Abstract

Boreal forest is a sensitive indicator of the influence of climate change. It can quantify the level and spatial divergence of forest change for forest resources and carbon cycle research. This study selected a typical boreal forest affected by few human activities as a research area, in Siberia, with a latitude span of 51°N–69°N. A total of 150 Landsat images of this area acquired in 1985 and 2015 were collected. A hierarchical classification approach was first established to retrieve the information of forest cover and species. The forested and nonforested lands were discriminated by the decision tree method and, furthermore, the forested land was classified to broad-leaved and coniferous forests by a random forest algorithm. The overall accuracy was 90.37%, which indicates the validity of the approach. Finally, the quantitative information of the forest cover and species changes in each latitude zone of every 2° was analyzed. The results show that the overall boreal forest cover increased by 5.11% over the past three decades, with broad-leaved forest increasing by 3.54% and coniferous forest increasing by 1.57%. In addition, boreal forest increased in every latitude zone, and the spatial divergence of the changes of the boreal forest cover and species in different latitude zones were significant. Finally, broad-leaved forest increased more rapidly than coniferous forest, and the greatest increase, of up to 5.77%, occurred in the zone of 55°N–57°N.

Highlights

  • Forests cover more than one-third of the earth’s land surface

  • Climate change has a profound impact on global forestry, and continues to accelerate with increasing anthropogenic greenhouse gas (GHG) emissions [4]

  • Quantifying the spatial changes of forest cover and species is important for improving carbon accounting, climate change modeling, and biodiversity monitoring

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Summary

Introduction

Forests cover more than one-third of the earth’s land surface. They are one of the critical biomes globally and provide ecosystem services that benefit society at levels ranging from local to global [1,2]. Quantifying the spatial changes of forest cover and species is important for improving carbon accounting, climate change modeling, and biodiversity monitoring. Quantitative rates of the spatial changes of boreal forest cover and species are important indicators for research of the influence of climate change and are helpful for improving carbon accounting and biodiversity monitoring, which are not yet fully understood. Landsat images provide an ideal option for remote sensing with a medium spatial resolution of 30 m and temporal resolution of 16 days, allowing for monitoring of natural and human-induced landscape changes at local or regional scales over years and decades [30,31]. We selected a typical study area in Siberia in which the boreal forests have been affected primarily by natural factors to quantify the spatial changes and divergences of boreal forest cover and species over the past three decades using the Landsat series dataset. The aim was to reveal the latitude zones in which the forest cover and species were more sensitive to climate change, and to provide quantitative information for climate change and ecosystem research

Study Area
Datasets
Accuracy Assessment
Landsat Results
Spatial Change of Boreal Forest Cover
Spatial Changes of Boreal Forest Species
Conclusions
Full Text
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