Pablo Zarco-Tejada

Prediction of the severity of Dothistroma needle blight in radiata pine using plant based traits and narrow band indices derived from UAV hyperspectral imagery

MS Watt, T Poblete, D de Silva, HJC Estarija, RJL Hartley, EMC Leonardo, P Massam, H Buddenbaum, PJ Zarco-Tejada

Journal article  |  2023  |  Agricultural and Forest Meteorology

Dothistroma needle blight, caused by the fungi Dothistroma septosporum and D. pini is globally one of the most damaging diseases o..

Recent research accomplishments on early detection of Xylella fastidiosa outbreaks in the Mediterranean Basin

María P VELASCO-AMO, Antonio VICENT, Pablo J ZARCO-TEJADA, Juan A NAVAS-CORTÉS, Blanca B LANDA

Journal article  |  2023  |  Phytopathologia Mediterranea

Xylella fastidiosa is a major transboundary plant pest, causing severe socioeconomic impacts. Development of preventive strategies..

Airborne hyperspectral and Sentinel imagery to quantify winter wheat traits through ensemble modeling approaches

JL Pancorbo, M Alonso-Ayuso, C Camino, MD Raya-Sereno, PJ Zarco-Tejada, I Molina, JL Gabriel, M Quemada

Journal article  |  2023  |  Precision Agriculture

Early prediction of crop production by remote sensing (RS) may help to plan the harvest and ensure food security. This study aims ..

Assessment of crop traits retrieved from airborne hyperspectral and thermal remote sensing imagery to predict wheat grain protein content

AR Longmire, T Poblete, JR Hunt, D Chen, PJ Zarco-Tejada

Journal article  |  2022  |  ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Wheat (Triticum spp.) is among the world's most widely grown crops and receives large quantities of nitrogen (N) fertiliser. Grain..

Evaluating the role of solar-induced fluorescence (SIF) and plant physiological traits for leaf nitrogen assessment in almond using airborne hyperspectral imagery

Y Wang, L Suarez, T Poblete, V Gonzalez-Dugo, D Ryu, PJ Zarco-Tejada

Journal article  |  2022  |  REMOTE SENSING OF ENVIRONMENT

Accurate, spatially extensive, and frequent assessments of plant nitrogen (N) enabled by remote sensing allow growers to optimize ..

Assessment of peach trees water status and leaf gas exchange using on-the-ground versus airborne-based thermal imagery

JM Ramírez-Cuesta, MF Ortuño, V Gonzalez-Dugo, PJ Zarco-Tejada, M Parra, JS Rubio-Asensio, DS Intrigliolo

Journal article  |  2022  |  Agricultural Water Management

The thermal region of the electromagnetic spectrum might provide valuable information for assessing plant water status. Neverthele..

Assessment of canopy transpiration from temperature: application to almond orchards

V Gonzalez-Dugo, D Moldero, M Espadafor, F Orgaz, L Testi, PJ Zarco-Tejada, IJ Lorite, E Fereres

Journal article  |  2022  |  Acta Horticulturae

Cultivated area with irrigated almond is increasing throughout the Mediterranean area, and especially in Spain, because of the hig..

Evaluation of SIF retrievals from narrow-band and sub-nanometer airborne hyperspectral imagers flown in tandem: Modelling and validation in the context of plant phenotyping

A Belwalkar, T Poblete, A Longmire, A Hornero, R Hernandez-Clemente, PJ Zarco-Tejada

Journal article  |  2022  |  REMOTE SENSING OF ENVIRONMENT

Solar-induced chlorophyll fluorescence (SIF) can be used as an indicator of crop photosynthetic activity and a proxy for vegetatio..

Accounting for the Spectral Resolution on Sif Retrieval From a Narrow-Band Airborne Imager Using Scope

A Belwalkar, T Poblete, A Hornero, PJ Zarco-Tejada

Conference Proceedings  |  2022  |  International Geoscience and Remote Sensing Symposium (IGARSS)

Sub-nanometer hyperspectral imagers are increasingly being used to quantify solar-induced chlorophyll fluorescence (SIF) due to th..

Leaf Nitrogen Assessment with ISS DESIS Imaging Spectrometer as Compared to High-Resolution Airborne Hyperspectral Imagery

Y Wang, L Suarez, V Gonzalez-Dugo, D Ryu, P Moar, PJ Zarco-Tejada

Conference Proceedings  |  2022  |  International Geoscience and Remote Sensing Symposium (IGARSS)

Traditional methods to estimate leaf nitrogen (N) from satellite imagery rely on structural and chlorophyll a+b,(mathrm{C}-{text{a..