Application of Multispectral Remote Sensing for Mapping Flood-Affected Zones in the Brumadinho Mining District (Minas Gerais, Brasil)
The collapse of the tailing “Dam B1” of the Córrego do Feijão Mine (Brumadinho, Brasil) that occurred in January 2019 is considered a large socio-environmental flood-disaster where numerous people died and the local flora and fauna were seriously affected, including agricultural areas of the Paraope...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/6/1501 |
| _version_ | 1797442636209979392 |
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| author | Lorenzo Ammirati Rita Chirico Diego Di Martire Nicola Mondillo |
| author_facet | Lorenzo Ammirati Rita Chirico Diego Di Martire Nicola Mondillo |
| author_sort | Lorenzo Ammirati |
| collection | DOAJ |
| description | The collapse of the tailing “Dam B1” of the Córrego do Feijão Mine (Brumadinho, Brasil) that occurred in January 2019 is considered a large socio-environmental flood-disaster where numerous people died and the local flora and fauna were seriously affected, including agricultural areas of the Paraopeba River. This study aims to map the land area affected by the flood by using multispectral satellite images. To pursue this aim, Level-2A multispectral images from the European Space Agency’s Sentinel-2 sensor were acquired before and after the tailing dam collapse in the period 2019–2021. The pre- and post-failure event analysis allowed us to evidence drastic changes in the vegetation rate, as well as in the nature of soils and surficial waters. The spectral signatures of the minerals composing the mining products allowed us to highlight the effective area covered by the flood and to investigate the evolution of land properties after the disaster. This technique opens the possibility for quickly classifying areas involved in floods, as well as obtaining significant information potentially useful for monitoring and planning the reclamation and restoration activities in similar cases worldwide, representing an additional tool for evaluating the environmental issues related to mining operations in large areas at high temporal resolution. |
| first_indexed | 2024-03-09T12:44:49Z |
| format | Article |
| id | doaj.art-5b3697e01e274cf3ad185917dbb43787 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T12:44:49Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-5b3697e01e274cf3ad185917dbb437872023-11-30T22:14:02ZengMDPI AGRemote Sensing2072-42922022-03-01146150110.3390/rs14061501Application of Multispectral Remote Sensing for Mapping Flood-Affected Zones in the Brumadinho Mining District (Minas Gerais, Brasil)Lorenzo Ammirati0Rita Chirico1Diego Di Martire2Nicola Mondillo3Department of Earth Sciences, Environment, and Resources, University of Naples, Federico II, Via Vicinale Cupa Cintia 21, 80126 Naples, ItalyDepartment of Earth Sciences, Environment, and Resources, University of Naples, Federico II, Via Vicinale Cupa Cintia 21, 80126 Naples, ItalyDepartment of Earth Sciences, Environment, and Resources, University of Naples, Federico II, Via Vicinale Cupa Cintia 21, 80126 Naples, ItalyDepartment of Earth Sciences, Environment, and Resources, University of Naples, Federico II, Via Vicinale Cupa Cintia 21, 80126 Naples, ItalyThe collapse of the tailing “Dam B1” of the Córrego do Feijão Mine (Brumadinho, Brasil) that occurred in January 2019 is considered a large socio-environmental flood-disaster where numerous people died and the local flora and fauna were seriously affected, including agricultural areas of the Paraopeba River. This study aims to map the land area affected by the flood by using multispectral satellite images. To pursue this aim, Level-2A multispectral images from the European Space Agency’s Sentinel-2 sensor were acquired before and after the tailing dam collapse in the period 2019–2021. The pre- and post-failure event analysis allowed us to evidence drastic changes in the vegetation rate, as well as in the nature of soils and surficial waters. The spectral signatures of the minerals composing the mining products allowed us to highlight the effective area covered by the flood and to investigate the evolution of land properties after the disaster. This technique opens the possibility for quickly classifying areas involved in floods, as well as obtaining significant information potentially useful for monitoring and planning the reclamation and restoration activities in similar cases worldwide, representing an additional tool for evaluating the environmental issues related to mining operations in large areas at high temporal resolution.https://www.mdpi.com/2072-4292/14/6/1501multispectraltailing damsminingrisk managementSentinel-2remote sensing |
| spellingShingle | Lorenzo Ammirati Rita Chirico Diego Di Martire Nicola Mondillo Application of Multispectral Remote Sensing for Mapping Flood-Affected Zones in the Brumadinho Mining District (Minas Gerais, Brasil) Remote Sensing multispectral tailing dams mining risk management Sentinel-2 remote sensing |
| title | Application of Multispectral Remote Sensing for Mapping Flood-Affected Zones in the Brumadinho Mining District (Minas Gerais, Brasil) |
| title_full | Application of Multispectral Remote Sensing for Mapping Flood-Affected Zones in the Brumadinho Mining District (Minas Gerais, Brasil) |
| title_fullStr | Application of Multispectral Remote Sensing for Mapping Flood-Affected Zones in the Brumadinho Mining District (Minas Gerais, Brasil) |
| title_full_unstemmed | Application of Multispectral Remote Sensing for Mapping Flood-Affected Zones in the Brumadinho Mining District (Minas Gerais, Brasil) |
| title_short | Application of Multispectral Remote Sensing for Mapping Flood-Affected Zones in the Brumadinho Mining District (Minas Gerais, Brasil) |
| title_sort | application of multispectral remote sensing for mapping flood affected zones in the brumadinho mining district minas gerais brasil |
| topic | multispectral tailing dams mining risk management Sentinel-2 remote sensing |
| url | https://www.mdpi.com/2072-4292/14/6/1501 |
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