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Characterising the land surface phenology of middle eastern countries using moderate resolution landsat data

Characterising the land surface phenology of middle eastern countries using moderate resolution landsat data
Characterising the land surface phenology of middle eastern countries using moderate resolution landsat data
Global change impacts including climate change, increased CO2 and nitrogen deposition can be determined through a more precise characterisation of Land Surface Phenology (LSP) parameters. In addition, accurate estimation of LSP dates is being increasingly used in applications such as mapping vegetation types, yield forecasting, and irrigation management. However, there has not been any attempt to characterise Middle East vegetation phenology at the fine spatial resolution appropriate for such applications. Remote-sensing based approaches have proved to be a useful tool in such regions since access is restricted in some areas due to security issues and their inter-annual vegetation phenology parameters vary considerably because of high uncertainty in rainfall. This study aims to establish for the first time a comprehensive characterisation of the vegetation phenological characteristics of the major vegetation types in the Middle East at a fine spatial resolution of 30 m using Landsat Normalized Difference Vegetation Index (NDVI) time series data over a temporal range of 20 years (2000–2020). Overall, a progressive pattern in phenophases was observed from low to high latitude. The earliest start of the season was concentrated in the central and east of the region associated mainly with grassland and cultivated land, while the significantly delayed end of the season was mainly distributed in northern Turkey and Iran corresponding to the forest, resulting in the prolonged length of the season in the study area. There was a significant positive correlation between LSP parameters and latitude, which indicates a delay in the start of the season of 4.83 days (R2 = 0.86, p < 0.001) and a delay in the end of the season of 6.54 days (R2 = 0.83, p < 0.001) per degree of latitude increase. In addition, we have discussed the advantages of fine resolution LSP parameters over the available coarse datasets and showed how such outputs can improve many applications in the region. This study shows the potential of Landsat data to quantify the LSP of major land cover types in heterogeneous landscapes of the Middle East which enhances our understanding of the spatial-temporal dynamics of vegetation dynamics in arid and semi-arid settings in the world.
Land Surface phenology, Landsat, Middle East, remote sensing, vegetation phenology
2072-4292
Qader, Sarchil
b1afb647-aeff-4bb8-84f2-56865c4eb9e4
Priyatikanto, Rhorom
c250c3ca-958c-46a2-969a-3ad689b8630b
Khwarahm, Nabaz
2e1dea22-1f7f-41d6-b007-ed5bcc95f6ec
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Qader, Sarchil
b1afb647-aeff-4bb8-84f2-56865c4eb9e4
Priyatikanto, Rhorom
c250c3ca-958c-46a2-969a-3ad689b8630b
Khwarahm, Nabaz
2e1dea22-1f7f-41d6-b007-ed5bcc95f6ec
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8

Qader, Sarchil, Priyatikanto, Rhorom, Khwarahm, Nabaz, Tatem, Andrew and Dash, Jadunandan (2022) Characterising the land surface phenology of middle eastern countries using moderate resolution landsat data. Remote Sensing, 14 (9), [2136]. (doi:10.3390/rs14092136).

Record type: Article

Abstract

Global change impacts including climate change, increased CO2 and nitrogen deposition can be determined through a more precise characterisation of Land Surface Phenology (LSP) parameters. In addition, accurate estimation of LSP dates is being increasingly used in applications such as mapping vegetation types, yield forecasting, and irrigation management. However, there has not been any attempt to characterise Middle East vegetation phenology at the fine spatial resolution appropriate for such applications. Remote-sensing based approaches have proved to be a useful tool in such regions since access is restricted in some areas due to security issues and their inter-annual vegetation phenology parameters vary considerably because of high uncertainty in rainfall. This study aims to establish for the first time a comprehensive characterisation of the vegetation phenological characteristics of the major vegetation types in the Middle East at a fine spatial resolution of 30 m using Landsat Normalized Difference Vegetation Index (NDVI) time series data over a temporal range of 20 years (2000–2020). Overall, a progressive pattern in phenophases was observed from low to high latitude. The earliest start of the season was concentrated in the central and east of the region associated mainly with grassland and cultivated land, while the significantly delayed end of the season was mainly distributed in northern Turkey and Iran corresponding to the forest, resulting in the prolonged length of the season in the study area. There was a significant positive correlation between LSP parameters and latitude, which indicates a delay in the start of the season of 4.83 days (R2 = 0.86, p < 0.001) and a delay in the end of the season of 6.54 days (R2 = 0.83, p < 0.001) per degree of latitude increase. In addition, we have discussed the advantages of fine resolution LSP parameters over the available coarse datasets and showed how such outputs can improve many applications in the region. This study shows the potential of Landsat data to quantify the LSP of major land cover types in heterogeneous landscapes of the Middle East which enhances our understanding of the spatial-temporal dynamics of vegetation dynamics in arid and semi-arid settings in the world.

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Accepted/In Press date: 27 April 2022
Published date: 29 April 2022
Additional Information: Funding Information: Funding: This research was funded by UK Research and Innovation GCRF 323036/ARCP011217. Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Keywords: Land Surface phenology, Landsat, Middle East, remote sensing, vegetation phenology

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Local EPrints ID: 457489
URI: http://eprints.soton.ac.uk/id/eprint/457489
ISSN: 2072-4292
PURE UUID: 2da67802-0111-4029-8489-cba75d497bff
ORCID for Rhorom Priyatikanto: ORCID iD orcid.org/0000-0003-1203-2651
ORCID for Andrew Tatem: ORCID iD orcid.org/0000-0002-7270-941X
ORCID for Jadunandan Dash: ORCID iD orcid.org/0000-0002-5444-2109

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Date deposited: 09 Jun 2022 17:04
Last modified: 06 Jun 2024 02:12

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Contributors

Author: Sarchil Qader
Author: Rhorom Priyatikanto ORCID iD
Author: Nabaz Khwarahm
Author: Andrew Tatem ORCID iD
Author: Jadunandan Dash ORCID iD

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