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Improvement of the GPP estimations for Sudan using the evaporative fraction as water stress factor

Dissegna, Maria Angela LU (2016) In Lund University GEM thesis series NGEM01 20161
Dept of Physical Geography and Ecosystem Science
Abstract
Estimation of GPP in Sudan using the evaporative fraction as water stress factor

The Gross Primary Production "GPP" quantifies the amount of carbon entering an ecosystem. It is an ecosystem service since it is a source of energy for all organisms and it is estimated to reduce atmospheric CO2 in about 123 Pg C per year at the global scale. Therefore, the improvement of estimation methods at large spatial scales using tools such as remote sensing has gain relevance in the last years.
The study evaluates two approaches of a Light Use Efficiency model with the aim to improve existing estimations of GPP in semi-arid areas. The tested inputs were the Fraction of Absorbed Photosynthetically Active Radiation "FAPAR" and the Enhanced Vegetation... (More)
Estimation of GPP in Sudan using the evaporative fraction as water stress factor

The Gross Primary Production "GPP" quantifies the amount of carbon entering an ecosystem. It is an ecosystem service since it is a source of energy for all organisms and it is estimated to reduce atmospheric CO2 in about 123 Pg C per year at the global scale. Therefore, the improvement of estimation methods at large spatial scales using tools such as remote sensing has gain relevance in the last years.
The study evaluates two approaches of a Light Use Efficiency model with the aim to improve existing estimations of GPP in semi-arid areas. The tested inputs were the Fraction of Absorbed Photosynthetically Active Radiation "FAPAR" and the Enhanced Vegetation Index "EVI" used to represent the existent vegetation; coupled with the Evaporative Fraction as a term to represent moisture availability. The two approaches were tested trough a site level comparison between the GPP estimated from the records of the Eddy covariance flux tower located in Demokeya site in Sudan and the MODIS GPP product MOD17A2.
Results
The results show that the inclusion of the Evaporative Fraction increased the accuracy of the GPP estimations in the two approaches during the dry seasons but it underestimates of GPP during the rainy seasons. Both approaches performed significantly better compared to the existing MODIS GPP estimations (MOD17A2) and overall the use of FAPAR performed better than EVI for the case of Demokeya site. (Less)
Popular Abstract
Estimation of GPP in Sudan using the evaporative fraction as water stress factor

The Gross Primary Production "GPP" quantifies the amount of carbon entering an ecosystem. It is an ecosystem service since it is a source of energy for all organisms and it is estimated to reduce atmospheric CO2 in about 123 Pg C per year at the global scale. Therefore, the improvement of estimation methods at large spatial scales using tools such as remote sensing has gain relevance in the last years.

The study tested few models against in situ measurements with the aim to improve the existent estimations of GPP in semi arid regions. The main approach was to include the Evaporative Fraction "EF" as a limiting factor since it can be used to represent... (More)
Estimation of GPP in Sudan using the evaporative fraction as water stress factor

The Gross Primary Production "GPP" quantifies the amount of carbon entering an ecosystem. It is an ecosystem service since it is a source of energy for all organisms and it is estimated to reduce atmospheric CO2 in about 123 Pg C per year at the global scale. Therefore, the improvement of estimation methods at large spatial scales using tools such as remote sensing has gain relevance in the last years.

The study tested few models against in situ measurements with the aim to improve the existent estimations of GPP in semi arid regions. The main approach was to include the Evaporative Fraction "EF" as a limiting factor since it can be used to represent moisture availability for plants.
Results
The inclusion of EF in the models has proven to increase the accuracy of the GPP estimations during the dry seasons but also has lead to an underestimation during the rainy seasons. Nevertheless, the results obtained were more accurate than the NASA estimates GPP product. (Less)
Please use this url to cite or link to this publication:
author
Dissegna, Maria Angela LU
supervisor
organization
course
NGEM01 20161
year
type
H2 - Master's Degree (Two Years)
subject
keywords
semi-arid regions, light use efficiency models, evaporative fraction, gross primary production, Physical Geography and Ecosystem analysis, GEM
publication/series
Lund University GEM thesis series
report number
17
funder
CONACYT, National Council of Science and Technology of Mexico
language
English
id
8890789
date added to LUP
2016-09-07 08:49:00
date last changed
2016-09-07 16:12:31
@misc{8890789,
  abstract     = {{Estimation of GPP in Sudan using the evaporative fraction as water stress factor

The Gross Primary Production "GPP" quantifies the amount of carbon entering an ecosystem. It is an ecosystem service since it is a source of energy for all organisms and it is estimated to reduce atmospheric CO2 in about 123 Pg C per year at the global scale. Therefore, the improvement of estimation methods at large spatial scales using tools such as remote sensing has gain relevance in the last years.
The study evaluates two approaches of a Light Use Efficiency model with the aim to improve existing estimations of GPP in semi-arid areas. The tested inputs were the Fraction of Absorbed Photosynthetically Active Radiation "FAPAR" and the Enhanced Vegetation Index "EVI" used to represent the existent vegetation; coupled with the Evaporative Fraction as a term to represent moisture availability. The two approaches were tested trough a site level comparison between the GPP estimated from the records of the Eddy covariance flux tower located in Demokeya site in Sudan and the MODIS GPP product MOD17A2.
Results
The results show that the inclusion of the Evaporative Fraction increased the accuracy of the GPP estimations in the two approaches during the dry seasons but it underestimates of GPP during the rainy seasons. Both approaches performed significantly better compared to the existing MODIS GPP estimations (MOD17A2) and overall the use of FAPAR performed better than EVI for the case of Demokeya site.}},
  author       = {{Dissegna, Maria Angela}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Lund University GEM thesis series}},
  title        = {{Improvement of the GPP estimations for Sudan using the evaporative fraction as water stress factor}},
  year         = {{2016}},
}