A global Canopy Water Content product from AVHRR/Metop
(2020) In ISPRS Journal of Photogrammetry and Remote Sensing 162. p.77-93- Abstract
- Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetationstatus, and constitute essential information for studying ecosystem-climate interactions. Despite many effortsthere is currently no operational CWC product available to users. In the context of the Satellite ApplicationFacility for Land Surface Analysis (LSA-SAF), we have developed an algorithm to produce a global dataset ofCWC based on data from the Advanced Very High Resolution Radiometer (AVHRR) sensor on boardMeteorological–Operational (MetOp) satellites forming the EUMETSAT Polar System (EPS). CWC reflects thewater conditions at the leaf level and information related to canopy structure. An accuracy assessment of theEPS/AVHRR CWC... (More)
- Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetationstatus, and constitute essential information for studying ecosystem-climate interactions. Despite many effortsthere is currently no operational CWC product available to users. In the context of the Satellite ApplicationFacility for Land Surface Analysis (LSA-SAF), we have developed an algorithm to produce a global dataset ofCWC based on data from the Advanced Very High Resolution Radiometer (AVHRR) sensor on boardMeteorological–Operational (MetOp) satellites forming the EUMETSAT Polar System (EPS). CWC reflects thewater conditions at the leaf level and information related to canopy structure. An accuracy assessment of theEPS/AVHRR CWC indicated a close agreement with multi-temporal ground data from SMAPVEX16 in Canadaand Dahra in Senegal, with RMSE of 0.19 kg m−2 and 0.078 kg m−2 respectively. Particularly, when theNormalized Difference Infrared Index (NDII) was included the algorithm was better constrained in semi-aridregions and saturation effects were mitigated in dense canopies. An analysis of spatial scale effects shows themean bias error in CWC retrievals remains below 0.001 kg m−2 when spatial resolutions ranging from 20 m to1 km are considered. The present study further evaluates the consistency of the LSA-SAF product with respect tothe Simplified Level 2 Product Prototype Processor (SL2P) product, and demonstrates its applicability at differentspatio-temporal resolutions using optical data from MSI/Sentinel-2 and MODIS/Terra & Aqua. Resultssuggest that the LSA-SAF EPS/AVHRR algorithm is robust, agrees with the CWC dynamics observed in availableground data, and is also applicable to data from other sensors. We conclude that the EPS/AVHRR CWC product isa promising tool for monitoring vegetation water status at regional and global scales. (Less)
- Abstract (Swedish)
- Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetation
status, and constitute essential information for studying ecosystem-climate interactions. Despite many efforts
there is currently no operational CWC product available to users. In the context of the Satellite Application
Facility for Land Surface Analysis (LSA-SAF), we have developed an algorithm to produce a global dataset of
CWC based on data from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board
Meteorological–Operational (MetOp) satellites forming the EUMETSAT Polar System (EPS). CWC reflects the
water conditions at the leaf level and information related to canopy structure. An accuracy... (More) - Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetation
status, and constitute essential information for studying ecosystem-climate interactions. Despite many efforts
there is currently no operational CWC product available to users. In the context of the Satellite Application
Facility for Land Surface Analysis (LSA-SAF), we have developed an algorithm to produce a global dataset of
CWC based on data from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board
Meteorological–Operational (MetOp) satellites forming the EUMETSAT Polar System (EPS). CWC reflects the
water conditions at the leaf level and information related to canopy structure. An accuracy assessment of the
EPS/AVHRR CWC indicated a close agreement with multi-temporal ground data from SMAPVEX16 in Canada
and Dahra in Senegal, with RMSE of 0.19 kg m−2 and 0.078 kg m−2 respectively. Particularly, when the
Normalized Difference Infrared Index (NDII) was included the algorithm was better constrained in semi-arid
regions and saturation effects were mitigated in dense canopies. An analysis of spatial scale effects shows the
mean bias error in CWC retrievals remains below 0.001 kg m−2 when spatial resolutions ranging from 20 m to
1 km are considered. The present study further evaluates the consistency of the LSA-SAF product with respect to
the Simplified Level 2 Product Prototype Processor (SL2P) product, and demonstrates its applicability at different
spatio-temporal resolutions using optical data from MSI/Sentinel-2 and MODIS/Terra & Aqua. Results
suggest that the LSA-SAF EPS/AVHRR algorithm is robust, agrees with the CWC dynamics observed in available
ground data, and is also applicable to data from other sensors. We conclude that the EPS/AVHRR CWC product is
a promising tool for monitoring vegetation water status at regional and global scales. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/fc26061c-4ad7-462c-aaf5-b4337b47caa4
- author
- publishing date
- 2020-02-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- EUMETSAT Polar System (EPS), AVHRR/MetOp, Canopy Water Content (CWC), Gaussian Process Regression (GPR), Sentinel-2
- in
- ISPRS Journal of Photogrammetry and Remote Sensing
- volume
- 162
- article number
- 10.1016/j.isprsjprs.2020.02.007
- pages
- 17 pages
- publisher
- Elsevier
- external identifiers
-
- scopus:85079655820
- ISSN
- 0924-2716
- DOI
- 10.1016/j.isprsjprs.2020.02.007
- language
- English
- LU publication?
- no
- id
- fc26061c-4ad7-462c-aaf5-b4337b47caa4
- date added to LUP
- 2020-11-03 13:46:02
- date last changed
- 2022-04-19 01:32:06
@article{fc26061c-4ad7-462c-aaf5-b4337b47caa4,
abstract = {{Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetationstatus, and constitute essential information for studying ecosystem-climate interactions. Despite many effortsthere is currently no operational CWC product available to users. In the context of the Satellite ApplicationFacility for Land Surface Analysis (LSA-SAF), we have developed an algorithm to produce a global dataset ofCWC based on data from the Advanced Very High Resolution Radiometer (AVHRR) sensor on boardMeteorological–Operational (MetOp) satellites forming the EUMETSAT Polar System (EPS). CWC reflects thewater conditions at the leaf level and information related to canopy structure. An accuracy assessment of theEPS/AVHRR CWC indicated a close agreement with multi-temporal ground data from SMAPVEX16 in Canadaand Dahra in Senegal, with RMSE of 0.19 kg m−2 and 0.078 kg m−2 respectively. Particularly, when theNormalized Difference Infrared Index (NDII) was included the algorithm was better constrained in semi-aridregions and saturation effects were mitigated in dense canopies. An analysis of spatial scale effects shows themean bias error in CWC retrievals remains below 0.001 kg m−2 when spatial resolutions ranging from 20 m to1 km are considered. The present study further evaluates the consistency of the LSA-SAF product with respect tothe Simplified Level 2 Product Prototype Processor (SL2P) product, and demonstrates its applicability at differentspatio-temporal resolutions using optical data from MSI/Sentinel-2 and MODIS/Terra & Aqua. Resultssuggest that the LSA-SAF EPS/AVHRR algorithm is robust, agrees with the CWC dynamics observed in availableground data, and is also applicable to data from other sensors. We conclude that the EPS/AVHRR CWC product isa promising tool for monitoring vegetation water status at regional and global scales.}},
author = {{García-Haro, Francisco Javier and Campos-Taberner, Manuel and Moreno, Álvaro and Tagesson, Torbern and Camacho, Fernando and Martínez, Beatriz and Sánchez, Sergio and Piles, María and Camps-Valls, Gustau and Yebra, Marta and Amparo Gilabert, María}},
issn = {{0924-2716}},
keywords = {{EUMETSAT Polar System (EPS); AVHRR/MetOp; Canopy Water Content (CWC); Gaussian Process Regression (GPR); Sentinel-2}},
language = {{eng}},
month = {{02}},
pages = {{77--93}},
publisher = {{Elsevier}},
series = {{ISPRS Journal of Photogrammetry and Remote Sensing}},
title = {{A global Canopy Water Content product from AVHRR/Metop}},
url = {{http://dx.doi.org/10.1016/j.isprsjprs.2020.02.007}},
doi = {{10.1016/j.isprsjprs.2020.02.007}},
volume = {{162}},
year = {{2020}},
}