Assimilation of satellite observations for the estimation of Savanna gross primary production
Meroni, Michele ; Rembold, Felix ; Migliavacca, Mirco and Ardö, Jonas LU
(2015)
IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
p.3416-3418
- Abstract
Monitoring vegetation gross primary production (GPP) is required for both carbon balance studies and early warning systems aiming to detect unfavorable crop and pasture conditions. This manuscript describes the assimilation of MODIS observations by a simple process model, fed by meteorological data (temperature, incident radiation and rainfall) and linked with a canopy reflectance model, to estimate GPP. GPP simulations are benchmarked against eddy covariance data collected in a semi-arid environment of a sparse Savanna in the Sudan.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3c4111d7-a63f-4831-b267-61da310e7c29
- author
- Meroni, Michele
; Rembold, Felix
; Migliavacca, Mirco
and Ardö, Jonas
LU
- organization
- publishing date
- 2015-11-10
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- assimilation, GPP, MODIS, process model, radiative transfer
- host publication
- 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
- article number
- 7326553
- pages
- 3 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
- conference location
- Milan, Italy
- conference dates
- 2015-07-26 - 2015-07-31
- external identifiers
-
- scopus:84962556180
- ISBN
- 9781479979295
- DOI
- 10.1109/IGARSS.2015.7326553
- language
- English
- LU publication?
- yes
- id
- 3c4111d7-a63f-4831-b267-61da310e7c29
- date added to LUP
- 2016-09-22 12:58:43
- date last changed
- 2022-01-30 06:13:39
@inproceedings{3c4111d7-a63f-4831-b267-61da310e7c29,
abstract = {{<p>Monitoring vegetation gross primary production (GPP) is required for both carbon balance studies and early warning systems aiming to detect unfavorable crop and pasture conditions. This manuscript describes the assimilation of MODIS observations by a simple process model, fed by meteorological data (temperature, incident radiation and rainfall) and linked with a canopy reflectance model, to estimate GPP. GPP simulations are benchmarked against eddy covariance data collected in a semi-arid environment of a sparse Savanna in the Sudan.</p>}},
author = {{Meroni, Michele and Rembold, Felix and Migliavacca, Mirco and Ardö, Jonas}},
booktitle = {{2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings}},
isbn = {{9781479979295}},
keywords = {{assimilation; GPP; MODIS; process model; radiative transfer}},
language = {{eng}},
month = {{11}},
pages = {{3416--3418}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Assimilation of satellite observations for the estimation of Savanna gross primary production}},
url = {{http://dx.doi.org/10.1109/IGARSS.2015.7326553}},
doi = {{10.1109/IGARSS.2015.7326553}},
year = {{2015}},
}