Jorge Sánchez-Zapero

Dr. Jorge Sánchez-Zapero

Earth Observation Laboratory (EOLAB)
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 March 2020 in Remote Sensing
Verified
Journal Article
Open access
PDF file
BOBeatriz Fuster Ochando
Beatriz Fuster Ochando
Jorge Sánchez-ZaperoJorge Sánchez-Zapero
Jorge Sánchez-Zapero
Fernando Camacho De CocaFernando Camacho De Coca
Fernando Camacho De Coca
VSVicente Santos
Vicente Santos
Aleixandre VergerAleixandre Verger
Aleixandre Verger
BSBruno Smets
Bruno Smets
The Copernicus Global Land Service (CGLS) provides global time series of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fAPAR) and fraction of vegetation cover (fCOVER) data at a resolution of 300 m and a frequency of 10 days. We performed a quality assessment and validation of Version 1 Collection 300 m products that were consistent with the guidelines of the Land Product Validation (LPV) subgroup of the Committee on Earth Observation System (CEOS) Working Group on Calibration and Validation (WGCV). The spatiotemporal patterns of Collection 300 m V1 LAI, fAPAR and fCOVER products are consistent with CGLS Collection 1 km V1, Collection 1 km V2 and Moderate Resolution Imagery Spectroradiometer Collection 6 (MODIS C6) products. The Collection 300 m V1 products have good precision and smooth temporal profiles, and the interannual variations are consistent with similar satellite products. The accuracy assessment using ground measurements mainly over crops shows an overall root mean square deviation of 1.01 (44.3%) for LAI, 0.12 (22.2%) for fAPAR and 0.21 (42.6%) for fCOVER, with positive mean biases of 0.36 (15.5%), 0.05 (10.3%) and 0.16 (32.2%), respectively. The products meet the CGLS user accuracy requirements in 69.1%, 62.5% and 29.7% of the cases for LAI, fAPAR and fCOVER, respectively. The CGLS will continue the production of Collection 300 m V1 LAI, fAPAR and fCOVER beyond the end of the PROBA-V mission by using Sentinel-3 OLCI as input data.

1 May 2018 in ISPRS Journal of Photogrammetry and Remote Sensing
Verified
Journal Article
Closed access
F. Javier Garcia HaroF. Javier Garcia Haro
F. Javier Garcia Haro
Manuel Campos-TabernerManuel Campos-Taberner
Manuel Campos-Taberner
JMJordi Muñoz-Marí
Jordi Muñoz-Marí
VLValero Laparra
Valero Laparra
FCFernando Camacho
Fernando Camacho
GCGustau Camps-Valls
Gustau Camps-Valls

12 August 2021 in Remote Sensing
Verified
Journal Article
Open access
PDF file
LBLuke Brown
Luke Brown
Fernando Camacho De CocaFernando Camacho De Coca
Fernando Camacho De Coca
Vicente Garcia-SantosVicente Garcia-Santos
Vicente Garcia-Santos
NONiall Origo
Niall Origo
BOBeatriz Fuster Ochando
Beatriz Fuster Ochando
Jadunandan DashJadunandan Dash
Jadunandan Dash
With a wide range of satellite-derived vegetation bio-geophysical products now available to users, validation efforts are required to assess their accuracy and fitness for purpose. Substantial progress in the validation of such products has been made over the last two decades, but quantification of the uncertainties associated with in situ reference measurements is rarely performed, and the incorporation of uncertainties within upscaling procedures is cursory at best. Since current validation practices assume that reference data represent the truth, our ability to reliably demonstrate compliance with product uncertainty requirements through conformity testing is limited. The Fiducial Reference Measurements for Vegetation (FRM4VEG) project, initiated by the European Space Agency, is aiming to address this challenge by applying metrological principles to vegetation and surface reflectance product validation. Following FRM principles, and in accordance with the International Standards Organisation’s (ISO) Guide to the Expression of Uncertainty in Measurement (GUM), for the first time, we describe an end-to-end uncertainty evaluation framework for reference data of two key vegetation bio-geophysical variables: the fraction of absorbed photosynthetically active radiation (FAPAR) and canopy chlorophyll content (CCC). The process involves quantifying the uncertainties associated with individual in situ reference measurements and incorporating these uncertainties within the upscaling procedure (as well as those associated with the high-spatial-resolution imagery used for upscaling). The framework was demonstrated in two field campaigns covering agricultural crops (Las Tiesas–Barrax, Spain) and deciduous broadleaf forest (Wytham Woods, UK). Providing high-spatial-resolution reference maps with per-pixel uncertainty estimates, the framework is applicable to a range of other bio-geophysical variables including leaf area index (LAI), the fraction of vegetation cover (FCOVER), and canopy water content (CWC). The proposed procedures will facilitate conformity testing of moderate spatial resolution vegetation bio-geophysical products in future validation exercises.

9 September 2023 in International Journal of Applied Earth Observation and Geoinformation
Verified
Journal Article
Open access
Aleixandre VergerAleixandre Verger
Aleixandre Verger
Jorge Sánchez-ZaperoJorge Sánchez-Zapero
Jorge Sánchez-Zapero
MWMarie Weiss
Marie Weiss
ADAdrià Descals
Adrià Descals
FCFernando Camacho
Fernando Camacho
FBFred Baret
Fred Baret

1 September 2018 in Remote Sensing of Environment
Verified
Journal Article
Open access
Jean-Louis RoujeanJean-Louis Roujean
Jean-Louis Roujean
JLJonathan Leon-Tavares
Jonathan Leon-Tavares
BSBruno Smets
Bruno Smets
PCPatrick Claes
Patrick Claes
FCFernando Camacho De Coca
Fernando Camacho De Coca
Jorge Sánchez-ZaperoJorge Sánchez-Zapero
Jorge Sánchez-Zapero

9 September 2019 in Remote Sensing
Verified
Journal Article
Open access
PDF file
F. Javier Garcia HaroF. Javier Garcia Haro
F. Javier Garcia Haro
Fernando Camacho De CocaFernando Camacho De Coca
Fernando Camacho De Coca
BMBeatriz Martinez
Beatriz Martinez
Manuel Campos-TabernerManuel Campos-Taberner
Manuel Campos-Taberner
BOBeatriz Fuster Ochando
Beatriz Fuster Ochando
MGMaría Amparo Gilabert
María Amparo Gilabert
The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed by vegetation (FAPAR) and the fractional vegetation cover (FVC), for the whole Meteosat disk at two temporal frequencies, daily and 10-days. The FVC algorithm relies on a novel stochastic spectral mixture model which addresses the variability of soils and vegetation types using statistical distributions whereas the LAI and FAPAR algorithms use statistical relationships general enough for global applications. An overview of the LSA SAF SEVIRI/MSG vegetation products, including expert knowledge and quality assessment of its internal consistency is provided. The climate data record (CDR) is freely available in the LSA SAF, offering more than fifteen years (2004-present) of homogeneous time series required for climate and environmental applications. The high frequency and good temporal continuity of SEVIRI products addresses the needs of near-real-time users and are also suitable for long-term monitoring of land surface variables. The study also evaluates the potential of the SEVIRI/MSG vegetation products for environmental applications, spanning from accurate monitoring of vegetation cycles to resolving long-term changes of vegetation.