Urabn Planning
Analytical Architecture
Our architects and designers are trained to optimize resources to achieve design objectives.
Land & Environmental Analysis
Assessment of the built environment for planning decisions.
- Built Environment
- Permits
- Site suitability & environmental impact studies
- Flood, erosion & heat-exposure mapping
Analytical CAD
Rigorous analysis of environmental factors which could affect the design.
- Surveying and Site Data Analysis
- Land permits research
- Costs and Budget Analysis and Reporting
- Construction Management
Computer-aided Design (CAD)
Computer-aided design (CAD) is the use of specialized software to create, modify, analyze, and optimize digital 2D and 3D models.
Land Survveying
Land surveying is the precise science of measuring and mapping the physical boundaries, elevations, and features of a property.
Permit Research
Permits and Building Code Research and Analysis.
Collaborative Approach
Gatheirng Insights across expertise, for a holistic approach to design.
Geophysical — Geospatial Analysis
Environmental Data Analysis
We read the land before we design on it: combining geospatial analysis with statistical inference to inform planning decisions with measurable environmental effects.
Land & Environmental Analysis
GIS-based assessment of how development interacts with the land it sits on, built for urban planning decisions.
- Terrain, hydrology & drainage modeling
- Remote sensing & land-cover change detection
- Site suitability & environmental impact studies
- Flood, erosion & heat-exposure mapping
Statistical & Spatial Inference
Rigorous uncertainty quantification for environmental datasets, applied by our statisticians and data scientists.
- Bayesian modeling of environmental processes
- Spatial interpolation of sparse field measurements
- Sensor & time-series state estimation
- Risk & scenario forecasting for planners
Markov Chain Monte Carlo
Sampling-based estimation of posterior distributions when a direct solution is intractable.
Bayesian Inference
Updating probability estimates as new environmental data arrives, with honest uncertainty ranges.
Gaussian Processes
Non-parametric modeling of spatial fields, used to interpolate between sparse ground measurements.
Kalman Filtering
Recursive state estimation from noisy, sequential sensor or monitoring data over time.