This repository hosts the preprint paper titled "Spatiotemporal Analysis of Agricultural Drought Severity and Hotspots in Somaliland." The study provides a comprehensive analysis of agricultural droughts in Somaliland, utilizing spatiotemporal data. It integrates MODIS-derived vegetation indices and CHIRPS precipitation data to identify and assess drought severity and hotspots over time.
The repository contains the data, code, and results from the study, offering valuable resources for further research and practical applications in drought monitoring and mitigation.
Abdillahi Osman Omar1, Ahmed Abdiaziz Alasow2*, Abdiweli Ali Farah2, Shamsuddin Shahid3
1 Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands. Email: abdillahiosmanomar@student.utwente.nl
2 Department of Civil Engineering, Faculty of Engineering, Jamhuriya University of Science & Technology, Mogadishu, Somalia; alasow@just.edu.so
3 Department of Water and Environmental Engineering, Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), 81310 Skudia, Johor, Malaysia; sshahid@utm.my
This repository is organized as follows:
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Data: This directory contains all datasets used in the study, including MODIS-derived vegetation indices and CHIRPS precipitation data. The files are provided in a ready-to-use format for analysis.
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Notebooks: Contains all Python and JavaScripts codes used for data processing, analysis, and visualization. The scripts are well-commented to ensure easy understanding and reproducibility of the results.
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Reports: This folder includes the output from the scripts, such as processed data, figures, and tables which are referenced in the preprinted paper. These results highlight key findings and are crucial for understanding the spatiotemporal dynamics of drought in Somaliland.
Before running the scripts, ensure you have Python installed on your system. Required Python libraries packages include:
- NumPy: NumPy Official Website
- pandas: pandas Official Website
- matplotlib: matplotlib Official Website
- seaborn: seaborn Official Website
- rasterio: rasterio Official Website
- GDAL: GDAL Official Website
This project is licensed under the MIT License. For more details, see the LICENSE file.