TerraTrust Project Story

Overview

TerraTrust is a web application designed to evaluate land acquisition risk for Lennar, a residential construction company. By leveraging various data sources, TerraTrust calculates a risk score out of 100 for a given land address, helping Lennar assess environmental, crime, and economic risks associated with potential land deals.

Problem Statement

Acquiring land for residential communities involves multiple risks that can threaten the success of a project. These risks include environmental hazards, crime rates, and economic factors such as growth potential and market demand. TerraTrust aims to provide a reliable, data-driven risk score for land acquisition decisions.

Goal

Develop a web app where users can input a land address and receive a risk score based on several factors, including environmental conditions, crime data, and economic indicators. The risk score will help users make more informed decisions when evaluating land for acquisition.

Key Features

• User Input: Users enter a land address (in Texas, initially) into the web app.
• Risk Score Calculation: The app calculates a risk score based on environmental, crime, and economic factors, weighted according to predefined categories.
• Visualization: A dynamic, interactive dashboard will display the risk score and relevant data for each category.

Risk Score Categories and Weights

1. Environmental (30%)

   • Soil (10%)
   • Natural disaster risk (9%)
     • Hail (2%)
     • Damaging Winds (5%)
     • Tornadoes (2%)
   • Air Pollution (11%)

2. Crime (15%)

3. Economic Growth (55%)

   • Market Demand (10%)
   • Population Growth (10%)
   • Employment Rate & Growth (10%)
   • Public Infrastructure (10%)
   • Land Value Appreciation (15%)

Conclusion

TerraTrust empowers Lennar with a data-driven tool that reduces risk and enhances decision-making in land acquisition for residential development. By considering environmental, crime, and economic factors, the web app ensures a comprehensive risk analysis for every land evaluation.

Built With

• mapkit
• python
• pytorch
• swift