Volume 23, Issue 2 - December 2023
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Revista de Gestão Costeira Integrada
Volume 23, Issue 2, December 2023, Pages 153-175
DOI: 10.5894/rgci-n552
* Submission: 13 MAR 2023; Peer review: 17 MAR 2023; Revised: 28 AGO 2023; Accepted: 28 AGO 2023; Available on-line: 8 FEB 2024
Remote sensing approaches for land use/land cover change in coastal areas and oceanic islands: an open science-based systematic review
Rafaela Tiengo@ 1, 2, 3, Alicia Palácios-Orueta1, 4, Jéssica Uchôa2, 3 and Artur Gil3
@ Corresponding author: [email protected]
1 Departamento de Ingeniería Agroforestal. ETSIAAB —Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Spain.
2 cE3c – Centre for Ecology, Evolution and Environmental Changes, Azorean Biodiversity Group, CHANGE – Global Change and Sustainability Institute, Faculty of Sciences and Technology, University of the Azores, 9500-321 Ponta Delgada, Portugal.
3 Research Institute for Volcanology and Risks Assessment (IVAR), University of the Azores. 9500-321 Ponta Delgada, Portugal
4 Centro de Estudios e Investigación para la Gestión de Riesgos Agrarios y Medioambientales (CEIGRAM), Universidad Politécnica de Madrid, Paseo de la Senda del Rey, n° 13, 28040 Madrid, Spain
ABSTRACT
In the current climate change context, detecting and monitoring relevant land use/land cover (LULC) changes in insular and coastal areas is critical as soon as they occur. This research consists of a systematic literature review of 167 open-access articles from January 2010 to June 2022, based on several parameters, namely year of publication, journals, geographic location of the study area, time range of the studies, data source, data type, sensors, remote sensing-based approach, data processing algorithms, accuracy assessment approach, and spatial resolution, using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) declaration as a guideline. The results revealed that the years 2020 and 2021 showed the highest number of studies published, namely 33 for each year (20%). The continent with the most case studies was Asia (48%), with China being the most productive country in this field (23%). The most analyzed time range was superior to 20 years (37% of the studies). Satellite imagery was the most applied data source (77%), followed by relevant historical data (e.g., land cover maps). The multispectral data was used in 77% of the studies, and the Landsat Mission represents three of five of the most used sensors. Normalized Difference Vegetation Index was the most applied remote sensing-based approach (10%), and the Maximum Likelihood Classifier Algorithm was the most widely used data processing algorithm (10%). The Overall Accuracy is the most applied accuracy assessment approach used in 85 papers (51%). Many articles used a 30-meter spatial resolution (69%), and higher resolutions completed the top 5 approaches. This study contributes to perceiving the main current approaches for monitoring LULC changes in insular and coastal environments to identify research gaps for future developments.
Keywords: Land cover; land use; change detection; remote sensing; oceanic islands; coastal areas; climate change; natural hazards
RESUMO
No contexto atual das alterações climáticas, é fundamental detectar e monitorar alterações relevantes de uso/cobertura do solo em áreas insulares e costeiras logo que ocorram. A presente investigação consiste numa revisão sistemática da literatura de 167 artigos de acesso aberto publicados de Janeiro de 2010 a Junho de 2022, com base em diversos parâmetros, nomeadamente ano de publicação, revistas, localização geográfica da área de estudo, intervalo temporal analisado nos artigos, fonte de dados, tipo de dados, sensores, métodos baseados em sensoriamento remoto, algoritmos de processamento de dados, métodos de acurácia e resolução espacial, usando a declaração Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) como diretriz. Os resultados revelaram que os anos de 2020 e 2021 apresentaram o maior número de estudos publicados, ou seja, 33 para cada ano (20%). O continente com mais estudos de caso foi a Ásia (48%), sendo a China o país mais produtivo neste domínio (23%). O intervalo temporal mais analisado foi superior a 20 anos (37% dos estudos). Imagens de satélite foram a fonte de dados mais aplicada (77%), seguidas por dados históricos relevantes (por exemplo, mapas de cobertura da terra). Os dados multiespectrais foram utilizados em 77% dos estudos, sendo que a Missão Landsat representa três dos cinco sensores mais utilizados. O Índice de Vegetação por Diferença Normalizada foi o método baseado em sensoriamento remoto mais aplicado (10%) e o Algoritmo Classificador de Máxima Verossimilhança foi o algoritmo de processamento de dados mais amplamente utilizado (10%). O Overall Accuracy é o método de acurácia mais aplicado, usado em 85 artigos (51%). Muitos trabalhos usaram uma resolução espacial de 30 metros (69%) e resoluções espaciais maiores completaram as cinco mais utilizadas. Este estudo contribui para perceber as principais abordagens atuais para monitorar alterações no uso/cobertura do solo em ambientes insulares e costeiros para identificar lacunas de pesquisa para desenvolvimentos futuros.
Palavras-chave: Cobertura do solo; uso do solo; detecção de mudança; sensoriamento remoto; ilhas oceânicas; áreas costeiras; alterações climáticas; riscos naturais
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