Automatic forest change detection through a bi-annual time series of satellite imagery: Toward production of an integrated land cover map
Land cover mapping is fundamental for national and international agencies to monitor forest resources. However, monitoring forest disturbances by direct comparison of these maps poses several difficulties and challenges. As a result, different methodologies have been explored to detect forest distur...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-04-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223001115 |
| _version_ | 1797842812442509312 |
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| author | Alonso L. Picos J. Armesto J. |
| author_facet | Alonso L. Picos J. Armesto J. |
| author_sort | Alonso L. |
| collection | DOAJ |
| description | Land cover mapping is fundamental for national and international agencies to monitor forest resources. However, monitoring forest disturbances by direct comparison of these maps poses several difficulties and challenges. As a result, different methodologies have been explored to detect forest disturbances. However, most of them cannot be fully integrated with land cover map production since they require additional input data, while others are not suitable for monitoring small land parcels. This study presents a methodology that fulfils the need to integrate land cover mapping with land cover change detection. Specifically, this methodology was designed to complement the Sentinel-2-based land cover mapping used in Galicia, northwest Spain, a region characterized by small land parceling. First, two previously obtained land cover maps from 2019 and 2020 were compared to identify all the pixels with potential land cover changes using QGIS. The behavior of spectral indexes in a time series were then analyzed to identify which of the previously identified pixels correspond to forest disturbances. This step was implemented in the software R. Using the Normalized Difference Vegetation Index (NDVI) to detect different land cover changes it was obtained an overall accuracy of 82%, considering the existence of varying phenologies, diverse topographic conditions, and areas with a high level of stand fragmentation. This study could help agencies that have already developed their own land cover maps to easily advance the integration of their maps with land cover change detection, since this technique can be applied with any land cover mapping methodology based on multitemporal analysis of satellite images, without the need for additional input data. |
| first_indexed | 2024-04-09T16:55:28Z |
| format | Article |
| id | doaj.art-fb4febefecc34346b226adb57e3b228d |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-09T16:55:28Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-fb4febefecc34346b226adb57e3b228d2023-04-21T06:43:09ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-04-01118103289Automatic forest change detection through a bi-annual time series of satellite imagery: Toward production of an integrated land cover mapAlonso L.0Picos J.1Armesto J.2Forestry Engineering School, University of Vigo, A Xunqueira Campus, 36005 Pontevedra, Spain; CINTECX, GESSMin Group (Safe and Sustainable Management of Mineral Resources), 36310 Vigo, Spain; Corresponding author.Forestry Engineering School, University of Vigo, A Xunqueira Campus, 36005 Pontevedra, SpainForestry Engineering School, University of Vigo, A Xunqueira Campus, 36005 Pontevedra, Spain; CINTECX, GESSMin Group (Safe and Sustainable Management of Mineral Resources), 36310 Vigo, SpainLand cover mapping is fundamental for national and international agencies to monitor forest resources. However, monitoring forest disturbances by direct comparison of these maps poses several difficulties and challenges. As a result, different methodologies have been explored to detect forest disturbances. However, most of them cannot be fully integrated with land cover map production since they require additional input data, while others are not suitable for monitoring small land parcels. This study presents a methodology that fulfils the need to integrate land cover mapping with land cover change detection. Specifically, this methodology was designed to complement the Sentinel-2-based land cover mapping used in Galicia, northwest Spain, a region characterized by small land parceling. First, two previously obtained land cover maps from 2019 and 2020 were compared to identify all the pixels with potential land cover changes using QGIS. The behavior of spectral indexes in a time series were then analyzed to identify which of the previously identified pixels correspond to forest disturbances. This step was implemented in the software R. Using the Normalized Difference Vegetation Index (NDVI) to detect different land cover changes it was obtained an overall accuracy of 82%, considering the existence of varying phenologies, diverse topographic conditions, and areas with a high level of stand fragmentation. This study could help agencies that have already developed their own land cover maps to easily advance the integration of their maps with land cover change detection, since this technique can be applied with any land cover mapping methodology based on multitemporal analysis of satellite images, without the need for additional input data.http://www.sciencedirect.com/science/article/pii/S1569843223001115ForestDisturbancesLand cover changeSentinel-2Small parcels |
| spellingShingle | Alonso L. Picos J. Armesto J. Automatic forest change detection through a bi-annual time series of satellite imagery: Toward production of an integrated land cover map International Journal of Applied Earth Observations and Geoinformation Forest Disturbances Land cover change Sentinel-2 Small parcels |
| title | Automatic forest change detection through a bi-annual time series of satellite imagery: Toward production of an integrated land cover map |
| title_full | Automatic forest change detection through a bi-annual time series of satellite imagery: Toward production of an integrated land cover map |
| title_fullStr | Automatic forest change detection through a bi-annual time series of satellite imagery: Toward production of an integrated land cover map |
| title_full_unstemmed | Automatic forest change detection through a bi-annual time series of satellite imagery: Toward production of an integrated land cover map |
| title_short | Automatic forest change detection through a bi-annual time series of satellite imagery: Toward production of an integrated land cover map |
| title_sort | automatic forest change detection through a bi annual time series of satellite imagery toward production of an integrated land cover map |
| topic | Forest Disturbances Land cover change Sentinel-2 Small parcels |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223001115 |
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