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Disambiguation of "Zarco-Tejada, Pablo J"

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PROSPECT+ SAIL models: A review of use for vegetation characterization

, , , , , , , and . Remote Sensing of Environment, (2009)
DOI: 10.1016/j.rse.2008.01.026

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Pablo J Sanz Miguel

Amelia Tejada

Pablo Robert

Pablo Lorenzano

Pablo Zamora

 

Other publications of authors with the same name

PROSPECT+ SAIL models: A review of use for vegetation characterization, , , , , , , and . Remote Sensing of Environment, (2009)Residual Effect and N Fertilizer Rate Detection by High-Resolution VNIR-SWIR Hyperspectral Imagery and Solar-Induced Chlorophyll Fluorescence in Wheat., , , , , , and . IEEE Trans. Geosci. Remote. Sens., (2022)Assessment of Satellite Chlorophyll-Based Leaf Maximum Carboxylation Rate (Vcmax) Using Flux Observations at Crop and Grass Sites., , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2021)Evaluating the Relative Contribution of Photosystems I and II for Leaf Nitrogen Estimation Using Fractional Depth of Fraunhofer Lines and SIF Derived From Sub-Nanometer Airborne Hyperspectral Imagery., , , and . IGARSS, page 2819-2822. IEEE, (2023)Progress on the development of an integrated canopy fluorescence model., , , , , , , , , and 3 other author(s). IGARSS, page 601-603. IEEE, (2003)Needle chlorophyll content estimation: a comparative study of PROSPECT and LIBERTY., , , and . IGARSS, page 1676-1678. IEEE, (2003)Extracting tree crown properties from ground-based scanning laser data., , , , and . IGARSS, page 2830-2832. IEEE, (2007)Deriving Predictive Relationships of Carotenoid Content at the Canopy Level in a Conifer Forest Using Hyperspectral Imagery and Model Simulation., , and . IEEE Trans. Geosci. Remote. Sens., 52 (8): 5206-5217 (2014)Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data., , , , and . IEEE Trans. Geosci. Remote. Sens., 39 (7): 1491-1507 (2001)Unmixing-Based Fusion of Hyperspatial and Hyperspectral Airborne Imagery for Early Detection of Vegetation Stress., , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 7 (6): 2571-2582 (2014)