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First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems

Author:
  • A. M. Abdi
  • N. Boke-Olén
  • H. Jin
  • L. Eklundh
  • T. Tagesson
  • V. Lehsten
  • J. Ardö
Publishing year: 2019
Language: English
Pages: 249-260
Publication/Series: International Journal of Applied Earth Observation and Geoinformation
Volume: 78
Document type: Journal article
Publisher: Elsevier

Abstract english


The importance of semi-arid ecosystems in the global carbon cycle as sinks for CO
2
emissions has recently been highlighted. Africa is a carbon sink and nearly half its area comprises arid and semi-arid ecosystems. However, there are uncertainties regarding CO
2
fluxes for semi-arid ecosystems in Africa, particularly savannas and dry tropical woodlands. In order to improve on existing remote-sensing based methods for estimating carbon uptake across semi-arid Africa we applied and tested the recently developed plant phenology index (PPI). We developed a PPI-based model estimating gross primary productivity (GPP) that accounts for canopy water stress, and compared it against three other Earth observation-based GPP models: the temperature and greenness (T-G) model, the greenness and radiation (GöR) model and a light use efficiency model (MOD17). The models were evaluated against in situ data from four semi-arid sites in Africa with varying tree canopy cover (3–65%). Evaluation results from the four GPP models showed reasonable agreement with in situ GPP measured from eddy covariance flux towers (EC GPP) based on coefficient of variation (R
2
), root-mean-square error (RMSE), and Bayesian information criterion (BIC). The GöR model produced R
2
= 0.73, RMSE = 1.45 g C m
−2
d
−1
, and BIC = 678; the T-G model produced R
2
= 0.68, RMSE = 1.57 g C m
−2
d
−1
, and BIC = 707; the MOD17 model produced R
2
= 0.49, RMSE = 1.98 g C m
−2
d
−1
, and BIC = 800. The PPI-based GPP model was able to capture the magnitude of EC GPP better than the other tested models (R
2
= 0.77, RMSE = 1.32 g C m
−2
d
−1
, and BIC = 631). These results show that a PPI-based GPP model is a promising tool for the estimation of GPP in the semi-arid ecosystems of Africa.

Keywords

  • Physical Geography
  • Drylands
  • Eddy covariance
  • FLUXNET
  • GPP
  • Gross primary productivity
  • Land surface temperature
  • LST
  • MODIS
  • Plant phenology index
  • PPI
  • Semi-arid
  • Vapor pressure deficit
  • VPD

Other

Published
  • Global Savannah Phenology: Integrating Earth Observation, Ecosystem Modeling, and PhenoCams
  • ISSN: 1569-8432
E-mail: jonas [dot] ardo [at] nateko [dot] lu [dot] se

Professor

Dept of Physical Geography and Ecosystem Science

+46 46 222 40 31

369

16

Teaching staff

Dept of Physical Geography and Ecosystem Science

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Department of Physical Geography and Ecosystem Science
Lund University
Sölvegatan 12
S-223 62 Lund
Sweden

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