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Automatic detection of vegetation cover changes in urban-rural interface areas
The present work started from the need to streamline the process of monitoring changes in vegetation in the in urban-rural interface fuel management bands, defined by Portuguese legislation as areas where the existing biomass must be totally or partially removed. The model developed uses a time seri...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8913335/ https://www.ncbi.nlm.nih.gov/pubmed/35284248 http://dx.doi.org/10.1016/j.mex.2022.101643 |
Sumario: | The present work started from the need to streamline the process of monitoring changes in vegetation in the in urban-rural interface fuel management bands, defined by Portuguese legislation as areas where the existing biomass must be totally or partially removed. The model developed uses a time series of Sentinel 2 satellite images to search for changes in the vegetation cover in a 100 m buffer around built-up areas. The use of satellite data allows analysing large areas and speeds up the task of identifying the places where fuel management took place and the places where there is a need to carry out such management. The objective of the proposed method is to give a script in Python language that can verify the cleanliness of vegetation in the fuel management ranges through multi-temporal analysis of satellite images. • The paper presents a step-by-step procedure for a Sentinel 2 time series vegetation index analysis. • Automated routine to detection of spatiotemporal vegetation changes based on statistical parameters. • Used Python language to do geoprocessing analysis. |
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