Hasil Pencarian - Guanglong Ou

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  1. 1
    Improving Forest Aboveground Biomass Estimation of <i>Pinus densata</i> Forest in Yunnan of Southwest China by Spatial Regression using Landsat 8 Images

    Improving Forest Aboveground Biomass Estimation of <i>Pinus densata</i> Forest in Yunnan of Southwest China by Spatial Regression using Landsat 8 Images oleh Guanglong Ou, Yanyu Lv, Hui Xu, Guangxing Wang

    Diterbitkan 2019-11-01
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  2. 2
    Remote Sensing Estimation of Forest Carbon Stock Based on Machine Learning Algorithms

    Remote Sensing Estimation of Forest Carbon Stock Based on Machine Learning Algorithms oleh Fengyun Cheng, Guanglong Ou, Meng Wang, Chang Liu

    Diterbitkan 2024-04-01
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  3. 3
    Application of a Panel Data Quantile-Regression Model to the Dynamics of Carbon Sequestration in <i>Pinus kesiya</i> var. <i>langbianensis</i> Natural Forests

    Application of a Panel Data Quantile-Regression Model to the Dynamics of Carbon Sequestration in <i>Pinus kesiya</i> var. <i>langbianensis</i> Natural Forests oleh Chang Liu, Guanglong Ou, Yao Fu, Chengcheng Zhang, Cairong Yue

    Diterbitkan 2021-12-01
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  4. 4
    The relationship between species richness and aboveground biomass in a primary Pinus kesiya forest of Yunnan, southwestern China.

    The relationship between species richness and aboveground biomass in a primary Pinus kesiya forest of Yunnan, southwestern China. oleh Shuaifeng Li, Xuedong Lang, Wande Liu, Guanglong Ou, Hui Xu, Jianrong Su

    Diterbitkan 2018-01-01
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  5. 5
    High-density forest AGB estimation in tropical forest integrated with PolInSAR multidimensional features and optimized machine learning algorithms

    High-density forest AGB estimation in tropical forest integrated with PolInSAR multidimensional features and optimized machine learning algorithms oleh Hongbin Luo, Sitong Qin, Jing Li, Chi Lu, Cairong Yue, Guanglong Ou

    Diterbitkan 2024-03-01
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  6. 6
    Error Analysis on the Five Stand Biomass Growth Estimation Methods for a Sub-Alpine Natural Pine Forest in Yunnan, Southwestern China

    Error Analysis on the Five Stand Biomass Growth Estimation Methods for a Sub-Alpine Natural Pine Forest in Yunnan, Southwestern China oleh Guoqi Chen, Xilin Zhang, Chunxiao Liu, Chang Liu, Hui Xu, Guanglong Ou

    Diterbitkan 2022-10-01
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  7. 7
    An efficient method for estimating tropical forest canopy height from airborne PolInSAR data

    An efficient method for estimating tropical forest canopy height from airborne PolInSAR data oleh Hongbin Luo, Cairong Yue, Yong Wu, Xiaoli Zhang, Chi Lu, Guanglong Ou

    Diterbitkan 2024-09-01
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  8. 8
    Synergism of Multi-Modal Data for Mapping Tree Species Distribution—A Case Study from a Mountainous Forest in Southwest China

    Synergism of Multi-Modal Data for Mapping Tree Species Distribution—A Case Study from a Mountainous Forest in Southwest China oleh Pengfei Zheng, Panfei Fang, Leiguang Wang, Guanglong Ou, Weiheng Xu, Fei Dai, Qinling Dai

    Diterbitkan 2023-02-01
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  9. 9
    Enhancing Aboveground Biomass Estimation for Three Pinus Forests in Yunnan, SW China, Using Landsat 8

    Enhancing Aboveground Biomass Estimation for Three Pinus Forests in Yunnan, SW China, Using Landsat 8 oleh Jing Tang, Ying Liu, Lu Li, Yanfeng Liu, Yong Wu, Hui Xu, Guanglong Ou

    Diterbitkan 2022-09-01
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  10. 10
    Improving Aboveground Biomass Estimation of <i>Pinus densata</i> Forests in Yunnan Using Landsat 8 Imagery by Incorporating Age Dummy Variable and Method Comparison

    Improving Aboveground Biomass Estimation of <i>Pinus densata</i> Forests in Yunnan Using Landsat 8 Imagery by Incorporating Age Dummy Variable and Method Comparison oleh Guanglong Ou, Chao Li, Yanyu Lv, Anchao Wei, Hexian Xiong, Hui Xu, Guangxing Wang

    Diterbitkan 2019-03-01
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  11. 11
    Retrieval of Three-Dimensional Green Volume in Urban Green Space from Multi-Source Remote Sensing Data

    Retrieval of Three-Dimensional Green Volume in Urban Green Space from Multi-Source Remote Sensing Data oleh Zehu Hong, Weiheng Xu, Yun Liu, Leiguang Wang, Guanglong Ou, Ning Lu, Qinling Dai

    Diterbitkan 2023-11-01
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  12. 12
    A Method for Estimating Forest Aboveground Biomass at the Plot Scale Combining the Horizontal Distribution Model of Biomass and Sampling Technique

    A Method for Estimating Forest Aboveground Biomass at the Plot Scale Combining the Horizontal Distribution Model of Biomass and Sampling Technique oleh Chi Lu, Hui Xu, Jialong Zhang, Aiyun Wang, Heng Wu, Rui Bao, Guanglong Ou

    Diterbitkan 2022-10-01
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  13. 13
    Estimation of the Three-Dimension Green Volume Based on UAV RGB Images: A Case Study in YueYaTan Park in Kunming, China

    Estimation of the Three-Dimension Green Volume Based on UAV RGB Images: A Case Study in YueYaTan Park in Kunming, China oleh Zehu Hong, Weiheng Xu, Yun Liu, Leiguang Wang, Guanglong Ou, Ning Lu, Qinling Dai

    Diterbitkan 2023-04-01
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  14. 14
    Integrating three-dimensional greenness into RSEI improved the scientificity of ecological environment quality assessment for forest

    Integrating three-dimensional greenness into RSEI improved the scientificity of ecological environment quality assessment for forest oleh Yun Liu, Weiheng Xu, Zehu Hong, Leiguang Wang, Guanglong Ou, Ning Lu, Qinling Dai

    Diterbitkan 2023-12-01
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  15. 15
    Classifying Forest Types over a Mountainous Area in Southwest China with Landsat Data Composites and Multiple Environmental Factors

    Classifying Forest Types over a Mountainous Area in Southwest China with Landsat Data Composites and Multiple Environmental Factors oleh Ruonan Li, Panfei Fang, Weiheng Xu, Leiguang Wang, Guanglong Ou, Wanqiu Zhang, Xin Huang

    Diterbitkan 2022-01-01
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  16. 16
    Application of GM (1,1) to predict the dynamics of stand carbon storage in Pinus Kesiya var. langbianensis natural forests

    Application of GM (1,1) to predict the dynamics of stand carbon storage in Pinus Kesiya var. langbianensis natural forests oleh Chunxi Gu, Zhenyan Zhou, Chang Liu, Wangfei Zhang, Zhengdao Yang, Wenwu Zhou, Guanglong Ou

    Diterbitkan 2024-07-01
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  17. 17
    Regionalized classification of stand tree species in mountainous forests by fusing advanced classifiers and ecological niche model

    Regionalized classification of stand tree species in mountainous forests by fusing advanced classifiers and ecological niche model oleh Panfei Fang, Guanglong Ou, Ruonan Li, Leiguang Wang, Weiheng Xu, Qinling Dai, Xin Huang

    Diterbitkan 2023-12-01
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  18. 18
    Reduction in Uncertainty in Forest Aboveground Biomass Estimation Using Sentinel-2 Images: A Case Study of <i>Pinus densata</i> Forests in Shangri-La City, China

    Reduction in Uncertainty in Forest Aboveground Biomass Estimation Using Sentinel-2 Images: A Case Study of <i>Pinus densata</i> Forests in Shangri-La City, China oleh Lu Li, Boqi Zhou, Yanfeng Liu, Yong Wu, Jing Tang, Weiheng Xu, Leiguang Wang, Guanglong Ou

    Diterbitkan 2023-01-01
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  19. 19
    Spatial Effects Analysis on Individual-Tree Aboveground Biomass in a Tropical <i>Pinus kesiya</i> var. <i>langbianensis</i> Natural Forest in Yunnan, Southwestern China

    Spatial Effects Analysis on Individual-Tree Aboveground Biomass in a Tropical <i>Pinus kesiya</i> var. <i>langbianensis</i> Natural Forest in Yunnan, Southwestern China oleh Xilin Zhang, Guoqi Chen, Chunxiao Liu, Qinling Fan, Wenfang Li, Yong Wu, Hui Xu, Guanglong Ou

    Diterbitkan 2023-06-01
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  20. 20
    Aboveground biomass inversion of forestland in a Jinsha River dry-hot valley by integrating high and medium spatial resolution optical images: A case study on Yuanmou County of Southwest China

    Aboveground biomass inversion of forestland in a Jinsha River dry-hot valley by integrating high and medium spatial resolution optical images: A case study on Yuanmou County of Sou... oleh Zihao Liu, Tianbao Huang, Yong Wu, Xiaoli Zhang, Chunxiao Liu, Zhibo Yu, Can Xu, Guanglong Ou

    Diterbitkan 2024-11-01
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