Most geospatial data exists in fragmented formats (GeoTIFFs, shapefiles, and other domain-specific structures) requiring specialized tools to access and interpret. While existing platforms support data aggregation and visualization, they often lack tools for analyzing how site conditions evolve over time.

Dynamic Lands Lab is an independently developed system focused on spatiotemporal analysis, transforming heterogeneous geospatial data into structured datasets that capture patterns of change across terrain, vegetation, and environmental conditions. The goal is not just to describe what a site is, but how it changes.

The project grew out of prior work with Landsat data in urban heat island research and subsequent exploration across planning and land-use contexts, where a consistent gap became clear: limited infrastructure for integrating and analyzing spatial data as a unified, time-aware system. DLL addresses this by standardizing inputs, deriving composite metrics, and producing analysis-ready outputs.

Development & Iteration Loop

Market Signals / Use Cases

  • Geospatial community engagement

  • Real-World workflows

  • Identified gaps in tooling

Feature Design

  • Targeted pipeline development

  • Data processing and analytics layers

  • UI / visualization features

Development & Sharing

  • Ease of access

  • Minimized overhead

  • Web interfaces

Feedback & Validation

  • Reified analytics for non-technical stakeholders

  • Usability insights

  • Performance observations

Refinement & Iteration

  • Pipeline optimization

  • UI/UX refinement

  • Feature expansion

System Architecture & Data Flow

End-to-end architecture of the Dynamic Lands Lab, from data ingestion and processing to visualization and application layers.

Use Case Applications

Example use case of the DLL’s spatiotemporal insights in land management efforts