Mapping forest disturbance and recovery for forest dynamics over large areas using Landsat time-series remote sensing

Author(s):  
Huy Trung Nguyen ◽  
Mariela Soto-Berelov ◽  
Simon D. Jones ◽  
Andrew Haywood ◽  
Samuel Hislop
Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 52
Author(s):  
Mohammed Othman Aljahdali ◽  
Sana Munawar ◽  
Waseem Razzaq Khan

Rabigh Lagoon, located on the eastern coast of the Red Sea, is an ecologically rich zone in Saudi Arabia, providing habitat to Avicennia marina mangrove trees. The environmental quality of the lagoon has been decaying since the 1990s mainly from sedimentation, road construction, and camel grazing. However, because of remedial measures, the mangrove communities have shown some degree of restoration. This study aims to monitor mangrove health of Rabigh Lagoon during the time it was under stress from road construction and after the road was demolished. For this purpose, time series of EVI (Enhanced Vegetation Index), MSAVI (Modified, Soil-Adjusted Vegetation Index), NDVI (Normalized Difference Vegetation Index), and NDMI (Normalized Difference Moisture Index) have been used as a proxy to plant biomass and indicator of forest disturbance and recovery. Long-term trend patterns, through linear, least square regression, were estimated using 30 m annual Landsat surface-reflectance-derived indices from 1986 to 2019. The outcome of this study showed (1) a positive trend over most of the study region during the evaluation period; (2) most trend slopes were gradual and weakly positive, implying subtle changes as opposed to abrupt changes; (3) all four indices divided the times series into three phases: degraded mangroves, slow recovery, and regenerated mangroves; (4) MSAVI performed best in capturing various trend patterns related to the greenness of vegetation; and (5) NDMI better identified forest disturbance and recovery in terms of water stress. Validating observed patterns using only the regression slope proved to be a challenge. Therefore, water quality parameters such as salinity, pH/dissolved oxygen should also be investigated to explain the calculated trends.


2017 ◽  
Vol 194 ◽  
pp. 303-321 ◽  
Author(s):  
Joanne C. White ◽  
Michael A. Wulder ◽  
Txomin Hermosilla ◽  
Nicholas C. Coops ◽  
Geordie W. Hobart

2020 ◽  
Vol 12 (14) ◽  
pp. 2235
Author(s):  
Viktor Myroniuk ◽  
Andrii Bilous ◽  
Yevhenii Khan ◽  
Andrii Terentiev ◽  
Pavlo Kravets ◽  
...  

Mapping forest disturbance is crucial for many applications related to decision-making for sustainable forest management. This study identified the effect of illegal amber mining on forest change and accumulated carbon stock across a study area of 8125.5 ha in northern Ukraine. Our method relies on the Google Earth Engine (GEE) implementation of the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) temporal segmentation algorithm of Landsat time-series (LTS) to derive yearly maps of forest disturbance and recovery in areas affected by amber extraction operations. We used virtual reality (VR) 360 interactive panoramic images taken from the sites to attribute four levels of forest disturbance associated with the delta normalized burn ratio (dNBR) and then calculated the carbon loss. We revealed that illegal amber extraction in Ukraine has been occurring since the middle of the 1990s, yielding 3260 ha of total disturbed area up to 2019. This study indicated that the area of forest disturbance increased dramatically during 2013–2014, and illegal amber operations persist. As a result, regrowth processes were mapped on only 375 ha of total disturbed area. The results were integrated into the Forest Stewardship Council® (FSC®) quality management system in the region to categorize Forest Management Units (FMUs) conforming to different disturbance rates and taking actions related to their certification status. Moreover, carbon loss evaluation allows the responsible forest management systems to be streamlined and to endorse ecosystem service assessment.


2015 ◽  
Vol 170 ◽  
pp. 317-327 ◽  
Author(s):  
Ryan J. Frazier ◽  
Nicholas C. Coops ◽  
Michael A. Wulder

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