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Extração de informações de deposição de poeira na superfície das folhas em área de mineração baseada em dados Sentinel-2 e identificação de fontes de poeira

  • role： First author第一作者
  • Affiliation：

    Institute of Geologic Survey, China University of Geosciences (Wuhan), Wuhan 430074, China

    Hubei Institute of Land Surveying and Mapping, Wuhan 430010, China

  • Email：21844ss@cug.edu.cn
  • Introduction：帅爽，研究方向为遥感地质、地学遥感应用。E-mail： 21844ss@cug.edu.cn
SHUAI Shuang13,  
  • role： Corresponding author通信作者
  • Affiliation：

    Institute of Geophysics & Geomatics, China University of Geoscience (Wuhan), Wuhan 430074, China

  • Email：3slab@cug.edu.cn
  • Introduction：张志，研究方向为遥感地质、地学遥感应用。E-mail： 3slab@cug.edu.cn
ZHANG Zhi2*,  
  • Affiliation：

    Institute of Geologic Survey, China University of Geosciences (Wuhan), Wuhan 430074, China

LYU Xinbiao1,  
  • Affiliation：

    Hubei Institute of Land Surveying and Mapping, Wuhan 430010, China

CHEN Si3,  
  • Affiliation：

    Hubei Institute of Land Surveying and Mapping, Wuhan 430010, China

MA Zicheng3,  
  • Affiliation：

    Hubei Institute of Land Surveying and Mapping, Wuhan 430010, China

XIE Cuirong3

Resumo

O monitoramento remoto da deposição de poeira na superfície das folhas é um dos meios importantes para avaliar a situação da poluição por poeira em áreas de mineração. Em comparação com a poeira natural, a poeira de mineração enriquecida com metais pesados representa uma ameaça mais grave à saúde humana e ao crescimento da vegetação. Anteriormente, o monitoramento remoto da deposição de poeira na superfície das folhas concentrou-se principalmente na inversão e monitoramento da quantidade de deposição, sem estudar as diferenças entre a poeira de mineração e a poeira natural. Este artigo utiliza dados do Sentinel-2, tomando como exemplo a área da mina de chumbo, zinco e prata Jia’uwula-Chagan, na Região Autônoma da Mongólia Interior. Com base na análise das características de resposta espectral da deposição de poeira nas folhas, e utilizando o método FPCS (Feature-oriented Principal Components Selection) baseado na seleção de componentes principais orientada a características, foram extraídos o alcance e a intensidade da deposição de poeira nas folhas na área de estudo. Após analisar as diferenças nas características espectrais entre as fontes de poeira de mineração e natural, foi estabelecido o Índice do Espectro da Fonte de Poeira (DSI) para distinguir a poeira de mineração da poeira natural. Também foi analisada a correlação entre o tipo e intensidade da deposição de poeira nas folhas e a distribuição dos elementos da mina, bem como as características de dispersão da poeira das principais fontes de mineração. Os resultados mostram que a deposição de poeira nas folhas aumenta a refletância na faixa do visível, reduz na faixa do infravermelho próximo e provoca um deslocamento “azul” da borda vermelha da vegetação. Afasta-se da fonte de poeira, a refletância na faixa visível diminui gradativamente, e a posição da borda vermelha desloca-se para comprimentos de onda mais longos. Existem diferenças espectrais entre as fontes de poeira de mineração e natural, os pixels de deposição de poeira da mina mostram características de absorção de refletância próximas a 864,7 nm. O método FPCS extraiu com sucesso o alcance e intensidade da deposição de poeira, o índice DSI diferencia eficazmente a deposição de poeira de mineração e natural, e os pixels extraídos apresentam forte correlação espacial com os elementos da mina. As principais fontes de poeira na área de estudo são os montes de rejeitos e as estradas da mina, com intensidade e alcance de dispersão de poeira maior nos montes do que nas estradas. Este estudo pode fornecer um método técnico para avaliação rápida da poluição por poeira no desenvolvimento da mineração.

Palavras-chave

sensoriamento remoto; área de mineração; deposição de poeira na superfície das folhas; informações de fontes de poeira; Sentinel-2; FPCS; índice do espectro da fonte de poeira (DSI)

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