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Geospatial mapping of carbon estimates for forested areas using the InVEST model and Sentinel-2: A case study in Galicia (NW Spain).
García-Ontiyuelo, Mario; Acuña-Alonso, Carolina; Valero, Enrique; Álvarez, Xana.
Afiliação
  • García-Ontiyuelo M; University of Vigo, Agroforestry Group, School of Forestry Engineering, 36005, Pontevedra, Spain. Electronic address: mario.garcia.ontiyuelo@uvigo.es.
  • Acuña-Alonso C; University of Vigo, Agroforestry Group, School of Forestry Engineering, 36005, Pontevedra, Spain; Centre for the Research and Technology of Agro-Environmental and Biological Sciences - CITAB, University of Trás-os-Montes and Alto Douro (UTAD), Ap. 1013, 5001-801 Vila Real, Portugal. Electronic addre
  • Valero E; University of Vigo, Agroforestry Group, School of Forestry Engineering, 36005, Pontevedra, Spain. Electronic address: evalero@uvigo.es.
  • Álvarez X; University of Vigo, Agroforestry Group, School of Forestry Engineering, 36005, Pontevedra, Spain. Electronic address: xaalvarez@uvigo.es.
Sci Total Environ ; 922: 171297, 2024 Apr 20.
Article em En | MEDLINE | ID: mdl-38423322
ABSTRACT
CO2 emissions have increased exponentially in recent years, so measuring and quantifying carbon sequestration is a step towards sustainable forest management and combating climate change. The overall goal of this study is to develop an accurate model for estimating carbon storage and sequestration for forest areas of the Atlantic Biogeographic Region. Specifically, the modelling and field sampling are carried out in the municipality of Baiona (Galicia, NW Spain), which was selected as a representative biome of this region. The methodology consists of carrying out two object-based image analysis (OBIA) classifications in spring and autumn to observe possible stocks of seasonal differences. Two carbon storage and sequestration models are built up (model 1 and model 2) model 1 for forest areas only and model 2 including all other land cover in the study area. Sentinel-2 geospatial data for 2021, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) tools and geographic information systems (GIS) are used. A Kappa index of 0.92 is obtained for both classifications, thus ruling out any notable seasonal differences in the images used. The results from both models indicate that it is land covers associated with forest uses which store the most carbon in the study area, accounting for >50 % more than the other land covers. It is concluded that the methodology and data used are very useful for quantifying ecosystem services, which will help the governance of the region by implementing measures to mitigate some of the effects of climate change and help to create silvicultural models for the sustainable management of the Atlantic Biogeographic Region.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Total Environ Ano de publicação: 2024 Tipo de documento: Article País de publicação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Total Environ Ano de publicação: 2024 Tipo de documento: Article País de publicação: Holanda