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Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland

This study uses remote sensing data from 2005 to 2023 to analyze the spatiotemporal pattern of agricultural drought severity and hotspots in Somaliland. The Vegetation Condition Index (VCI), derived from MODIS satellite imagery, was employed to assess drought conditions, while CHIRPS rainfall data p...

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Main Authors: Omar, Abdillahi Osman, Alasow, Ahmed Abdiaziz, Farah, Abdiweli Ali, Shahid, Shamsuddin
Format: Article
Language:English
Published: International Information and Engineering Technology Association 2024
Online Access:http://psasir.upm.edu.my/id/eprint/114776/1/114776.pdf
http://psasir.upm.edu.my/id/eprint/114776/
https://iieta.org/journals/ijsdp/paper/10.18280/ijsdp.191104
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spelling my.upm.eprints.1147762025-01-31T02:35:30Z http://psasir.upm.edu.my/id/eprint/114776/ Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland Omar, Abdillahi Osman Alasow, Ahmed Abdiaziz Farah, Abdiweli Ali Shahid, Shamsuddin This study uses remote sensing data from 2005 to 2023 to analyze the spatiotemporal pattern of agricultural drought severity and hotspots in Somaliland. The Vegetation Condition Index (VCI), derived from MODIS satellite imagery, was employed to assess drought conditions, while CHIRPS rainfall data provided insights into precipitation patterns. Results revealed significant temporal and spatial variability in drought severity across Somaliland. VCI trends indicated cyclical patterns of vegetation health, with severe stress observed from 2015 to 2018, followed by recovery from 2019 to 2021. A strong positive correlation between VCI and rainfall was observed, with correlation coefficients ranging from 0.5638 in Saaxil to 0.7701 in Togdheer. Drought severity classification identified Sool and Togdheer as the most critically affected regions, with 90% and 85% of their areas under extreme drought conditions, respectively. Saaxil exhibited the lowest percentage of extreme drought at 35%. Temporal analysis of NDVI deviations confirmed prolonged vegetation stress from 2015 to 2018, with notable improvement in 2020 and 2021. The findings underscore Somaliland's vulnerability to recurrent droughts, emphasizing the urgent need for targeted interventions and adaptive management strategies to enhance resilience in this semi-arid region. International Information and Engineering Technology Association 2024 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/114776/1/114776.pdf Omar, Abdillahi Osman and Alasow, Ahmed Abdiaziz and Farah, Abdiweli Ali and Shahid, Shamsuddin (2024) Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland. International Journal of Sustainable Development and Planning, 19 (11). pp. 4135-4146. ISSN 1743-7601; eISSN: 1743-761X https://iieta.org/journals/ijsdp/paper/10.18280/ijsdp.191104 10.18280/ijsdp.191104
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This study uses remote sensing data from 2005 to 2023 to analyze the spatiotemporal pattern of agricultural drought severity and hotspots in Somaliland. The Vegetation Condition Index (VCI), derived from MODIS satellite imagery, was employed to assess drought conditions, while CHIRPS rainfall data provided insights into precipitation patterns. Results revealed significant temporal and spatial variability in drought severity across Somaliland. VCI trends indicated cyclical patterns of vegetation health, with severe stress observed from 2015 to 2018, followed by recovery from 2019 to 2021. A strong positive correlation between VCI and rainfall was observed, with correlation coefficients ranging from 0.5638 in Saaxil to 0.7701 in Togdheer. Drought severity classification identified Sool and Togdheer as the most critically affected regions, with 90% and 85% of their areas under extreme drought conditions, respectively. Saaxil exhibited the lowest percentage of extreme drought at 35%. Temporal analysis of NDVI deviations confirmed prolonged vegetation stress from 2015 to 2018, with notable improvement in 2020 and 2021. The findings underscore Somaliland's vulnerability to recurrent droughts, emphasizing the urgent need for targeted interventions and adaptive management strategies to enhance resilience in this semi-arid region.
format Article
author Omar, Abdillahi Osman
Alasow, Ahmed Abdiaziz
Farah, Abdiweli Ali
Shahid, Shamsuddin
spellingShingle Omar, Abdillahi Osman
Alasow, Ahmed Abdiaziz
Farah, Abdiweli Ali
Shahid, Shamsuddin
Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland
author_facet Omar, Abdillahi Osman
Alasow, Ahmed Abdiaziz
Farah, Abdiweli Ali
Shahid, Shamsuddin
author_sort Omar, Abdillahi Osman
title Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland
title_short Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland
title_full Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland
title_fullStr Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland
title_full_unstemmed Spatiotemporal analysis of agricultural drought severity and hotspots in Somaliland
title_sort spatiotemporal analysis of agricultural drought severity and hotspots in somaliland
publisher International Information and Engineering Technology Association
publishDate 2024
url http://psasir.upm.edu.my/id/eprint/114776/1/114776.pdf
http://psasir.upm.edu.my/id/eprint/114776/
https://iieta.org/journals/ijsdp/paper/10.18280/ijsdp.191104
_version_ 1823093270495887360
score 13.239859

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