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188 related items for PubMed ID: 31035986

  • 1. Estimation of vegetation water content using hyperspectral vegetation indices: a comparison of crop water indicators in response to water stress treatments for summer maize.
    Zhang F, Zhou G.
    BMC Ecol; 2019 Apr 29; 19(1):18. PubMed ID: 31035986
    [Abstract] [Full Text] [Related]

  • 2. Retrieving the Diurnal FPAR of a Maize Canopy from the Jointing Stage to the Tasseling Stage with Vegetation Indices under Different Water Stresses and Light Conditions.
    Zhao L, Liu Z, Xu S, He X, Ni Z, Zhao H, Ren S.
    Sensors (Basel); 2018 Nov 15; 18(11):. PubMed ID: 30445752
    [Abstract] [Full Text] [Related]

  • 3. [Fraction of absorbed photosynthetically active radiation over summer maize canopy estimated by hyperspectral remote sensing under different drought conditions.].
    Liu EH, Zhou GS, Zhou L.
    Ying Yong Sheng Tai Xue Bao; 2019 Jun 15; 30(6):2021-2029. PubMed ID: 31257775
    [Abstract] [Full Text] [Related]

  • 4. Capability of crop water content for revealing variability of winter wheat grain yield and soil moisture under limited irrigation.
    Zhang C, Liu J, Shang J, Cai H.
    Sci Total Environ; 2018 Aug 01; 631-632():677-687. PubMed ID: 29539596
    [Abstract] [Full Text] [Related]

  • 5. Deriving a light use efficiency estimation algorithm using in situ hyperspectral and eddy covariance measurements for a maize canopy in Northeast China.
    Zhang F, Zhou G.
    Ecol Evol; 2017 Jul 01; 7(13):4735-4744. PubMed ID: 28690803
    [Abstract] [Full Text] [Related]

  • 6.
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  • 7. [Estimation models for vegetation water content at both leaf and canopy levels].
    Shen Y, Niu Z, Yan C.
    Ying Yong Sheng Tai Xue Bao; 2005 Jul 01; 16(7):1218-23. PubMed ID: 16252855
    [Abstract] [Full Text] [Related]

  • 8. Spatial Variation of Soil Respiration in a Cropland under Winter Wheat and Summer Maize Rotation in the North China Plain.
    Huang N, Wang L, Hu Y, Tian H, Niu Z.
    PLoS One; 2016 Jul 01; 11(12):e0168249. PubMed ID: 27977743
    [Abstract] [Full Text] [Related]

  • 9. [Discussion on hyperspectral index for the estimation of cotton canopy water content].
    Wang Q, Yi QX, Bao AM, Zhao J.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2013 Feb 01; 33(2):507-12. PubMed ID: 23697143
    [Abstract] [Full Text] [Related]

  • 10. Effectiveness of vegetation indices and UAV-multispectral imageries in assessing the response of hybrid maize (Zea mays L.) to water deficit stress under field environment.
    Pipatsitee P, Tisarum R, Taota K, Samphumphuang T, Eiumnoh A, Singh HP, Cha-Um S.
    Environ Monit Assess; 2022 Nov 19; 195(1):128. PubMed ID: 36402920
    [Abstract] [Full Text] [Related]

  • 11. Predicting vegetation water content in wheat using normalized difference water indices derived from ground measurements.
    Wu C, Niu Z, Tang Q, Huang W.
    J Plant Res; 2009 May 19; 122(3):317-26. PubMed ID: 19242776
    [Abstract] [Full Text] [Related]

  • 12. Leaf surface water, not plant water stress, drives diurnal variation in tropical forest canopy water content.
    Xu X, Konings AG, Longo M, Feldman A, Xu L, Saatchi S, Wu D, Wu J, Moorcroft P.
    New Phytol; 2021 Jul 19; 231(1):122-136. PubMed ID: 33539544
    [Abstract] [Full Text] [Related]

  • 13. [Soil moisture estimation method based on both ground-based remote sensing data and air temperature in a summer maize ecosystem.].
    Wang MZ, Zhou GS.
    Ying Yong Sheng Tai Xue Bao; 2016 Jun 19; 27(6):1804-1810. PubMed ID: 29737686
    [Abstract] [Full Text] [Related]

  • 14. Off-Nadir Hyperspectral Sensing for Estimation of Vertical Profile of Leaf Chlorophyll Content within Wheat Canopies.
    Kong W, Huang W, Casa R, Zhou X, Ye H, Dong Y.
    Sensors (Basel); 2017 Nov 23; 17(12):. PubMed ID: 29168757
    [Abstract] [Full Text] [Related]

  • 15. Accurate estimation of sorghum crop water content under different water stress levels using machine learning and hyperspectral data.
    Tunca E, Köksal ES, Öztürk E, Akay H, Çetin Taner S.
    Environ Monit Assess; 2023 Jun 23; 195(7):877. PubMed ID: 37353582
    [Abstract] [Full Text] [Related]

  • 16. Assessing the Spectral Properties of Sunlit and Shaded Components in Rice Canopies with Near-Ground Imaging Spectroscopy Data.
    Zhou K, Deng X, Yao X, Tian Y, Cao W, Zhu Y, Ustin SL, Cheng T.
    Sensors (Basel); 2017 Mar 13; 17(3):. PubMed ID: 28335375
    [Abstract] [Full Text] [Related]

  • 17. Are optical indices good proxies of seasonal changes in carbon fluxes and stress-related physiological status in a beech forest?
    Nestola E, Scartazza A, Di Baccio D, Castagna A, Ranieri A, Cammarano M, Mazzenga F, Matteucci G, Calfapietra C.
    Sci Total Environ; 2018 Jan 15; 612():1030-1041. PubMed ID: 28892844
    [Abstract] [Full Text] [Related]

  • 18. Estimation of leaf water content from hyperspectral data of different plant species by using three new spectral absorption indices.
    Li H, Yang W, Lei J, She J, Zhou X.
    PLoS One; 2021 Jan 15; 16(3):e0249351. PubMed ID: 33784352
    [Abstract] [Full Text] [Related]

  • 19. [Research on maize multispectral image accurate segmentation and chlorophyll index estimation].
    Wu Q, Sun H, Li MZ, Song YY, Zhang YE.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2015 Jan 15; 35(1):178-83. PubMed ID: 25993844
    [Abstract] [Full Text] [Related]

  • 20. [An Analysis of the Spectrums between Different Canopy Structures Based on Hyperion Hyperspectral Data in a Temperate Forest of Northeast China].
    Yu QZ, Wang SQ, Huang K, Zhou L, Chen DC.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2015 Jul 15; 35(7):1980-5. PubMed ID: 26717763
    [Abstract] [Full Text] [Related]

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