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.
Original language | English |
---|---|
Title of host publication | 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings |
Publisher | IEEE - Institute of Electrical and Electronics Engineers Inc. |
Pages | 3416-3418 |
Number of pages | 3 |
ISBN (Electronic) | 9781479979295 |
DOIs | |
Publication status | Published - 2015 Nov 10 |
Event | IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Milan, Italy Duration: 2015 Jul 26 → 2015 Jul 31 |
Conference
Conference | IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 |
---|---|
Country/Territory | Italy |
City | Milan |
Period | 2015/07/26 → 2015/07/31 |
Subject classification (UKÄ)
- Physical Geography
Free keywords
- assimilation
- GPP
- MODIS
- process model
- radiative transfer