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236 related items for PubMed ID: 36048352

  • 1. Integrating spaceborne LiDAR and Sentinel-2 images to estimate forest aboveground biomass in Northern China.
    Jiang F, Deng M, Tang J, Fu L, Sun H.
    Carbon Balance Manag; 2022 Sep 01; 17(1):12. PubMed ID: 36048352
    [Abstract] [Full Text] [Related]

  • 2. Total and component forest aboveground biomass inversion via LiDAR-derived features and machine learning algorithms.
    Ma J, Zhang W, Ji Y, Huang J, Huang G, Wang L.
    Front Plant Sci; 2023 Sep 01; 14():1258521. PubMed ID: 37954998
    [Abstract] [Full Text] [Related]

  • 3. Estimation of forest canopy closure in northwest Yunnan based on multi-source remote sensing data colla-boration.
    Zhou WW, Shu QT, Wang SW, Yang ZD, Luo SL, Xu L, Xiao JN.
    Ying Yong Sheng Tai Xue Bao; 2023 Jul 01; 34(7):1806-1816. PubMed ID: 37694464
    [Abstract] [Full Text] [Related]

  • 4. Estimating the aboveground biomass of coniferous forest in Northeast China using spectral variables, land surface temperature and soil moisture.
    Jiang F, Kutia M, Ma K, Chen S, Long J, Sun H.
    Sci Total Environ; 2021 Sep 01; 785():147335. PubMed ID: 33933773
    [Abstract] [Full Text] [Related]

  • 5. Impact of data model and point density on aboveground forest biomass estimation from airborne LiDAR.
    Garcia M, Saatchi S, Ferraz A, Silva CA, Ustin S, Koltunov A, Balzter H.
    Carbon Balance Manag; 2017 Dec 01; 12(1):4. PubMed ID: 28413848
    [Abstract] [Full Text] [Related]

  • 6. Continuous mapping of forest canopy height using ICESat-2 data and a weighted kernel integration of multi-temporal multi-source remote sensing data aided by Google Earth Engine.
    Mansouri J, Jafari M, Taheri Dehkordi A.
    Environ Sci Pollut Res Int; 2024 Aug 01; 31(37):49757-49779. PubMed ID: 39085688
    [Abstract] [Full Text] [Related]

  • 7. Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico.
    Urbazaev M, Thiel C, Cremer F, Dubayah R, Migliavacca M, Reichstein M, Schmullius C.
    Carbon Balance Manag; 2018 Feb 21; 13(1):5. PubMed ID: 29468474
    [Abstract] [Full Text] [Related]

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  • 10. Improved estimation of aboveground biomass of regional coniferous forests integrating UAV-LiDAR strip data, Sentinel-1 and Sentinel-2 imageries.
    Wang Y, Jia X, Chai G, Lei L, Zhang X.
    Plant Methods; 2023 Jun 30; 19(1):65. PubMed ID: 37391772
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  • 12. Improved estimation of aboveground biomass in wheat from RGB imagery and point cloud data acquired with a low-cost unmanned aerial vehicle system.
    Lu N, Zhou J, Han Z, Li D, Cao Q, Yao X, Tian Y, Zhu Y, Cao W, Cheng T.
    Plant Methods; 2019 Jun 30; 15():17. PubMed ID: 30828356
    [Abstract] [Full Text] [Related]

  • 13. Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling.
    Ma L, Hurtt G, Tang H, Lamb R, Lister A, Chini L, Dubayah R, Armston J, Campbell E, Duncanson L, Healey S, O'Neil-Dunne J, Ott L, Poulter B, Shen Q.
    Glob Chang Biol; 2023 Jun 30; 29(12):3378-3394. PubMed ID: 37013906
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  • 14. Exploring UAS-lidar as a sampling tool for satellite-based AGB estimations in the Miombo woodland of Zambia.
    Shamaoma H, Chirwa PW, Zekeng JC, Ramoelo A, Hudak AT, Handavu F, Syampungani S.
    Plant Methods; 2024 Jun 08; 20(1):88. PubMed ID: 38849856
    [Abstract] [Full Text] [Related]

  • 15. Mapping and analyzing the spatiotemporal dynamics of forest aboveground biomass in the ChangZhuTan urban agglomeration using a time series of Landsat images and meteorological data from 2010 to 2020.
    Liu Z, Long J, Lin H, Sun H, Ye Z, Zhang T, Yang P, Ma Y.
    Sci Total Environ; 2024 Sep 20; 944():173940. PubMed ID: 38879041
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  • 17. Forestry Applications of Space-Borne LiDAR Sensors: A Worldwide Bibliometric Analysis.
    Aguilar FJ, Rodríguez FA, Aguilar MA, Nemmaoui A, Álvarez-Taboada F.
    Sensors (Basel); 2024 Feb 08; 24(4):. PubMed ID: 38400264
    [Abstract] [Full Text] [Related]

  • 18. Forest degradation and biomass loss along the Chocó region of Colombia.
    Meyer V, Saatchi S, Ferraz A, Xu L, Duque A, García M, Chave J.
    Carbon Balance Manag; 2019 Mar 23; 14(1):2. PubMed ID: 30904964
    [Abstract] [Full Text] [Related]

  • 19. Forest aboveground biomass estimation using Landsat 8 and Sentinel-1A data with machine learning algorithms.
    Li Y, Li M, Li C, Liu Z.
    Sci Rep; 2020 Jun 19; 10(1):9952. PubMed ID: 32561836
    [Abstract] [Full Text] [Related]

  • 20. Dynamic monitoring of aboveground biomass in inner Mongolia grasslands over the past 23 Years using GEE and analysis of its driving forces.
    Yang D, Yang Z, Wen Q, Ma L, Guo J, Chen A, Zhang M, Xing X, Yuan Y, Lan X, Yang X.
    J Environ Manage; 2024 Mar 19; 354():120415. PubMed ID: 38417359
    [Abstract] [Full Text] [Related]

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