grande do Xingu (Brazilian Amazon), under influence of the Belo Monte hydroelectric power plant. Different pixel-based classification methods were performed on Landsat 7 and 8 multispectral products from the years 2000 and 2017, using a 2008 map as the ground truth image. The accuracies of the classifications were compared, and land use change analyses were performed in the different scenarios. The main impacts regarding land use and land cover change were from forest to agro pasture, from non-river to river upstream the Xingu river, and from river to non-river in the south of the Volta Grande do Xingu, resulting in rocks exposure.

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Remote‐sensing image mining: detecting agents of land‐use change in tropical forest areas

Cited by 43 publications

References 31 publications

Deforestation patterns and stages of the Southern Amazon agricultural frontier

Deforestation patterns and stages of the Southern Amazon agricultural frontier

Use of Remote Sensing to Support Forest and Wetlands Policies in the USA

Assessing Land Use and Land Cover Change in the Volta Grande Do Xingu (Pará – Brazil) Between 2000 and 2017

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