Guanglong Ou

发表

Positive relationship between species richness and aboveground biomass across forest strata in a primary Pinus kesiya forest

Shuaifeng Li, Jianrong Su, Wande Liu, 2018, Scientific Reports.

Classifying Forest Types over a Mountainous Area in Southwest China with Landsat Data Composites and Multiple Environmental Factors

Xin Huang, Ruonan Li, Weiheng Xu, 2022, Forests.

Application of a Panel Data Quantile-Regression Model to the Dynamics of Carbon Sequestration in Pinus kesiya var. langbianensis Natural Forests

Chang-fu Liu, Guanglong Ou, Yao Fu, 2021, Forests.

Assessment of Spatial-Temporal Changes of Landscape Ecological Risk in Xishuangbanna, China from 1990 to 2019

Yun Liu, Weiheng Xu, Leiguang Wang, 2022, Sustainability.

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

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

A Method for Estimating Forest Aboveground Biomass at the Plot Scale Combining the Horizontal Distribution Model of Biomass and Sampling Technique

Jialong Zhang, Chi Lu, Hui Xu, 2022, Forests.

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

Z. Qin, Jinlong Fan, Hui Xu, 2022, Remote. Sens..

Incorporating topographic factors in nonlinear mixed-effects models for aboveground biomass of natural Simao pine in Yunnan, China

Hui Xu, Guanglong Ou, B. Zhang, 2016, Journal of Forestry Research.

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

Weiheng Xu, Fei Dai, Leiguang Wang, 2023, 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..

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

Hui Xu, Guangxing Wang, Guanglong Ou, 2019, Remote. Sens..

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

Chao Li, Hui Xu, Guangxing Wang, 2019, Remote. Sens..

Collapse risk assessment of deep-buried tunnel during construction and its application

Fei Tan, Guang-Zhao Ou, Yu-Yong Jiao, 2021 .

Incorporating competition factors in a mixed-effect model with random effects of site quality for individual tree above-ground biomass growth of Pinus kesiya var. langbianensis

Hui Xu, Guanglong Ou, Yanbing Leng, 2019 .

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.

Regionalized classification of stand tree species in mountainous forests by fusing advanced classifiers and ecological niche model

Ruonan Li, Weiheng Xu, Leiguang Wang, 2023, GIScience & Remote Sensing.

Positive relationship between species richness and aboveground biomass across forest strata in a primary Pinus kesiya forest

Shuaifeng Li, Jianrong Su, Wande Liu, 2018, Scientific Reports.

The relationship between species richness and aboveground biomass in a primary Pinus kesiya forest of Yunnan, southwestern China

Shuaifeng Li, Hui Xu, Jianrong Su, 2018, PloS one.

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.

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

Weiheng Xu, Guanglong Ou, Zehu Hong, 2023, Remote. Sens..

Remote Sensing Estimation of Forest Carbon Stock Based on Machine Learning Algorithms

Guanglong Ou, Fengyun Cheng, Meng Wang, 2024, Forests.

Advances and challenges of carbon storage estimation in tea plantation

Weiheng Xu, Guanglong Ou, Zehu Hong, 2024, Ecological Informatics.