NEWS - Reforestation to combat climate change often encroaches on natural forests, wetlands and grasslands, destroying biodiversity, disrupting the natural environment and disrupting carbon and water cycles.
Forest cover is increasing globally, but it is difficult to know whether this is natural forest regeneration and growth or whether it is new tree planting. Accurately mapping forests with remote sensing technology could help.
Researchers from Tongji University in Shanghai and South Dakota State University in Brookings present an innovative approach that automatically maps natural forests and new plantations accurately at a spatial resolution of 30 meters.
“Accurately mapping the global distribution of natural forests and plantations at such a fine spatial resolution is challenging, but it is critical to understanding and mitigating environmental issues such as carbon sequestration and biodiversity loss,” said Yuelong Xiao of Tongji University in Shanghai.
“Traditional methods often lack sufficient sampling, hampering the accuracy and resolution of global forest maps. Our study presents a new approach to overcome these limitations by generating extensive sampling through time-series analysis of Landsat imagery,” said Xiao.
The data were taken from several different mapping systems, with the primary sources being Google Earth Engine Landsat imagery from 1985-2021 preprocessed by the US Geological Survey and imagery from the Sentinel-1 satellite from 2021.
The researchers also used the European Space Agency’s 2021 land cover map (WorldCover2021) and data from the ALOS Global Digital Surface Model. To overcome computational limitations, the world was divided into 57,559 small patches covering the entire globe and 70 million samples.
Established natural forests and plantations were distinguished using a value called disturbance frequency. Natural forests are more stable and less likely to change in size due to external factors, while plantations are more likely to be disturbed through reforestation or deforestation and other natural and man-made changes.
“This method for accurately mapping natural forests and plantations globally at 30-meter resolution is reliable. The resulting maps and samples are valuable resources for future environmental research and management, contributing to efforts to combat climate change,” Xiao said.
“Next, we will use the resulting samples and mapping methods to periodically update and refine global maps of natural and planted forests. Our ultimate goal is to improve the accuracy and resolution of forest maps worldwide, providing critical data for policymakers and researchers,” Xiao said.
Original research
Yuelong Xiao, Qunming Wang, Hankui K. Zhang. Global Natural and Planted Forests Mapping at Fine Spatial Resolution of 30 m. Journal of Remote Sensing. 2024;4:0204, DOI:10.34133/remotesensing.0204
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Forest cover is increasing globally, but it is difficult to know whether this is natural forest regeneration and growth or whether it is new tree planting. Accurately mapping forests with remote sensing technology could help.
Researchers from Tongji University in Shanghai and South Dakota State University in Brookings present an innovative approach that automatically maps natural forests and new plantations accurately at a spatial resolution of 30 meters.
“Accurately mapping the global distribution of natural forests and plantations at such a fine spatial resolution is challenging, but it is critical to understanding and mitigating environmental issues such as carbon sequestration and biodiversity loss,” said Yuelong Xiao of Tongji University in Shanghai.
“Traditional methods often lack sufficient sampling, hampering the accuracy and resolution of global forest maps. Our study presents a new approach to overcome these limitations by generating extensive sampling through time-series analysis of Landsat imagery,” said Xiao.
The data were taken from several different mapping systems, with the primary sources being Google Earth Engine Landsat imagery from 1985-2021 preprocessed by the US Geological Survey and imagery from the Sentinel-1 satellite from 2021.
The researchers also used the European Space Agency’s 2021 land cover map (WorldCover2021) and data from the ALOS Global Digital Surface Model. To overcome computational limitations, the world was divided into 57,559 small patches covering the entire globe and 70 million samples.
Established natural forests and plantations were distinguished using a value called disturbance frequency. Natural forests are more stable and less likely to change in size due to external factors, while plantations are more likely to be disturbed through reforestation or deforestation and other natural and man-made changes.
“This method for accurately mapping natural forests and plantations globally at 30-meter resolution is reliable. The resulting maps and samples are valuable resources for future environmental research and management, contributing to efforts to combat climate change,” Xiao said.
“Next, we will use the resulting samples and mapping methods to periodically update and refine global maps of natural and planted forests. Our ultimate goal is to improve the accuracy and resolution of forest maps worldwide, providing critical data for policymakers and researchers,” Xiao said.
Original research
Yuelong Xiao, Qunming Wang, Hankui K. Zhang. Global Natural and Planted Forests Mapping at Fine Spatial Resolution of 30 m. Journal of Remote Sensing. 2024;4:0204, DOI:10.34133/remotesensing.0204
Dlium theDlium