Classification of vegetation type in Iraq using satellite-based phenological parameters
Classification of vegetation type in Iraq using satellite-based phenological parameters
Primary information of great importance to various
grand challenges such as sustainable agricultural intensification,
food insecurity, and climate change impacts, can be obtained indirectly
from land cover monitoring. However, in arid-to-semiarid
regions, such as Iraq, accurate discrimination of different vegetation
types is challenging due to their similar spectral responses.
Moreover, Iraq has been subjected to major disturbances, both
natural and anthropogenic which have affected the distribution
of land cover types through space and time. Reliable information
about croplands and natural vegetation in such regions is generally
scarce. This research aimed to develop a phenology-based
classification approach using support vector machines for the
assessment of space-time distribution of the dominant vegetation
land cover (VLC) types in Iraq, particularly croplands, from 2002
to 2012. Thirteen successive years of 8-day composites of MODISNDVI
data at a spatial resolution of 250 m were employed to
estimate 11 phenological parameters. The classification methodology
was assessed using reference samples taken from fine spatial
resolution imagery and independent testing data obtained through
fieldwork. Overall accuracies were generally >85%, with relatively
high Kappa coefficients (>0.86) across the classified land
cover types. The predicted cropland class area and the Global
MODIS land cover product were compared with ground statistical
data at the governorate level, revealing a significantly larger coefficient
of determination for the present phenology-based approach
R2 = 0.70 against R2 = 0.33 for MODIS, p< 0.05. The
resulting maps delimit for the first time, at a fine spatial resolution,
the spatial and interannual variability in the dominant VLC
classes across Iraq.
Classification, Iraq, monitoring, phenology, time-series
414-424
Qader, Sarchil
b1afb647-aeff-4bb8-84f2-56865c4eb9e4
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Rodriguez Galiano, Victor
44144f72-19cd-433e-be40-36a054d8fbf3
28 January 2016
Qader, Sarchil
b1afb647-aeff-4bb8-84f2-56865c4eb9e4
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Rodriguez Galiano, Victor
44144f72-19cd-433e-be40-36a054d8fbf3
Qader, Sarchil, Dash, Jadunandan, Atkinson, Peter M. and Rodriguez Galiano, Victor
(2016)
Classification of vegetation type in Iraq using satellite-based phenological parameters.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9 (1), .
(doi:10.1109/JSTARS.2015.2508639).
Abstract
Primary information of great importance to various
grand challenges such as sustainable agricultural intensification,
food insecurity, and climate change impacts, can be obtained indirectly
from land cover monitoring. However, in arid-to-semiarid
regions, such as Iraq, accurate discrimination of different vegetation
types is challenging due to their similar spectral responses.
Moreover, Iraq has been subjected to major disturbances, both
natural and anthropogenic which have affected the distribution
of land cover types through space and time. Reliable information
about croplands and natural vegetation in such regions is generally
scarce. This research aimed to develop a phenology-based
classification approach using support vector machines for the
assessment of space-time distribution of the dominant vegetation
land cover (VLC) types in Iraq, particularly croplands, from 2002
to 2012. Thirteen successive years of 8-day composites of MODISNDVI
data at a spatial resolution of 250 m were employed to
estimate 11 phenological parameters. The classification methodology
was assessed using reference samples taken from fine spatial
resolution imagery and independent testing data obtained through
fieldwork. Overall accuracies were generally >85%, with relatively
high Kappa coefficients (>0.86) across the classified land
cover types. The predicted cropland class area and the Global
MODIS land cover product were compared with ground statistical
data at the governorate level, revealing a significantly larger coefficient
of determination for the present phenology-based approach
R2 = 0.70 against R2 = 0.33 for MODIS, p< 0.05. The
resulting maps delimit for the first time, at a fine spatial resolution,
the spatial and interannual variability in the dominant VLC
classes across Iraq.
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More information
Accepted/In Press date: 2 December 2015
e-pub ahead of print date: 5 January 2016
Published date: 28 January 2016
Keywords:
Classification, Iraq, monitoring, phenology, time-series
Identifiers
Local EPrints ID: 412164
URI: http://eprints.soton.ac.uk/id/eprint/412164
ISSN: 1939-1404
PURE UUID: 24ab9198-4559-40eb-9436-08ae7f46861c
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Date deposited: 13 Jul 2017 16:31
Last modified: 16 Mar 2024 03:35
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Author:
Peter M. Atkinson
Author:
Victor Rodriguez Galiano
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