Using remote sensing , GIS and other Earth Observatory System applications for climate assessment in West African countries
# West-Africa-Climate-Assessment-Tool
Using remote sensing , GIS and other Earth Observatory System applications for climate assessment in West African countries
## MODIS Land Surface Temperature (LST) & Precipitation level Viewer for Ghana & Nigeria
### Overview
This project is a Google Earth Engine (GEE) application that visualizes and analyzes Land Surface Temperature (LST) and Precipitation level data for Ghana and Nigeria. It allows users to select a year and month, visualize LST & Precipitation level data, as well as view a time series of both climate factor patterns/values for specific locations. The tool also provides a user-friendly interface for interaction, making it easy to explore the MODIS LST dataset and CHIRPS precipitation data over the region.
Futhermore, the base code is modular therby making the same assessment possible at any local and/or national level by changing a few parameters to suit the desired ROI.
Credit to Osman-Geomatics93/Sudan-Cli… for the inspiration.
### Goals
Visualize LST and Precipitation Data: Allow users to view MODIS Land Surface Temperature (LST) data & Rainfall Patterns.
Interactive Time Series: Let users click on the map to view a time series of LST values & rainfall patterns for any location.
User-friendly Interface: Provide a well-structured, clean UI webapp for year and month selection, data visualization, and chart generation.
### Data Sources
Land Surface Temperature: MODIS/061/MOD11A2
Rainfall Data: UCSB-CHG/CHIRPS/PENTAD
Administrative Boundaries: USDOS/LSIB_SIMPLE/2017
### Features
Temperature Analysis: MODIS-based LST data processing and visualization
Rainfall Patterns: CHIRPS precipitation data analysis
Interactive Maps: Toggle between temperature and rainfall layers
Time Series Charts: Visual representation of temporal climate patterns
Point Analysis: Click-based location-specific climate information
Custom Legend: Clear visualization of data ranges …