Imagine you've been tasked to evaluate potential sites for a new warehouse. This evaluation is to be based on access to transportation, the presence of special restrictions such as nearby historical neighborhoods, access to restaurants and other facilities that employees may need, access to public transportation for employees, and nearby land use that may restrict or enhance development. How do you evaluate these sites in a quantifiable and defensible way? Of course you need data, but you also need tools that can analyze and measure geographic relationships.
Whenever you look at a map, you inherently start turning that map into information by finding patterns, assessing trends, or making decisions. This process is called spatial analysis, and it's what our eyes and minds do naturally whenever we look at a map.
But many patterns and relationships aren't always obvious by looking at a map. Often, there's too much data to sift through and present coherently on a map. The way you display the data on the map can change the patterns you see. Spatial analysis tools allow you to quantify patterns and relationships in the data and display the results as maps, tables, and charts. The spatial analysis tools that are now part of ArcGIS Online empower you to answer questions and make important decisions using more than a visual analysis.
To learn more about accessing and running the tools, see Use the analysis tools. An overview of each of the tools is available in the section below. The analysis tools are arranged in categories. These categories are logical groupings and do not affect how you access or use the tasks in any way.
If you're a developer, you can access these tools via web APIs. For more information, see the Spatial Analysis Service REST API.
These tools calculate total counts, lengths, areas, and basic descriptive statistics of features and their attributes within areas or near other features.
This tool works with a layer of point features and a layer of area features. It first figures out which points fall within each area. After determining this point-in-area spatial relationship, statistics about all points in the area are calculated and assigned to the area. The most basic statistic is the count of the number of points within the area, but you can get other statistics as well.
For example, suppose you have point features of coffee shop locations and area features of counties, and you want to summarize coffee sales by county. Assuming the coffee shops have a TOTAL_SALES attribute, you can get the sum of all TOTAL_SALES within each county, or the minimum or maximum TOTAL_SALES within each county, or the standard deviation of all sales within each county.
This tool finds features within a specified distance of features in the analysis layer. Distance can be measured as a straight-line distance, a drive-time distance (for example, within 10 minutes), or a drive distance (within 5 kilometers). Statistics are then calculated for the nearby features. For example:
This tool finds features (and portions of features) within the boundaries of areas in the analysis layer. For example:
These tools find features that pass any number of criteria that you specify. They are typically used for site selection, where the objective is to find places that satisfy multiple criteria.
Find Existing Locations
This tool selects existing features in your study area that meet a series of criteria you specify. These criteria can be based on attribute queries (for example, parcels that are vacant) and spatial queries (for example, parcels within 1 mile of a river).
These tools help you explore the character of areas. Detailed demographic data and statistics are returned for your chosen areas. Comparative information can also be reported for expanded areas such as counties and states.
This tool enriches your point or area data by getting facts about the people, places, and businesses that surround your data locations. Enrich Layer enables you to answer new questions about locations that you cannot answer with maps alone; for example, What kind of people live here? What do people like to do in this area? What are their habits and lifestyles? What kind of businesses are there in this area?
The result will be a new layer containing all demographic and geographic information from given data collections. This new information is added as fields in the table.
These tools help you identify, quantify, and visualize spatial patterns in your data by identifying areas of statistically significant clusters.
Find Hot Spots
The Find Hot Spots tool will determine if there is any statistically significant clustering in the spatial pattern of your data.
These tools help you answer one of the most common questions posed in spatial analysis: "What is near what?"
A buffer is an area that covers a given distance from a point, line, or area feature.
Buffers are typically used to create areas that can be further analyzed using a tool such as Overlay Layers. For example, if the question is "What buildings are within one mile of the school?", the answer can be found by creating a one-mile buffer around the school and overlaying the buffer with the layer containing building footprints. The end result is a layer of those buildings within one mile of the school.
Create Drive-Time Areas
Create Drive-Time Areas creates areas that can be reached within a specified drive time or drive distance. It measures out from one or many points (up to 1,000), along roads, to create a layer that can help you answer questions such as:
You may be able to answer your questions solely through visualizing the output areas. Alternatively, you can perform further spatial analysis using the output areas. For instance, running Aggregate Points using drive-time areas with demographic data can help determine which potential store location would likely provide the best customer base for your type of business.
This tool finds the nearest features and, optionally, reports and ranks the distance to the nearby features. To find what's nearby, the tool can either measure straight-line distance, road distance, or driving time. There are options to limit the number of nearest features to find or the search range in which to find them. The results from this tool can help you answer the following kinds of questions:
Find Nearest returns a layer containing the nearest features and, optionally, a line layer that links the start locations to their nearest locations. The optional line layer contains information about the start and nearest locations and the distances between.
These tools are used for both the day-to-day management of geographic data and for combining data prior to analysis.
With this tool, you can select and download data for a specified area of interest. Layers that you select will be added to a zip file or layer package.
Areas that overlap or share a common boundary are merged together to form a single area.
You can control which boundaries are merged by specifying a field. For example, if you have a layer of counties, and each county has a State_Name attribute, you can dissolve boundaries using the State_Name attribute. Adjacent counties will be merged together if they have the same value for State_Name. The end result is a layer of state boundaries.
This tool copies features from two layers into a new layer. The layers to be merged must all contain the same feature types (points, lines, or areas). You can control how the fields from the input layers are joined and copied. For example:
Overlay Layers combines two or more layers into one single layer. You can think of overlay as peering through a stack of maps and creating a single map containing all the information found in the stack. In fact, before the advent of GIS, cartographers would literally copy maps onto clear acetate sheets, overlay these sheets on a light table, and hand draw a new map from the overlaid data. Overlay is much more than a merging of line work; all the attributes of the features taking part in the overlay are carried through to the final product. Overlay is used to answer one of the most basic questions of geography, "What is on top of what?" For example: