
David Tenenbaum
Professor

Evaluating Water Controls on Vegetation Growth in the Semi-Arid Sahel Using Field and Earth Observation Data
Författare
Summary, in English
Water loss is a crucial factor for vegetation in the semi-arid Sahel region of Africa. Global satellite-driven estimates of plant CO2 uptake (gross primary productivity, GPP) have been found to not accurately account for Sahelian conditions, particularly the impact of canopy water stress. Here, we identify the main biophysical limitations that induce canopy water stress in Sahelian vegetation and evaluate the relationships between field data and Earth observation-derived spectral products for up-scaling GPP. We find that plant-available water and vapor pressure deficit together control the GPP of Sahelian vegetation through their impact on the greening and browning phases. Our results show that a multiple linear regression (MLR) GPP model that combines the enhanced vegetation index, land surface temperature, and the short-wave infrared reflectance (Band 7, 2105–2155 nm) of the moderate-resolution imaging spectroradiometer satellite sensor was able to explain between 88% and 96% of the variability of eddy covariance flux tower GPP at three Sahelian sites (overall = 89%). The MLR GPP model presented here is potentially scalable at a relatively high spatial and temporal resolution. Given the scarcity of field data on CO2 fluxes in the Sahel, this scalability is important due to the low number of flux towers in the region.
Avdelning/ar
- Institutionen för naturgeografi och ekosystemvetenskap
- BECC: Biodiversity and Ecosystem services in a Changing Climate
Publiceringsår
2017-03-21
Språk
Engelska
Publikation/Tidskrift/Serie
Remote Sensing
Volym
9
Issue
3
Fulltext
Dokumenttyp
Artikel i tidskrift
Förlag
MDPI AG
Ämne
- Physical Geography
- Environmental Sciences
- Ecology
- Remote Sensing
Nyckelord
- Sahel
- Drought
- Africa
- Earth observation
- Plant available water
- Soil moisture
- Vapor pressure deficit
- Plant stress
- Remote sensing
- Ecosystem ecology
Aktiv
Published
ISBN/ISSN/Övrigt
- ISSN: 2072-4292