Analyzing Decadal Trends of Vegetation Cover in Djibouti Using Landsat and Open Data Cube
This study investigates decadal trends in vegetation cover in Djibouti from 1990 to 2020, addressing challenges related to its arid climate and limited resources. Using Digital Earth Africa’s Open Data Cube and thirty years of Landsat imagery, change detection algorithms, and statistical analysis, t...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
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| Series: | Geomatics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-7418/5/1/6 |
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| Summary: | This study investigates decadal trends in vegetation cover in Djibouti from 1990 to 2020, addressing challenges related to its arid climate and limited resources. Using Digital Earth Africa’s Open Data Cube and thirty years of Landsat imagery, change detection algorithms, and statistical analysis, this research explores vegetation dynamics at various spatial and temporal scales. Studies on change detection have advanced the field through exploring Landsat time series and diverse algorithms, but face limitations in handling data inconsistencies, integrating methods, and addressing practical and socio-environmental challenges. The results, obtained through change detection using NDVI differencing and Welch’s <i>t</i>-test, reveal significant trends in vegetation across Djibouti’s administrative and countrywide levels. Results show significant countrywide vegetative loss from 1990 to 2010, but recovery from 2010 to 2020, as evidenced by Welch’s <i>t</i>-test results. This disproved the Null Hypothesis of no trend and confirmed significant trends across all regions and resolutions analyzed. The findings provide important information for policymakers, land managers, and conservationists, providing awareness into patterns of Djibouti’s vegetation trends in the face of future climate change. The use of Open Data Cube and cloud computing enhances research capacity, allowing for the rapid and repeated analysis of larger time periods and geographical regions. |
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| ISSN: | 2673-7418 |