Continuous Tracking of Forest Disturbance and Recovery in the Greater Khingan Mountains from Annual Landsat Imagery

Understanding accurate and continuous forest dynamics is of key importance for forest protection and management in the Greater Khingan Mountains (GKM). There has been a lack of finely captured and long-term information on forest disturbance and recovery since the mega-fire of 1987 which may limit th...
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Autor*in:	Huixin Ren [verfasserIn] Chunying Ren [verfasserIn] Zongming Wang [verfasserIn] Mingming Jia [verfasserIn] Wensen Yu [verfasserIn] Pan Liu [verfasserIn] Chenzhen Xia [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	forest disturbance forest recovery LandTrendr random forests (RF) TimeSync-Plus Greater Khingan Mountains (GKM)

Übergeordnetes Werk:	In: Remote Sensing - MDPI AG, 2009, 15(2023), 22, p 5426
Übergeordnetes Werk:	volume:15 ; year:2023 ; number:22, p 5426

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/rs15225426

Katalog-ID:	DOAJ101193661

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author	Huixin Ren
spellingShingle	Huixin Ren misc forest disturbance misc forest recovery misc LandTrendr misc random forests (RF) misc TimeSync-Plus misc Greater Khingan Mountains (GKM) misc Science misc Q Continuous Tracking of Forest Disturbance and Recovery in the Greater Khingan Mountains from Annual Landsat Imagery
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topic_title	Continuous Tracking of Forest Disturbance and Recovery in the Greater Khingan Mountains from Annual Landsat Imagery forest disturbance forest recovery LandTrendr random forests (RF) TimeSync-Plus Greater Khingan Mountains (GKM)
topic	misc forest disturbance misc forest recovery misc LandTrendr misc random forests (RF) misc TimeSync-Plus misc Greater Khingan Mountains (GKM) misc Science misc Q
topic_unstemmed	misc forest disturbance misc forest recovery misc LandTrendr misc random forests (RF) misc TimeSync-Plus misc Greater Khingan Mountains (GKM) misc Science misc Q
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title	Continuous Tracking of Forest Disturbance and Recovery in the Greater Khingan Mountains from Annual Landsat Imagery
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title_full	Continuous Tracking of Forest Disturbance and Recovery in the Greater Khingan Mountains from Annual Landsat Imagery
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title_sort	continuous tracking of forest disturbance and recovery in the greater khingan mountains from annual landsat imagery
title_auth	Continuous Tracking of Forest Disturbance and Recovery in the Greater Khingan Mountains from Annual Landsat Imagery
abstract	Understanding accurate and continuous forest dynamics is of key importance for forest protection and management in the Greater Khingan Mountains (GKM). There has been a lack of finely captured and long-term information on forest disturbance and recovery since the mega-fire of 1987 which may limit the scientific assessment of the GKM’s vegetation conditions. Therefore, we proposed a rapid and robust approach to track the dynamics of forest disturbance and recovery from 1987 to 2021 using Landsat time series, LandTrendr, and random forests (RF) models. Furthermore, we qualified the spatial characteristics of forest changes in terms of burn severity, topography, and distances from roads and settlements. Our results revealed that the integrated method of LandTrendr and RF is well adapted to track forest dynamics in the GKM, with an overall accuracy of 0.86. From 1987 to 2021, forests in the GKM showed a recovery trend with a net increase of more than 4.72 × 10<sup<4</sup< ha. Over 90% of disturbances occurred between 1987 and 2010 and over 75% of recovery occurred between 1987 and 1988. Mildly burned areas accounted for 51% of forest disturbance and severely burned areas contributed to 45% of forest recovery. Forest changes tended to occur in zones with elevations of 400–650 m, slopes of less than 9°, and within 6 km of roads and 24 km of settlements. Temporal trends of forest disturbance and recovery were mainly explained by the implementation timelines of major forestry policies. Our results provide high-resolution and time-series information on forest disturbance and recovery in the GKM which could support scientific decisions on forest management and sustainable utilization.
abstractGer	Understanding accurate and continuous forest dynamics is of key importance for forest protection and management in the Greater Khingan Mountains (GKM). There has been a lack of finely captured and long-term information on forest disturbance and recovery since the mega-fire of 1987 which may limit the scientific assessment of the GKM’s vegetation conditions. Therefore, we proposed a rapid and robust approach to track the dynamics of forest disturbance and recovery from 1987 to 2021 using Landsat time series, LandTrendr, and random forests (RF) models. Furthermore, we qualified the spatial characteristics of forest changes in terms of burn severity, topography, and distances from roads and settlements. Our results revealed that the integrated method of LandTrendr and RF is well adapted to track forest dynamics in the GKM, with an overall accuracy of 0.86. From 1987 to 2021, forests in the GKM showed a recovery trend with a net increase of more than 4.72 × 10<sup<4</sup< ha. Over 90% of disturbances occurred between 1987 and 2010 and over 75% of recovery occurred between 1987 and 1988. Mildly burned areas accounted for 51% of forest disturbance and severely burned areas contributed to 45% of forest recovery. Forest changes tended to occur in zones with elevations of 400–650 m, slopes of less than 9°, and within 6 km of roads and 24 km of settlements. Temporal trends of forest disturbance and recovery were mainly explained by the implementation timelines of major forestry policies. Our results provide high-resolution and time-series information on forest disturbance and recovery in the GKM which could support scientific decisions on forest management and sustainable utilization.
abstract_unstemmed	Understanding accurate and continuous forest dynamics is of key importance for forest protection and management in the Greater Khingan Mountains (GKM). There has been a lack of finely captured and long-term information on forest disturbance and recovery since the mega-fire of 1987 which may limit the scientific assessment of the GKM’s vegetation conditions. Therefore, we proposed a rapid and robust approach to track the dynamics of forest disturbance and recovery from 1987 to 2021 using Landsat time series, LandTrendr, and random forests (RF) models. Furthermore, we qualified the spatial characteristics of forest changes in terms of burn severity, topography, and distances from roads and settlements. Our results revealed that the integrated method of LandTrendr and RF is well adapted to track forest dynamics in the GKM, with an overall accuracy of 0.86. From 1987 to 2021, forests in the GKM showed a recovery trend with a net increase of more than 4.72 × 10<sup<4</sup< ha. Over 90% of disturbances occurred between 1987 and 2010 and over 75% of recovery occurred between 1987 and 1988. Mildly burned areas accounted for 51% of forest disturbance and severely burned areas contributed to 45% of forest recovery. Forest changes tended to occur in zones with elevations of 400–650 m, slopes of less than 9°, and within 6 km of roads and 24 km of settlements. Temporal trends of forest disturbance and recovery were mainly explained by the implementation timelines of major forestry policies. Our results provide high-resolution and time-series information on forest disturbance and recovery in the GKM which could support scientific decisions on forest management and sustainable utilization.
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container_issue	22, p 5426
title_short	Continuous Tracking of Forest Disturbance and Recovery in the Greater Khingan Mountains from Annual Landsat Imagery
url	https://doi.org/10.3390/rs15225426 https://doaj.org/article/aca84470fda3402695e078647ddf16ba https://www.mdpi.com/2072-4292/15/22/5426 https://doaj.org/toc/2072-4292
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up_date	2024-07-03T19:11:40.375Z
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Mildly burned areas accounted for 51% of forest disturbance and severely burned areas contributed to 45% of forest recovery. Forest changes tended to occur in zones with elevations of 400–650 m, slopes of less than 9°, and within 6 km of roads and 24 km of settlements. Temporal trends of forest disturbance and recovery were mainly explained by the implementation timelines of major forestry policies. 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Continuous Tracking of Forest Disturbance and Recovery in the Greater Khingan Mountains from Annual Landsat Imagery

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