Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut Control
Land fragmentation and small plots are the main features of the rural environment of Galicia (NW Spain). Smallholding limits land use management, representing a drawback in local forest planning. This study analyzes the potential use of multitemporal Sentinel-2 images to detect and control forest cu...
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Online Access: | https://www.mdpi.com/2072-4292/13/15/2983 |
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doaj-591c965267e848ca8ed8393c27cbd7a42021-08-06T15:30:43ZengMDPI AGRemote Sensing2072-42922021-07-01132983298310.3390/rs13152983Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut ControlAlberto López-Amoedo0Xana Álvarez1Henrique Lorenzo2Juan Luis Rodríguez3Asefor Ingeniería Forestal, S.L.E. Centro de Emprendemento Monte Gaiás, Cidade da Cultura, 15707 Santiago de Compostela, SpainSchool of Forestry Engineering, University of Vigo, Campus A Xunqueira s/n, 36005 Pontevedra, SpainCINTECX, GeoTECH Research Group, Universidade de Vigo, 36310 Vigo, SpainCINTECX, GeoTECH Research Group, Universidade de Vigo, 36310 Vigo, SpainLand fragmentation and small plots are the main features of the rural environment of Galicia (NW Spain). Smallholding limits land use management, representing a drawback in local forest planning. This study analyzes the potential use of multitemporal Sentinel-2 images to detect and control forest cuts in very small pine and eucalyptus plots located in southern Galicia. The proposed approach is based on the analysis of Sentinel-2 NDVI time series in 4231 plots smaller than 3 ha (average 0.46 ha). The methodology allowed us to detect cuts, allocate cut dates and quantify plot areas due to different cutting cycles in an uneven-aged stand. An accuracy of approximately 95% was achieved when the whole plot was cut, with an 81% accuracy for partial cuts. The main difficulty in detecting and dating cuts was related to cloud cover, which affected the multitemporal analysis. In conclusion, the proposed methodology provides an accurate estimation of cutting date and area, helping to improve the monitoring system in sustainable forest certifications to ensure compliance with forest management plans.https://www.mdpi.com/2072-4292/13/15/2983remote sensingforest cover<i>Eucalyptus globulus</i><i>Pinus pinaster</i>time series |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alberto López-Amoedo Xana Álvarez Henrique Lorenzo Juan Luis Rodríguez |
spellingShingle |
Alberto López-Amoedo Xana Álvarez Henrique Lorenzo Juan Luis Rodríguez Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut Control Remote Sensing remote sensing forest cover <i>Eucalyptus globulus</i> <i>Pinus pinaster</i> time series |
author_facet |
Alberto López-Amoedo Xana Álvarez Henrique Lorenzo Juan Luis Rodríguez |
author_sort |
Alberto López-Amoedo |
title |
Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut Control |
title_short |
Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut Control |
title_full |
Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut Control |
title_fullStr |
Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut Control |
title_full_unstemmed |
Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut Control |
title_sort |
multi-temporal sentinel-2 data analysis for smallholding forest cut control |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2021-07-01 |
description |
Land fragmentation and small plots are the main features of the rural environment of Galicia (NW Spain). Smallholding limits land use management, representing a drawback in local forest planning. This study analyzes the potential use of multitemporal Sentinel-2 images to detect and control forest cuts in very small pine and eucalyptus plots located in southern Galicia. The proposed approach is based on the analysis of Sentinel-2 NDVI time series in 4231 plots smaller than 3 ha (average 0.46 ha). The methodology allowed us to detect cuts, allocate cut dates and quantify plot areas due to different cutting cycles in an uneven-aged stand. An accuracy of approximately 95% was achieved when the whole plot was cut, with an 81% accuracy for partial cuts. The main difficulty in detecting and dating cuts was related to cloud cover, which affected the multitemporal analysis. In conclusion, the proposed methodology provides an accurate estimation of cutting date and area, helping to improve the monitoring system in sustainable forest certifications to ensure compliance with forest management plans. |
topic |
remote sensing forest cover <i>Eucalyptus globulus</i> <i>Pinus pinaster</i> time series |
url |
https://www.mdpi.com/2072-4292/13/15/2983 |
work_keys_str_mv |
AT albertolopezamoedo multitemporalsentinel2dataanalysisforsmallholdingforestcutcontrol AT xanaalvarez multitemporalsentinel2dataanalysisforsmallholdingforestcutcontrol AT henriquelorenzo multitemporalsentinel2dataanalysisforsmallholdingforestcutcontrol AT juanluisrodriguez multitemporalsentinel2dataanalysisforsmallholdingforestcutcontrol |
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