Guanglong Ou

According to our database, Guanglong Ou authored at least 9 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Retrieval of Three-Dimensional Green Volume in Urban Green Space from Multi-Source Remote Sensing Data.

Zehu Hong, Weiheng Xu, Yun Liu, Leiguang Wang, Guanglong Ou, Ning Lu, Qinling Dai

Remote. Sens., November, 2023

Estimating the Aboveground Biomass of Various Forest Types with High Heterogeneity at the Provincial Scale Based on Multi-Source Data.

Tianbao Huang, Guanglong Ou, Yong Wu, Xiaoli Zhang, Zihao Liu, Hui Xu, Xiongwei Xu, Zhenghui Wang, Can Xu

Remote. Sens., July, 2023

Synergism of Multi-Modal Data for Mapping Tree Species Distribution - A Case Study from a Mountainous Forest in Southwest China.

Pengfei Zheng, Panfei Fang, Leiguang Wang, Guanglong Ou, Weiheng Xu, Fei Dai, Qinling Dai

Remote. Sens., February, 2023

Reduction in Uncertainty in Forest Aboveground Biomass Estimation Using Sentinel-2 Images: A Case Study of Pinus densata Forests in Shangri-La City, China.

Lu Li, Boqi Zhou, Yanfeng Liu, Yong Wu, Jing Tang, Weiheng Xu, Leiguang Wang, Guanglong Ou

Remote. Sens., February, 2023

2022

Enhancing Aboveground Biomass Estimation for Three Pinus Forests in Yunnan, SW China, Using Landsat 8.

Jing Tang, Ying Liu, Lu Li, Yanfeng Liu, Yong Wu, Hui Xu, Guanglong Ou

Remote. Sens., 2022

Mapping Forest Aboveground Biomass with MODIS and Fengyun-3C VIRR Imageries in Yunnan Province, Southwest China Using Linear Regression, K-Nearest Neighbor and Random Forest.

Huafang Chen, Zhihao Qin, De-Li Zhai, Guanglong Ou, Xiong Li, Gaojuan Zhao, Jinlong Fan, Chunliang Zhao, Hui Xu

Remote. Sens., 2022

2021

Mapping Forest Type with Multi-Seasonal Landsat Data and Multiple Environmental Factors in Yunnan Province Based on Google Earth Engine.

Ruonan Li, Leiguang Wang, Guanglong Ou, Weiheng Xu, Qinling Dai

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2019

Improving Forest Aboveground Biomass Estimation of Pinus densata Forest in Yunnan of Southwest China by Spatial Regression using Landsat 8 Images.

Guanglong Ou, Yanyu Lv, Hui Xu, Guangxing Wang

Remote. Sens., 2019

Improving Aboveground Biomass Estimation of <i>Pinus densata</i> Forests in Yunnan Using Landsat 8 Imagery by Incorporating Age Dummy Variable and Method Comparison.

Guanglong Ou, Chao Li, Yanyu Lv, Anchao Wei, Hexian Xiong, Hui Xu, Guangxing Wang

Remote. Sens., 2019