This repository contains a Python script for processing and visualizing soil moisture data in Kenya from (19833 to date).
# Kenya soil moisture Analysis
# Overview
This project focuses on analyzing soil moisture data for Kenya, spanning the years 1983 to 2024. The data is sourced from TAMSAT and involves several key steps, including downloading, clipping, and visualizing soil moisture metric
# Objectives
Data Acquisition: writing a python script to download soil moisture data from TAMSAT data repository
Data Processing
Mapping/clipping the data to Kenya's geographical boundaries as our main region of focus
Calculate and visualize monthly, quarterly (three-month average), and Annual soil moisture averages.
Extracting the processed soil moisture data and export it to Excel in a matrix time series format for different wards separatelyfor further analysis
## Data
Data was sourced from TAMSAT and has the following properties.
Spatial domain African continent, including Madagascar (N: 37.375°, S: -35.375°, W: -17.875°, E:51.375°)
Dimensions 292 pixels (latitude) by 278 pixels (longitude)
Spatial resolution 0.25° (approx. 25km)
Time-step daily, pentadal, dekadal, monthly, seasonal
Data format -
NetCDF
Available variable - sm_c4grass
Cost and Terms of use - TAMSAT data are free to use and are released for operational, research and commercial use under the terms of the Creative Commons Attribution 4.0 International license (CC BY 4.0). To view a copy of this license, visit
creativecommons.org.
Read more at :
research.reading.ac.uk
## Run Locally
Clone the project
```bash
git clone
github.com
```
Go to the project directory
```bash
cd Kenya-soil-moisture-Analysis
```
Install dependencies
```bash
pip install -r requirements.txt
```
Download Kenya Shape file level 3 from GADM
link ->
gadm.org
Run the data downloading script
```bash
WebCrawler.py
```
Run the quaterly plots script
```bash
quaterly plots.py
```
run the data fetching …