Pablo Jesús Zarco Tejada

Hyperspectral and thermal remote sensing for vegetation stress detection

Within the field of remote sensing, I work on the simulation and validation of algorithms for the detection of stress in vegetation from the estimation of biophysical parameters and biochemical constituents in vegetation using hyperspectral and thermal sensors. My work is based on the development and use of physical models of radiative transfer that simulate heterogeneous canopies, studying the effect of bi-directional reflectance on narrow band indices used for the detection of water and nutritional (abiotic) and disease (biotic) stress. My work on predictive stress indicators, such as chlorophyll fluorescence, photochemical indices related to the degradation of photosynthetic pigments, such as xanthophylls, and temperature estimation, allow early detection of stress in vegetation from manned vehicles (AHS sensors, CASI, AVIRIS) and unmanned platforms (UAVs/UAS/RPAS).

E-mail: pablo.zarco@csic.es
http://quantalab.ias.csic.es
IAS annex building – Office 1 first floor
Telephone: 957 49 92 80

Outstanding contributions

Mohammed, G.H.; Colombo, R.; Middleton, E.M.; Rascher, U.; van der Tol, C.; Nedbal, L.; Goulas, Y.; Pérez-Priego, O.; Damm, A.; Meroni, M.; Joiner, J.Cogliati, S.; Verhoef, W.; Malenovský, Z.; Gastellu-Etchegorry, J.P.; Miller, J.R.; Guanter, L.; Moreno, J.; Moya, I.; Berry, J.A.; Frankenberg, C.; Zarco-Tejada, P.J. 2019. Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress. Remote Sensing of Environment, 231: 111177.
Poblete, T.; Camino, C.; Beck, P.S.A.; Hornero, A.; Kattenborn, T.; Saponari, M.; Boscia, D.; Navas?Cortes, J.A.; Zarco-Tejada, P.J. 2020. Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis. ISPRS Journal of Photogrammetry and Remote Sensing, 162: 27 – 40
Jin, X., Zarco-Tejada, P.J., Schmidhalter, U., Reynolds, M.P., Hawkesford, M., Varshney, R.K., Yang, T., Nie, C., Li, Z., Ming, B., Xiao, Y., Xie, Y., Li, S. 2020. A review of high-throughput estimation of crop traits using ground and aerial phenotyping platforms, IEEE Geoscience and Remote Sensing Magazine.