Journal
FORESTS
Volume 11, Issue 2, Pages -Publisher
MDPI
DOI: 10.3390/f11020130
Keywords
Landsat; GEE; random forest; tree species distribution evolution; Mount Tai
Categories
Funding
- Chinese Public Research Fund for Key Technologies for Landscape Quality Improvement and Resource Conservation in Forest Parks [201104051]
- Integration and Demonstration of High Yield and Efficiency Technology of Black Locust [2017YFD0601203]
- Key Mechanism of Natural Regeneration of Chinese Arborvitae of Mount Tai [2017GNC10121]
Ask authors/readers for more resources
Located in the Mount Tai state-owned forest farm, this study adopted Landsat multispectral remote sensing data in 2000 and 2016 on the GEE (Google Earth Engine) platform and selected four phases of images each year according to the phenological period. By dealing with the current situation map of forestry resources in 2000 and the field survey data in 2016, the samples of tree species distribution in 2000 and 2016 were obtained. On the basis of topographic correction with the empirical rotation model, this study used the random forest (RF) classifier to classify tree species from remote sensing images in 2000 and 2016, achieving high classification accuracy. The results showed that, after 16 years of evolution, the percentage of pine species in the forest decreased from 55.69% to 50.22%, with a percentage decrease as high as 5.47%. The percentage of black locust (Robinia pseudoacacia) increased from 10.15% in 2000 to 13.75% in 2016, with an increase of 3.60%. Quercus also had a positive growth in the area. This result reflected the expansion of black locust.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available