🌍 NASA Space Apps 2024 - GIS Mapping Challenge 🌍

Welcome to the PakStellar GIS Mapping Project, created for the NASA Space Apps 2024 Hackathon! This project harnesses the power of Geographic Information Systems (GIS) to explore critical issues in local communities by mapping and analyzing open data.

🚀 Overview

A Geographic Information System (GIS) allows you to create, manage, analyze, and visualize data to uncover spatial patterns and relationships. By layering open datasets onto maps, new insights emerge—revealing connections between physical geography and the societal issues they influence.

🛰️ Challenge Objective

The NASA Space Apps Challenge encourages participants to use mapping technologies and open data to explore how physical geography shapes community issues. Our project specifically tackles:

• GIS Mapping and Analysis: Using various open datasets, we analyze and visualize spatial relationships to generate meaningful insights.

🛠️ Project Tools and Technologies

• Python & Jupyter Notebook: For coding, data manipulation, and visualization.
• GIS Libraries: To handle geospatial data, including:
  • Leafmap / ipyleaflet for interactive mapping.
  • GeoPandas for geospatial data handling and analysis.
• Open Data Sources: We used publicly available datasets (e.g., [specific datasets, e.g., "NASA Earth Observations," "OpenStreetMap data"]) to overlay on the map for insightful analysis.
• Interactive Visualizations: Creating an interactive map that allows users to explore various layers of data.

📌 How to Run the Project

Prerequisites

• Python 3.x installed on your system.
• Jupyter Notebook or Jupyter Lab to run .ipynb files.
• Required Python packages (use requirements.txt or the instructions below).

Installation

1. Clone this repository:

   git clone https://github.com/YourUsername/NASA_Space_Apps_2024.git
   cd NASA_Space_Apps_2024

2. Install the necessary dependencies: Manually install key libraries:

   !pip install geopandas ipyleaflet leafmap pandas

3. Open the Jupyter Notebook:

   jupyter notebook NASA_SPACE_APP_2024_PakStellar.ipynb

4. Run the notebook cells to generate maps and analyze data layers.

🗺️ Project Features

1. Interactive Mapping with GIS:

   • Visualize and explore geospatial data overlaid on a map using open datasets.
   • Use different basemaps and layers to compare and contrast geographic features and community issues.

2. Data Analysis & Visualization:

   • Overlay various layers of open data to analyze their relationships
   • Generate visual insights through charts, graphs, and heatmaps.

3. Real-World Issue Exploration:

   • Present a clear visualization of how physical geography impacts a specific community issue.
   • The map provides an interactive experience for users to understand the spatial dynamics of the topic at hand.

🛠️ How It Works

1. Data Collection & Preparation:

   • Collect and clean open datasets relevant to the community issue being studied.
   • Transform data into a geospatial format using tools like GeoPandas for easier mapping.

2. Map Creation & Layering:

   • Use Leafmap or ipyleaflet to build an interactive map centered around your area of interest.
   • Overlay datasets as separate layers to provide a visual exploration tool.

3. Visualization & Analysis:

   • Analyze the spatial data to identify trends, correlations, and insights that help understand the community issue in greater depth.
   • Use the map to tell a story and offer potential solutions or areas for further exploration.

🔍 Exploring the Map

• Pan, Zoom, and Click: Interact with the map to view different areas and click on data points for more information.
• Layer Controls: Use layer toggles to add or remove specific datasets for analysis.
• Pop-ups and Tooltips: Click on map elements to view detailed data and descriptions, such as pollution levels, vegetation coverage, or other attributes.

🌐 Possible Use Cases

• Environmental Monitoring: Analyze the effects of industrial pollution on local water bodies.
• Urban Planning: Identify food deserts or green spaces in a city and propose improvements.
• Disaster Response: Map flood-prone areas and evaluate the vulnerability of local infrastructure.

🏆 Team & Contributions

• Team PakStellar: [Haseeb Ijaz, Kainat Ijaz, Aun]
• Contributors: If you would like to contribute to this project, please feel free to open an issue or create a pull request.

📊 Future Enhancements

• Expanded Data Layers: Incorporate more diverse datasets for broader analysis (e.g., traffic, population density).
• Advanced Analytics: Use machine learning or statistical models to predict future trends based on current spatial data.
• Enhanced Visualization: Develop more dynamic and user-friendly visualizations to enhance the storytelling aspect of the project.

🎯 Conclusion

Through this project, we aim to demonstrate the potential of GIS and open science data in providing actionable insights on how geography influences local community issues. By visualizing spatial data effectively, we can uncover new solutions and foster a deeper understanding of our world. 🌍📊

💡 Get Involved & Share

If you have ideas, feedback, or would like to share your own findings using this tool, feel free to reach out or contribute to this repository! Together, we can make a difference using the power of open data and GIS mapping. 💪

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Happy Mapping! 🚀✨