Sensoriamento remoto na análise de variáveis ambientais influenciadas pela implantação da usina hidrelétrica de Belo Monte (PA)

Neto, Albertino Monteiro; Batista, Lucas Mota; Sousa, Maria Zélia Aguiar de; Freitas, Kemuel Maciel; Araújo, Suzana Romeiro

doi:10.5752/p.2318-2962.2021v31n66p823

Cited by 1 publication

(4 citation statements)

References 14 publications

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“…Due to the importance of a comprehensive comparison of different algorithms for LULC classification, aiming to improve knowledge on issues such as accuracy assessment and the selection of suitable algorithms for a historical remote sensing analysis for the VGX, the discussion section intends to sum with other previous initiatives that sought to measure and evaluate manmade transformations in study areas using remote sensing [3,12,15,28,30,31,42,46,66,67].…”

Section: Discussionmentioning

confidence: 99%

“…It has drained approximately 130 km of the river channel between Pimental and the outlet of the BMHC dam (downstream-the focus of this study). From there, the water is returned to the Xingu's main channel [29][30][31].…”

Section: Study Areamentioning

confidence: 99%

“…This new hydrological regime imposed by the dam operators has been implemented since the end of 2019, with some occasional interruptions due to judicial interferences caused by the proven unsustainable conditions to keep healthy riverine ecosystems [38,39]. Indeed, some studies already indicated that the artificial regulation of the Xingu water flow level is failing to simulate the natural flood pulse and specialized vegetation and aquatic organisms are not able to survive the new conditions [27,30,31,37].…”

Section: Study Areamentioning

confidence: 99%

“…The literature's recommendation states that the creation of mitigation measures, such as the intensification of environmental monitoring and the creation of protected areas, with the aim to avoid or reduce deforestation, are the most effective strategies to attenuate the harmful impacts of such great enterprises [31,75].…”

Section: Land Use and Land Cover Changesmentioning

confidence: 99%

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A Comparison between Supervised Classification Methods: Study Case on Land Cover Change Detection Caused by a Hydroelectric Complex Installation in the Brazilian Amazon

et al. 2023

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The Volta Grande do Xingu (VGX) in the Amazon Forest of Brazil was chosen to analyze the land use and land cover changes (LULCC) from 2000 to 2017, with the aim of assessing the most suitable classification method for the area. Three parametric (Mahalanobis distance, maximum likelihood and minimum distance) and three non-parametric (neural net, random forest and support vector machine) classification algorithms were tested in two Landsat scenes. The accuracy assessment was evaluated through a confusion matrix. Change detection of the landscape was analyzed through the post-classification comparison method. While maximum likelihood was more capable of highlighting errors in individual classes, support vector machine was slightly superior when compared with the other non-parametric options, these being the most suitable classifiers within the scope of this study. The main changes detected in the landscape were from forest to agro-pasture, from forest/agro-pasture to river, and from river to non-river, resulting in rock exposure. The methodology outlined in this research highlights the usefulness of remote sensing tools in follow-up observations of LULCC in the study area (with the possibility of application to the entire Amazon rainforest). Thus, it is possible to carry out adaptive management that aims to minimize unforeseen or underestimated impacts in previous stages of environmental licensing.

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