Parcel Level Case Study

Parcel-level case studies analyze individual land units to address diverse challenges across various domains. Research focuses on leveraging machine learning, often incorporating human-in-the-loop approaches, to improve accuracy in tasks such as property value assessment, vacant land identification, and land use classification from diverse data sources including remote sensing, social media, and IoT sensors. These studies contribute to improved urban planning, resource management, and more efficient logistics, offering valuable insights for both scientific modeling and practical applications in fields like environmental monitoring and real estate.