dollahdorankhutupe-dev/Malawi_Climate_Tracker

The Malawi Climate Vulnerability & Drought Intelligence Dashboard # Malawi Climate Vulnerability & Drought Intelligence Dashboard **Malawi Climate Tracker** is an interactive, Shiny-based dashboard that integrates climate, satellite, and agricultural data from DERPIn and FS-COR platforms. It visualizes real-time drought risk, food security, and nutrition vulnerability, enabling policymakers, NGOs, and community planners to anticipate shocks, design targeted interventions, and strengthen resilience at the community level. --- ## Demo Click here for a video demonstration. --- ## Features - **Real-Time Drought Risk Monitoring:** Visualizes current and historical drought risk across Malawi using integrated satellite and climate data. - **Food Security & Nutrition Vulnerability Mapping:** Displays spatial data on food security and nutrition vulnerability at district and community levels. - **Integrated Data Sources:** Combines DERPIn and FS-COR data streams for comprehensive climate and agriculture insights. - **Interactive Data Exploration:** Allows users to filter, zoom, and interact with maps and graphs to explore trends by region and over time. - **Custom Alerts & Early Warning System:** Notifies users of emerging risks or hotspots for targeted response. - **Downloadable Reports:** Enables users to export data visualizations and reports for offline analysis or sharing. - **User-Friendly Interface:** Designed for ease of use by policymakers, NGOs, and community planners, even those without technical expertise. --- ## How to Run ### Option 1: Using Posit Cloud (Recommended) 1. **Open Posit Cloud and create a new project.** 2. Upload all project files (including `app.R` and any data folders such as `data/`, `www/`, or `demo/`) to your Posit Cloud project. 3. In the Posit Cloud interface, open `app.R`. 4. Click the **Run App** button at the top of the RStudio editor pane. > **Note:** Required packages are installed automatically by the code in `app.R`. If prompted, click “Install”. --- ### Option 2: Run Locally in R or RS …