Strategies for detecting land-use change on the River Tea SCI ecological corridor via satellite images DOI Creative Commons
Mario García-Ontiyuelo, Carolina Acuña-Alonso, Christos Vasilakos

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 957, P. 177507 - 177507

Published: Nov. 19, 2024

Land-cover change is often accompanied by land-use change, altering ecosystem services, species habitats and contributing to climate change. The general goal of this study analyse different sources information quantify land use cover (LULCC) in the River Tea SCI (Galicia, NW Spain) 2015-2023. area has multiple coverages with very low variability between them a great deal fragmentation territory, which makes it difficult obtain high accuracy levels. Land was classified using object-based image analysis (OBIA) Classification Artificial Neural Network (ANN) methodologies based on images from Sentinel-2 Planet Labs (RapidEye PlanetScope) multispectral satellite platforms. In addition, simulations for 2031 were carried out techniques post-classification. highest obtained 80 %, data OBIA methodology. Using same methodology best around 70 ANN developed 55 %. Thus, used followed influence levels classifications. choice what are be depends goals pursued characteristics area. Finally, concluded that geospatial available useful detecting quantifying changes cover. It confirmed contributes territorial planning sustainable forest management, facilitating future decisions action plans governance region.

Language: Английский

Identifying groundwater anthropogenic disturbances and their predominant impact on microbial nitrogen cycling at a former contamination site adjacent to Baiyangdian Lake DOI

Sining Zhong,

Bin Li, Qian Chen

et al.

Water Research, Journal Year: 2025, Volume and Issue: unknown, P. 123544 - 123544

Published: March 1, 2025

Language: Английский

Citations

0
Divergent drivers of temporal stability for gravel and sandy desert ecosystems around mobile deserts: Implications for ecosystem conservation and desertification management DOI
Lemin Wei,

Lingfei Zhong,

Yajun Yue

et al.

CATENA, Journal Year: 2025, Volume and Issue: 256, P. 109088 - 109088

Published: May 1, 2025

Language: Английский

Citations

0
Strategies for detecting land-use change on the River Tea SCI ecological corridor via satellite images DOI Creative Commons
Mario García-Ontiyuelo, Carolina Acuña-Alonso, Christos Vasilakos

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 957, P. 177507 - 177507

Published: Nov. 19, 2024

Land-cover change is often accompanied by land-use change, altering ecosystem services, species habitats and contributing to climate change. The general goal of this study analyse different sources information quantify land use cover (LULCC) in the River Tea SCI (Galicia, NW Spain) 2015-2023. area has multiple coverages with very low variability between them a great deal fragmentation territory, which makes it difficult obtain high accuracy levels. Land was classified using object-based image analysis (OBIA) Classification Artificial Neural Network (ANN) methodologies based on images from Sentinel-2 Planet Labs (RapidEye PlanetScope) multispectral satellite platforms. In addition, simulations for 2031 were carried out techniques post-classification. highest obtained 80 %, data OBIA methodology. Using same methodology best around 70 ANN developed 55 %. Thus, used followed influence levels classifications. choice what are be depends goals pursued characteristics area. Finally, concluded that geospatial available useful detecting quantifying changes cover. It confirmed contributes territorial planning sustainable forest management, facilitating future decisions action plans governance region.

Language: Английский

Citations

0