Mangrove spectra changes induced by oil spills monitored by image differencing of normalised indices: Tools to assist delimitation of impacted areas

Pavanelli, David Domingues; Loch, Carlos

doi:10.1016/j.rsase.2018.10.001

Cited by 6 publications

(2 citation statements)

References 43 publications

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“…E por consequência, devido a capacidade de biomagnificação deste poluente, pode ocorrer transferência de energia por acumulação nos níveis mais altos da cadeia trófica (Kumar, et al, 2021). Derramamentos de petróleo e seus derivados em manguezais podem provocar efeitos agudos, que se manifestam em curto prazo, e crônicos, que irão provocar impactos observáveis após períodos de tempo mais longos (Parvanelli & Loch, 2018;Duke, 2019). Antes de estabelecer os principais efeitos que o derramamento de óleo pode causar em manguezais, deve-se ter em mente que as respostas do ecossistema a este impacto irão depender de fatores químicos, físicos, oceanográficos e microbiológicos, tais como: a quantidade de óleo derramado, sua composição, a hidrodinâmica do local, disponibilidade de nutrientes, a irradiação solar, a temperatura, granulometria do sedimento, a composição da comunidade microbiana no meio, dentre outros fatores (Garcia & La Rovere, 2011;Silva, 2019).…”

Section: Interações Do Petróleo No Sedimento De Manguezalunclassified

Processos enzimáticos na biorremediação e fitorremediação de petróleo em sedimentos de manguezal: uma revisão

Lacerda

Santana

Filho

et al. 2021

RSD

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Diversos vazamentos de petróleo em mares e oceanos ocorreram nas últimas décadas, afetando principalmente estuários e manguezais. Acidentes ambientais envolvendo o petróleo, seus derivados e os resíduos gerados têm sido uma preocupação crescente, por conta dos hidrocarbonetos do petróleo ser considerados contaminantes orgânicos tóxicos e de difícil degradação. Os avanços biotecnológicos têm levado os pesquisadores a adotar a biorremediação e fitorremediação como alternativas potencialmente eficazes para solos e sedimentos contaminados e o uso enzimas têm sido adotado como uma estratégia além do uso de plantas e microrganismos na biorremediação. Este estudo consiste em uma revisão bibliográfica baseada em livros, artigos, teses, dissertações e sites, com o intuito de reunir e avaliar os processos enzimáticos na fitorremediação e fitorremediação em ambientes impactados por atividades do petróleo.

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Section: Interações Do Petróleo No Sedimento De Manguezalunclassified

Processos enzimáticos na biorremediação e fitorremediação de petróleo em sedimentos de manguezal: uma revisão

Lacerda

Santana

Filho

et al. 2021

RSD

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“…In the Panamanian coast, oil spill destroyed over 27km of mangrove vegetation and newly planted seedlings [19]. Pavanelli and Loch [20] observed deterioration in vegetation health during the first 40 days after oil spills in two different sites in Brazil. The study concluded that the impact of the oil spill on vegetation depends on the level of exposure and the chemistry of the oil.…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Analysis of Oil Spill Impact and Recovery Pattern of Coastal Vegetation and Wetland Using Multispectral Satellite Landsat 8-OLI Imagery and Machine Learning Models

et al. 2020

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Oil spills are a global phenomenon with impacts that cut across socio-economic, health, and environmental dimensions of the coastal ecosystem. However, comprehensive assessment of oil spill impacts and selection of appropriate remediation approaches have been restricted due to reliance on laboratory experiments which offer limited area coverage and classification accuracy. Thus, this study utilizes multispectral Landsat 8-OLI remote sensing imagery and machine learning models to assess the impacts of oil spills on coastal vegetation and wetland and monitor the recovery pattern of polluted vegetation and wetland in a coastal city. The spatial extent of polluted areas was also precisely quantified for effective management of the coastal ecosystem. Using Johor, a coastal city in Malaysia as a case study, a total of 49 oil spill (ground truth) locations, 54 non-oil-spill locations and Landsat 8-OLI data were utilized for the study. The ground truth points were divided into 70% training and 30% validation parts for the classification of polluted vegetation and wetland. Sixteen different indices that have been used to monitor vegetation and wetland stress in literature were adopted for impact and recovery analysis. To eliminate similarities in spectral appearance of oil-spill-affected vegetation, wetland and other elements like burnt and dead vegetation, Support Vector Machine (SVM) and Random Forest (RF) machine learning models were used for the classification of polluted and nonpolluted vegetation and wetlands. Model optimization was performed using a random search method to improve the models’ performance, and accuracy assessments confirmed the effectiveness of the two machine learning models to identify, classify and quantify the area extent of oil pollution on coastal vegetation and wetland. Considering the harmonic mean (F1), overall accuracy (OA), User’s accuracy (UA), and producers’ accuracy (PA), both models have high accuracies. However, the RF outperformed the SVM with F1, OA, PA and UA values of 95.32%, 96.80%, 98.82% and 95.11%, respectively, while the SVM recorded accuracy values of F1 (80.83%), OA (92.87%), PA (95.18%) and UA (93.81%), respectively, highlighting 1205.98 hectares of polluted vegetation and 1205.98 hectares of polluted wetland. Analysis of the vegetation indices revealed that spilled oil had a significant impact on the vegetation and wetland, although steady recovery was observed between 2015-2018. This study concludes that Chlorophyll Vegetation Index, Modified Difference Water Index, Normalized Difference Vegetation Index and Green Chlorophyll Index vegetation indices are more sensitive for impact and recovery assessment of both vegetation and wetland, in addition to Modified Normalized Difference Vegetation Index for wetlands. Thus, remote sensing and Machine Learning models are essential tools capable of providing accurate information for coastal oil spill impact assessment and recovery analysis for appropriate remediation initiatives.

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Impact of petroleum hydrocarbon and heavy metal pollution on coral reefs and mangroves: a review

Elumalai,

Parthipan,

Gao

et al. 2024

Environ Chem Lett

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Mangrove spectra changes induced by oil spills monitored by image differencing of normalised indices: Tools to assist delimitation of impacted areas

Cited by 6 publications

References 43 publications

Processos enzimáticos na biorremediação e fitorremediação de petróleo em sedimentos de manguezal: uma revisão

Processos enzimáticos na biorremediação e fitorremediação de petróleo em sedimentos de manguezal: uma revisão

Spatio-Temporal Analysis of Oil Spill Impact and Recovery Pattern of Coastal Vegetation and Wetland Using Multispectral Satellite Landsat 8-OLI Imagery and Machine Learning Models

Impact of petroleum hydrocarbon and heavy metal pollution on coral reefs and mangroves: a review

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