Search Results - "Gao, Zhihai"

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  1. 1

    High resolution remote sensing recognition of elm sparse forest via deep-learning-based semantic segmentation by Liu, Hao, Sun, Bin, Gao, Zhihai, Chen, Zhulin, Zhu, Zhongzheng

    Published in Ecological indicators (01-09-2024)
    “…•Constructs a Gaofen-2 imagery dataset specialized for elm canopy semantic segmentation task.•Trains 6 deep-learning segmentation frameworks; selects the…”
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    Journal Article
  2. 2

    Effects of grazing exclusion in Xilin Gol grassland differ between regions by Liu, Jinghui, Wu, Jianjun, Su, Hongbo, Gao, Zhihai, Wu, Zhitao

    Published in Ecological engineering (01-02-2017)
    “…Establishment of grazing exclusion has become an important rangeland rehabilitation strategy in semi-arid regions. However, the effect of grazing exclusion on…”
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  3. 3

    Ecological restoration effects of the Beijing–Tianjin Sandstorm Source Control Project in China since 2000 by Li, Changlong, Gao, Zhihai, Sun, Bin, Wu, Junjun, Wang, Hongyan, Ding, Xiangyuan

    Published in Ecological indicators (01-02-2023)
    “…[Display omitted] •A vegetation–water–soil–environment ecological restoration evaluation system.•Optimized models were used to evaluate the four-dimensional…”
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  4. 4

    An Integrated Method for Estimating Forest-Canopy Closure Based on UAV LiDAR Data by Gao, Ting, Gao, Zhihai, Sun, Bin, Qin, Pengyao, Li, Yifu, Yan, Ziyu

    Published in Remote sensing (Basel, Switzerland) (01-09-2022)
    “…Forest-canopy closure (FCC) reflects the coverage of the forest tree canopy, which is one of the most important indicators of forest structure and a core…”
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  5. 5

    Estimation of Evapotranspiration in Sparse Vegetation Areas by Applying an Optimized Two-Source Model by Li, Changlong, Li, Zengyuan, Gao, Zhihai, Sun, Bin

    Published in Remote sensing (Basel, Switzerland) (01-04-2021)
    “…Evapotranspiration (ET) is an important part of the water, carbon, and energy cycles in ecosystems, especially in the drylands. However, due to the…”
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  6. 6

    Methods for sandy land detection based on multispectral remote sensing data by Wu, Junjun, Gao, Zhihai, Liu, Qinhuo, Li, Zengyuan, Zhong, Bo

    Published in Geoderma (15-04-2018)
    “…Sandification is becoming a serious threat to the sustainability of human habitation. The potential of remote sensing in sandy land detection has been…”
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  7. 7

    Global degradation trends of grassland and their driving factors since 2000 by Yan, Ziyu, Gao, Zhihai, Sun, Bin, Ding, Xiangyuan, Gao, Ting, Li, Yifu

    Published in International journal of digital earth (31-12-2023)
    “…Grassland is the second largest terrestrial ecosystem and a fundamental land resource for human survival and development. Although grassland degradation is a…”
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  8. 8

    Nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates of typical desert vegetation in western China by Ji, Cuicui, Jia, Yonghong, Gao, Zhihai, Wei, Huaidong, Li, Xiaosong

    Published in PloS one (14-12-2017)
    “…Desert vegetation plays significant roles in securing the ecological integrity of oasis ecosystems in western China. Timely monitoring of…”
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  9. 9

    How can integrated Space–Air–Ground observation contribute in aboveground biomass of shrub plants estimation in shrub-encroached Grasslands? by Sun, Bin, Rong, Rong, Cui, Hanwen, Guo, Ye, Yue, Wei, Yan, Ziyu, Wang, Han, Gao, Zhihai, Wu, Zhitao

    “…•Integrated Space–Air–Ground enhance the accuracy of the Shrub AGB estimation in SEGs.•3D information is important for AGB estimation, especially the planar…”
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  10. 10

    Is Spectral Unmixing Model or Nonlinear Statistical Model More Suitable for Shrub Coverage Estimation in Shrub-Encroached Grasslands Based on Earth Observation Data? A Case Study in Xilingol Grassland, China by Xu, Zhengyong, Sun, Bin, Zhang, Wangfei, Gao, Zhihai, Yue, Wei, Wang, Han, Wu, Zhitao, Teng, Sihan

    Published in Remote sensing (Basel, Switzerland) (01-12-2023)
    “…Due to the effects of global climate change and altered human land-use patterns, typical shrub encroachment in grasslands has become one of the most prominent…”
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  11. 11

    Land degradation dynamic in the first decade of twenty-first century in the Beijing–Tianjin dust and sandstorm source region by Li, Xiaosong, Wang, Hongyan, Wang, Jinying, Gao, Zhihai

    Published in Environmental earth sciences (01-09-2015)
    “…Land degradation dynamic assessment is very important to understand the effectiveness of ecological engineering and provide decision support for future…”
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  12. 12

    Evaluating Forest Ecosystem Services in the Greater Khingan Mountains Area Using Remote Sensing by Gao, Ting, Gao, Zhihai, Sun, Bin, Liu, Hao, Wu, Zhitao

    “…Evaluating forest ecosystem services ( FES ) is crucial for comprehensively recognizing forest value and for formulating targeted forest management plans…”
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  13. 13

    Estimating Soil Organic Carbon Density in the Otindag Sandy Land, Inner Mongolia, China, for modelling spatiotemporal variations and evaluating the influences of human activities by Sun, Bin, Wang, Yan, Li, Zengyuan, Gao, Wentao, Wu, Junjun, Li, Changlong, Song, Zhangliang, Gao, Zhihai

    Published in Catena (Giessen) (01-08-2019)
    “…Accurate quantitative estimates of Soil Organic Carbon Density (SOCD) can effectively represent regional carbon cycle processes and regulation mechanisms, and…”
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  14. 14
  15. 15

    Integrating vegetation phenological characteristics and polarization features with object-oriented techniques for grassland type identification by Sun, Bin, Qin, Pengyao, Li, Changlong, Gao, Zhihai, Grainger, Alan, Li, Xiaosong, Wang, Yan, Yue, Wei

    Published in Geo-spatial information science (03-05-2024)
    “…Due to the small size, variety, and high degree of mixing of herbaceous vegetation, remote sensing-based identification of grassland types primarily focuses on…”
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  16. 16

    Comparison of Methods for Estimating Fractional Cover of Photosynthetic and Non-Photosynthetic Vegetation in the Otindag Sandy Land Using GF-1 Wide-Field View Data by Li, Xiaosong, Zheng, Guoxiong, Wang, Jinying, Ji, Cuicui, Sun, Bin, Gao, Zhihai

    Published in Remote sensing (Basel, Switzerland) (01-10-2016)
    “…Photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) are important ground cover types for desertification monitoring and land management…”
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  17. 17

    Extraction of rocky desertification information in karst area by using different multispectral sensor data and multiple endmember spectral mixture analysis method by Li, Yifu, Sun, Bin, Gao, Zhihai, Su, Wensen, Wang, Bengyu, Yan, Ziyu, Gao, Ting

    Published in Frontiers in environmental science (07-11-2022)
    “…As a typical form of land degradation, karst rocky desertification seriously restricts the development of the regional social economy and seriously threatens…”
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  18. 18

    Did Ecological Engineering Projects Have a Significant Effect on Large-scale Vegetation Restoration in Beijing-Tianjin Sand Source Region, China? A Remote Sensing Approach by Li, Xiaosong, Wang, Hongyan, Zhou, Shufang, Sun, Bin, Gao, Zhihai

    Published in Chinese geographical science (01-04-2016)
    “…Aiming for the restoration of degraded ecosystems, many ecological engineering projects have been implemented around the world. This study investigates the…”
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  19. 19

    High Spatial Resolution Topsoil Organic Matter Content Mapping Across Desertified Land in Northern China by Junting, Yang, Xiaosong, Li, Bo, Wu, Junjun, Wu, Bin, Sun, Changzhen, Yan, Zhihai, Gao

    Published in Frontiers in environmental science (25-08-2021)
    “…Soil organic matter (SOM) content is an effective indicator of desertification; thus, monitoring its spatial‒temporal changes on a large scale is important for…”
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  20. 20

    Degraded land detection by soil particle composition derived from multispectral remote sensing data in the Otindag Sandy Lands of China by Wu, Junjun, Li, Zengyuan, Gao, Zhihai, Wang, Bengyu, Bai, Lina, Sun, Bin, Li, Changlong, Ding, Xiangyuan

    Published in Geoderma (01-03-2015)
    “…Remote sensing technology has shown considerable potential for the estimation of soil properties. In this paper, we proposed a method by using the measured…”
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