Detection of Tree Species in Beijing Plain Afforestation Project Using Satellite Sensors and Machine Learning Algorithms
Mapping tree species distributions in urban areas is significant for managing afforestation plans and pest infestations but can be challenging over large areas. This research compared the classification accuracy of three data sources and three machine learning algorithm combinations. It evaluated th...
Main Authors: | Xudong Zhang, Linfeng Yu, Quan Zhou, Dewei Wu, Lili Ren, Youqing Luo |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-09-01
|
Series: | Forests |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4907/14/9/1889 |
Similar Items
-
Potentialities and Limitations of Research on VHRS Data: Alexander the Great’s Military Camp at Gaugamela on the Navkur Plain in Kurdish Iraq as a Test Case
by: Tomasz Pirowski, et al.
Published: (2021-02-01) -
Susceptibility Mapping of Unhealthy Trees in Jiuzhaigou Valley Biosphere Reserve
by: Sheng Gao, et al.
Published: (2023-11-01) -
Evaluation of Sentinel-2 and Landsat 8 Images for Estimating Chlorophyll-a Concentrations in Lake Chad, Africa
by: Willibroad Gabila Buma, et al.
Published: (2020-07-01) -
SEG-ESRGAN: A Multi-Task Network for Super-Resolution and Semantic Segmentation of Remote Sensing Images
by: Luis Salgueiro, et al.
Published: (2022-11-01) -
Fusion of Dense Airborne LiDAR and Multispectral Sentinel-2 and Pleiades Satellite Imagery for Mapping Riparian Forest Species Biodiversity at Tree Level
by: Houssem Njimi, et al.
Published: (2024-03-01)