Search Results - "Mu, Xihan"

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  1. 1

    Review of indirect optical measurements of leaf area index: Recent advances, challenges, and perspectives by Yan, Guangjian, Hu, Ronghai, Luo, Jinghui, Weiss, Marie, Jiang, Hailan, Mu, Xihan, Xie, Donghui, Zhang, Wuming

    Published in Agricultural and forest meteorology (15-02-2019)
    “…•Latest progress and prospects of indirect LAI measurement.•Comprehensive review of theories, algorithms, instruments, and challenges.•Appealing new means of…”
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  2. 2

    Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review by Gao, Lin, Wang, Xiaofei, Johnson, Brian Alan, Tian, Qingjiu, Wang, Yu, Verrelst, Jochem, Mu, Xihan, Gu, Xingfa

    “…Green fractional vegetation cover (fc) is an important phenotypic factor in the fields of agriculture, forestry, and ecology. Spatially explicit monitoring of…”
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  3. 3

    Fractional vegetation cover estimation by using multi-angle vegetation index by Mu, Xihan, Song, Wanjuan, Gao, Zhan, McVicar, Tim R., Donohue, Randall J., Yan, Guangjian

    Published in Remote sensing of environment (01-10-2018)
    “…The vegetation index-based (VI-based) mixture model is widely used to derive green fractional vegetation cover (FVC) from remotely sensed data. Two critical…”
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  4. 4

    Indirect measurement of leaf area index on the basis of path length distribution by Hu, Ronghai, Yan, Guangjian, Mu, Xihan, Luo, Jinghui

    Published in Remote sensing of environment (01-12-2014)
    “…Accurate leaf area index (LAI) measurements are important for understanding and evaluating global mass and energy cycle. Foliage clumping serves an important…”
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  5. 5

    Extracting the Green Fractional Vegetation Cover from Digital Images Using a Shadow-Resistant Algorithm (SHAR-LABFVC) by Song, Wanjuan, Mu, Xihan, Yan, Guangjian, Huang, Shuai

    Published in Remote sensing (Basel, Switzerland) (01-08-2015)
    “…Taking photographs with a commercially available digital camera is an efficient and objective method for determining the green fractional vegetation cover…”
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  6. 6

    Single-footprint retrieval of clear-sky surface longwave radiation from hyperspectral AIRS data by Jiao, Zhong-Hu, Mu, Xihan

    “…•New SLR retrieval model was developed for hyperspectral infrared sounders.•An AIRS footprint geometrical model was proposed to match MODIS cloud masks.•Site…”
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  7. 7

    Topographic radiation modeling and spatial scaling of clear-sky land surface longwave radiation over rugged terrain by Yan, Guangjian, Wang, Tianxing, Jiao, Zhonghu, Mu, Xihan, Zhao, Jing, Chen, Ling

    Published in Remote sensing of environment (01-01-2016)
    “…Longwave radiation (5–100μm) is a critical component of the Earth's radiation budget. Most of the existing satellite-based retrieval algorithms are valid only…”
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  8. 8

    Simulating High-Resolution Sun-Induced Chlorophyll Fluorescence Image of Three-Dimensional Canopy Based on Photon Mapping by Luo, Yaotao, Xie, Donghui, Qi, Jianbo, Yan, Guangjian, Mu, Xihan

    Published in Remote sensing (Basel, Switzerland) (01-10-2024)
    “…The remote sensing of sun-induced chlorophyll fluorescence (SIF) is an emerging technique with immense potential for terrestrial vegetation sciences. However,…”
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  9. 9

    A novel method for extracting green fractional vegetation cover from digital images by Liu, Yaokai, Mu, Xihan, Wang, Haoxing, Yan, Guangjian

    Published in Journal of vegetation science (01-06-2012)
    “…Question: Although digital photography is an efficient and objective means of extracting green fractional vegetation cover (FVC), it lacks automation and…”
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  10. 10

    Quantifying Understory and Overstory Vegetation Cover Using UAV-Based RGB Imagery in Forest Plantation by Li, Linyuan, Chen, Jun, Mu, Xihan, Li, Weihua, Yan, Guangjian, Xie, Donghui, Zhang, Wuming

    Published in Remote sensing (Basel, Switzerland) (01-01-2020)
    “…Vegetation cover estimation for overstory and understory layers provides valuable information for modeling forest carbon and water cycles and refining forest…”
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  11. 11

    Ultrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach by Li, Linyuan, Mu, Xihan, Chianucci, Francesco, Qi, Jianbo, Jiang, Jingyi, Zhou, Jiaxin, Chen, Ling, Huang, Huaguo, Yan, Guangjian, Liu, Shouyang

    “…•Self-supervised deep learning for forest canopy mapping using UAVs is proposed.•2D images and 3D SfM point clouds are combined for automated training set…”
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  12. 12

    Assessment of remote-sensed vegetation indices for estimating forest chlorophyll concentration by Gao, Si, Yan, Kai, Liu, Jinxiu, Pu, Jiabin, Zou, Dongxiao, Qi, Jianbo, Mu, Xihan, Yan, Guangjian

    Published in Ecological indicators (01-05-2024)
    “…•3D RT simulations are used to assess the VI performance for estimating forest chlorophyll concentration.•Influences of saturation effect, soil backgrounds,…”
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  13. 13

    LESS LiDAR: A Full-Waveform and Discrete-Return Multispectral LiDAR Simulator Based on Ray Tracing Algorithm by Luo, Yaotao, Xie, Donghui, Qi, Jianbo, Zhou, Kun, Yan, Guangjian, Mu, Xihan

    Published in Remote sensing (Basel, Switzerland) (01-09-2023)
    “…Light detection and ranging (LiDAR) is a widely used technology for the acquisition of three-dimensional (3D) information about a wide variety of physical…”
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  14. 14

    Quantitative Analysis of Aerosol Influence on Suomi-NPP VIIRS Nighttime Light in China by Wang, Xuejun, Mu, Xihan, Yan, Guangjian

    “…As a primary nighttime light (NTL) data source, the day/night band (DNB) sensor of the visible infrared imaging radiometer suite (VIIRS) is used in a wide…”
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  15. 15

    Analysis Ready Data of the Chinese GaoFen Satellite Data by Zhong, Bo, Yang, Aixia, Liu, Qinhuo, Wu, Shanlong, Shan, Xiaojun, Mu, Xihan, Hu, Longfei, Wu, Junjun

    Published in Remote sensing (Basel, Switzerland) (01-05-2021)
    “…Analysis Ready Data (ARD) has been greatly recommended by the Committee on Earth Observation Satellites (CEOS) for simplifying and fostering long time series…”
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  16. 16

    Generation of a 16 m/10-day fractional vegetation cover product over China based on Chinese GaoFen-1 observations: method and validation by Zhao, Jing, Li, Jing, Liu, Qinhuo, Xu, Baodong, Mu, Xihan, Dong, Yadong

    Published in International journal of digital earth (08-12-2023)
    “…As China has recently launched the GaoFen-1 satellite (GF-1) carrying on the wide-field view (WFV) sensor, it is a challenging task to make full use of its…”
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  17. 17

    Revisiting the Performance of the Kernel-Driven BRDF Model Using Filtered High-Quality POLDER Observations by Hanliang Li, Kai Yan, Si Gao, Wanjuan Song, Xihan Mu

    Published in Forests (01-03-2022)
    “…The Bidirectional Reflectance Distribution Function (BRDF) is usually used to describe the reflectance anisotropy of a non-Lambertian surface and estimate…”
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  18. 18

    Individual tree segmentation of airborne and UAV LiDAR point clouds based on the watershed and optimized connection center evolution clustering by Li, Yi, Xie, Donghui, Wang, Yingjie, Jin, Shuangna, Zhou, Kun, Zhang, Zhixiang, Li, Weihua, Zhang, Wuming, Mu, Xihan, Yan, Guangjian

    Published in Ecology and evolution (01-07-2023)
    “…Light detection and ranging (LiDAR) data can provide 3D structural information of objects and are ideal for extracting individual tree parameters, and…”
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  19. 19

    Angular Normalization of Land Surface Temperature and Emissivity Using Multiangular Middle and Thermal Infrared Data by Huazhong Ren, Rongyuan Liu, Guangjian Yan, Xihan Mu, Zhao-Liang Li, Nerry, Francoise, Qiang Liu

    “…This paper aimed at the case of nonisothermal pixels and proposed a daytime temperature-independent spectral indices (TISI) method to retrieve directional…”
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  20. 20

    Analysis of the Directional Characteristics of the Clumping Index (CI) Based on RAMI-V Canopy Scenes by Xie, Jinke, Xie, Donghui, Zhou, Kun, Yan, Guangjian, Mu, Xihan

    Published in Journal of remote sensing (01-01-2024)
    “…The vegetation canopy clumping index (CI) is an important indicator for understanding radiative transport processes, radiation interception, and the…”
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