Yong Wu

发表

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

Y. Liu, Hui Xu, Guanglong Ou, 2022, Remote. Sens..

Evaluating the Hydrus-1D Model Optimized by Remote Sensing Data for Soil Moisture Simulations in the Maize Root Zone

Chunjiang Zhao, Lili Zhangzhong, J. Peng, 2022, Remote. Sens..

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

Weiheng Xu, Leiguang Wang, Guanglong Ou, 2023, Remote. Sens..

Spatial Effects Analysis on Individual-Tree Aboveground Biomass in a Tropical Pinus kesiya var. langbianensis Natural Forest in Yunnan, Southwestern China

Hui Xu, Guanglong Ou, Yong Wu, 2023, Forests.

Improving the accuracy of forest aboveground biomass using Landsat 8 OLI images by quantile regression neural network for Pinus densata forests in southwestern China

Weiheng Xu, Leiguang Wang, Xiaoli Zhang, 2023, Frontiers in Forests and Global Change.

Characterising spatial effects of individual tree and component biomass for three typical tree species in Yunnan, China

Guanglong Ou, Yong Wu, Qinlin Fan, 2024, Ecological Indicators.

An efficient and accurate deep learning method for tree species classification that integrates depthwise separable convolution and dilated convolution using hyperspectral data

Guanglong Ou, Yong Wu, Xiaoli Zhang, 2024, International Journal of Digital Earth.

Improved random forest algorithms for increasing the accuracy of forest aboveground biomass estimation using Sentinel-2 imagery

Weiheng Xu, Guanglong Ou, Yong Wu, 2024, Ecological Indicators.

Interacting Sentinel-2A, Sentinel 1A, and GF-2 Imagery to Improve the Accuracy of Forest Aboveground Biomass Estimation in a Dry-Hot Valley

Guanglong Ou, Yong Wu, Fuyan Zou, 2024, Forests.