Add value to data by understanding spatial relationships and patterns
Aggregate and normalize
Uncover patterns in large datasets by applying filters and simplifying, aggregating, and enriching data. The example in this tutorial compares the density of electric alternate fueling stations to population by state.
Intersect and extract
Perform powerful spatial operations such as point in polygon, line crosses polygon, or polygon is within polygon to find data that matches your criteria. The example in this tutorial explores the value of land parcels extracted for an area in southwestern Colorado.
Buffer and route
Combine buffer, distance, and network analysis to solve complex routing problems. This tutorial's example explores the accessibility of ski resorts in Colorado from the Denver airport.
Identify, quantify, and find visual spatial patterns in your data. The example in this tutorial identifies patterns of car theft in San Francisco.
Use the Geometry Engine (client side) and the Geometry Service (server side) to perform advanced geometric and spatial relationship operations on points, lines, and polygons. The scenario in this tutorial creates buffers around hurricane tracks and then calculates the intersecting area and shoreline distance impacted.
View, project, and perform spatial analyses on your data in any coordinate system with the Geometry Engine (client side) and the Geometry Service (server side). This tutorial's scenario illustrates how you can apply geographic and projected coordinate systems to your data.