Geospatial Training Services specializes in the use of spatial analytics and data science techniques to help our clients resolve complex questions and problems that have spatial and temporal components and often include big datasets.
Spatial statistics is a set of exploratory techniques for describing and modeling spatial distributions, patterns, processes, and relationships. Although spatial statistics are similar to traditional statistics they also integrate spatial relationships into the calculations. In spatial statistics, proximity is important. Things that are closer together are more related and we can expand that to include a temporal component that specifies that things that are closer together in space and time are more related.
Spatial statistics extends traditional statistics through the analysis of geographic data via techniques that describe the distribution of data (descriptive spatial statistics), analysis of spatial patterns of data (spatial pattern analysis), identification and measurement of spatial relationships (spatial regression), and the creation of surface layers through sampled data (spatial interpolation).
We use spatial analysis and geostatistical tools from ArcGIS Desktop (Spatial Analyst and Spatial Statistics Toolbox), QGIS, Carto, R, Python and others to perform analysis for natural resources, real estate, crime, health, and environmental applications.
Our spatial statistics capabilities include ordinary least squares regression, geographically weighted regression, hot spot analysis, outlier and cluster analysis, similarity search, grouping analysis, spatial autocorrelation, and more.
What Types of Questions Can We Help With?
- Where do crimes cluster in Phoenix?
- What are the primary predictors of high rates of burglary in Seattle?
- What are the trends over space and time for diabetes rates in Alabama?
- Where are the hot spots of wildfire activity in the Rocky Mountains?
- What are the trends for human caused wildfires in the past decade for California?
- What are the demographic and socio-economic variables that predict where a new retail store will be successful?
- Where do luxury home sales cluster in Austin?
- Where are the hot spots for elk grazing in Wyoming?
- What census tracts in Denver are most similar when comparing income, education, and race?
Spatial and Data Science Functional Capabilities
- Hot Spot Analysis
- Cluster and Outlier Analysis
- Spatial-Temporal Analysis
- Simple Least Squares Regression
- Geographically Weighted Regression
- Similarity Search
- Grouping Analysis
- Spatial Autocorrelation
- Statistical Modeling
- Data Cleansing and Preparation
- Data Mining
- Data Visualization (charts and graphs with plotly and Bokeh)
Spatial and Data Science Technical Capabilities
- ArcGIS Spatial Statistics Toolbox
- ArcGIS Spatial Analyst
- Python Programming with Pandas, NumPy, SciPi, plotly, Bokeh
- R Programming
Industries We Serve
- Natural Resources
- Environmental Management
- Real Estate
Recent webinars on this topic:
My book on this topic: Spatial Analytics in ArcGIS
Contact us at sales at geospatialtraining.com for more information on how we can assist you with your project.