Vacant Lot Detection

A vacant lot refers to unused or underutilized land, often lacking significant structures or active development. Identifying these lots is crucial for urban planning, real estate investment, and sustainable land management.

Properly detecting vacant land can help optimize resource allocation, support infrastructure development, and contribute to economic growth. Additionally, recognizing these spaces enables policymakers to address issues such as urban sprawl, inefficient land use, and environmental sustainability.

Vacant Lot Detection Using Aerial Imagery, developed a deep learning computer vision model to identify and segment vacant lots from aerial imagery for urban planning and land management. Utilized remote sensing techniques, image processing, and geospatial analysis to detect underutilized land by analyzing land cover patterns and features.

The project involved training state-of-the-art deep learning models such as YOLO (You Only Look Once) for real-time object detection and DeepLabv3 for semantic segmentation. The models were trained on large datasets of satellite imagery, achieving high accuracy in identifying vacant lots across diverse urban landscapes.