Advanced

Assessing vegetation changes for parts of the Sudan and Chad during 2000-2010 using time series analysis of MODIS-NDVI

Ghezahai, Salem Beyene (2011) In Lunds universitets Naturgeografiska institution - Seminarieuppsatser
Dept of Physical Geography and Ecosystem Science
Abstract
Phenological vegetation characteristics are valuable inputs to several ecosystem-related
models: including carbon exchange and climate change. Phenological characteristics are
effective measures of changes in vegetation in an area and are subject to the seasonal and
inter-annual climatic variations. In arid and semi-arid ecosystems, precipitation is the main
driving factor for changes in vegetation and phenological parameters. In this regard, remotely
sensed vegetation indices are widely used. In the current study, time series of 16-day
composite normalized difference vegetation index (NDVI) images from Moderate Resolution
Imaging Spectroradiometer (MODIS) were analyzed to assess vegetation changes for parts of
the Sudan and Chad... (More)
Phenological vegetation characteristics are valuable inputs to several ecosystem-related
models: including carbon exchange and climate change. Phenological characteristics are
effective measures of changes in vegetation in an area and are subject to the seasonal and
inter-annual climatic variations. In arid and semi-arid ecosystems, precipitation is the main
driving factor for changes in vegetation and phenological parameters. In this regard, remotely
sensed vegetation indices are widely used. In the current study, time series of 16-day
composite normalized difference vegetation index (NDVI) images from Moderate Resolution
Imaging Spectroradiometer (MODIS) were analyzed to assess vegetation changes for parts of
the Sudan and Chad (between 10o-20o Northern latitude and 23o-35o Eastern longitude)
during 2000-2010. Spatial and temporal variation in NDVI and phenological (seasonality)
parameters were assessed for the land cover classes shrubland, grassland, cropland and
savanna. Mathematical models from TIMESAT, a program package developed for extracting
seasonality parameters from a series of data captured using remote sensing techniques over
time, were implemented to suppress the noisy patterns in NDVI and to extract phenological
parameters. The observed changes were then explained by looking at the amount of rainfall.
Even though the results cannot be generalized, majority of the cases depict an increase in the
fitted NDVI, delay on the start and end of the growing seasons, shortening of growing season
length, decrease in amplitude and integrals. However, statistical test outputs were not
significant for most of the cases. This could be due to the effect of small sample sizes, which
increase the likelihood of obtaining erroneous results and further inspection is recommended.
In general, high temporal and spatial variations were evident. The temporal variation could
mainly be attributed to the erratic nature of the rainfall. The spatial variation is also a factor
of the strong north-south rainfall diversity. Even so, the results depict that rainfall amount
only cannot explain the observed changes. (Less)
Please use this url to cite or link to this publication:
author
Ghezahai, Salem Beyene
supervisor
organization
year
type
H2 - Master's Degree (Two Years)
subject
keywords
geography, physical geography, NDVI, MODIS, TIMESAT, time series, land cover, temporal variation, spatial variation, rainfall, phenological parameters, vegetation
publication/series
Lunds universitets Naturgeografiska institution - Seminarieuppsatser
report number
221
language
English
id
2158922
date added to LUP
2012-03-20 10:53:09
date last changed
2012-03-20 10:53:09
@misc{2158922,
  abstract     = {Phenological vegetation characteristics are valuable inputs to several ecosystem-related
models: including carbon exchange and climate change. Phenological characteristics are
effective measures of changes in vegetation in an area and are subject to the seasonal and
inter-annual climatic variations. In arid and semi-arid ecosystems, precipitation is the main
driving factor for changes in vegetation and phenological parameters. In this regard, remotely
sensed vegetation indices are widely used. In the current study, time series of 16-day
composite normalized difference vegetation index (NDVI) images from Moderate Resolution
Imaging Spectroradiometer (MODIS) were analyzed to assess vegetation changes for parts of
the Sudan and Chad (between 10o-20o Northern latitude and 23o-35o Eastern longitude)
during 2000-2010. Spatial and temporal variation in NDVI and phenological (seasonality)
parameters were assessed for the land cover classes shrubland, grassland, cropland and
savanna. Mathematical models from TIMESAT, a program package developed for extracting
seasonality parameters from a series of data captured using remote sensing techniques over
time, were implemented to suppress the noisy patterns in NDVI and to extract phenological
parameters. The observed changes were then explained by looking at the amount of rainfall.
Even though the results cannot be generalized, majority of the cases depict an increase in the
fitted NDVI, delay on the start and end of the growing seasons, shortening of growing season
length, decrease in amplitude and integrals. However, statistical test outputs were not
significant for most of the cases. This could be due to the effect of small sample sizes, which
increase the likelihood of obtaining erroneous results and further inspection is recommended.
In general, high temporal and spatial variations were evident. The temporal variation could
mainly be attributed to the erratic nature of the rainfall. The spatial variation is also a factor
of the strong north-south rainfall diversity. Even so, the results depict that rainfall amount
only cannot explain the observed changes.},
  author       = {Ghezahai, Salem Beyene},
  keyword      = {geography,physical geography,NDVI,MODIS,TIMESAT,time series,land cover,temporal variation,spatial variation,rainfall,phenological parameters,vegetation},
  language     = {eng},
  note         = {Student Paper},
  series       = {Lunds universitets Naturgeografiska institution - Seminarieuppsatser},
  title        = {Assessing vegetation changes for parts of the Sudan and Chad during 2000-2010 using time series analysis of MODIS-NDVI},
  year         = {2011},
}