Aggregate Points

This tool works with a layer of point features and a layer of area features. It first identifies the points that fall within each area. After identifying 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, 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.

Join Features

This tool transfers the attributes of one layer or table to another based on spatial and attribute relationships. Statistics can then be calculated on the joined features.

For example, you can do the following:

• Join crime data to police districts using a spatial relationship.
• Join land use descriptions to land use polygons using code values.

Summarize Nearby

This tool finds features within a specified distance of features in the analysis layer. Distance can be measured as a straight-line distance or a selected travel mode. Statistics are then calculated for the nearby features.

For example, you can do the following:

• Calculate the total population within a 5-minute drive time of a proposed store location.
• Calculate the number of freeway access ramps within a 1-mile driving distance of a proposed store location to use as a measure of store accessibility.

Summarize Within

This tool finds features (and portions of features) within the boundaries of areas in the analysis layer.

For example, you can do the following:

• Given a layer of watershed boundaries and a layer of land-use boundaries by land-use type, calculate the total acreage of land-use type for each watershed.
• Given a layer of parcels in a county and a layer of city boundaries, summarize the average value of vacant parcels within each city boundary.

Summarize Center and Dispersion

This tool finds the central feature, mean center, median center, or ellipse (directional distribution) of point features.

For example, you can do the following:

• Find the central feature in a set of points, such as trees, buildings, or parks.
• Find the mean center of a set of points, such as crime incidents or wildlife sightings.
• Find the median center of a set of points, such as the locations of car accidents.
• Find the dispersion (ellipse) of a set of points, such as disease occurrences or the location of an invasive plant species.

Find Existing Locations

This tool identifies 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).

Derive New Locations

This tool derives new 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 that are within flood zones).

Find Similar Locations

This tool measures the similarity of locations in your candidate search layer to one or more reference locations based on criteria that you specify.

Geocode Locations from Table

This tool geocodes large tables and files of addresses into points. The output can be created as a comma-separated values file (.csv), an Excel (XLS) spreadsheet, or a feature service.

Choose Best Facilities

This tool finds the set of facilities that will best serve demand from surrounding areas.

Facilities can be public institutions that offer a service, such as fire stations, schools, or libraries, or they can be commercial facilities, such as drug stores or distribution centers for a parcel delivery service. Demand represents the need for a service that the facilities can meet. Demand is associated with point locations, with each location representing a given amount of demand.

Create Viewshed

This tool creates areas where an observer can see objects on the ground. The input analysis points can represent either observers (such as people on the ground or lookouts in a fire tower) or observed objects (such as wind turbines, water towers, vehicles, or other people). The result areas are where the observers can see the observed objects and vice versa: the observed objects can see the observers. The output is typically used in site suitability and selection analysis.

Create Watersheds

This tool identifies catchment areas based on locations you specify.

Trace Downstream

This tool identifies the trace, or flow path, in a downstream direction from the points in your analysis layer.

Find Centroids

This tool creates central point features from multipoint, line, and area features.

Enrich Layer

This tool enriches your point or area data by getting facts about the people, places, and businesses that surround your data locations. Using this tool, you can answer 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 in this area?

The result is a new layer containing all demographic and geographic information from given data collections. This information is added as fields in the table.

Calculate Density

This tool creates a density map from point or line features by spreading known quantities of a phenomenon (represented as attributes of the points or lines) across the map. The result is a layer of areas classified from least dense to most dense.

For example, you can do the following:

• Calculate densities of hospitals in a county. The result layer shows areas with high and low accessibility to hospitals, and you can use this information to determine where new hospitals should be built.
• Identify areas that are at high risk of forest fires based on historical locations of forest fires.
• Locate communities that are far from major highways to plan where new roads should be constructed.

Find Hot Spots

This tool identifies statistically significant clustering in the spatial pattern of your data.

For example, you can do the following:

• Determine if your points (crime incidents, trees, traffic accidents) are clustered.
• Discover a statistically significant hot spot (for spending, infant mortality, consistently high test scores).

Find Outliers

This tool identifies statistically significant outliers in the spatial pattern of your data.

For example, you can do the following:

• Find anomalous areas in the pattern of your data (crime incidents, trees, traffic accidents).
• Discover a statistically significant outlier (for spending, infant mortality, consistently high test scores),

Find Point Clusters

This tool finds clusters of point features in surrounding noise based on their spatial distribution.

For example, you can do the following:

• Find clusters of houses infested with pests.
• Find clusters of crime incidents, such as theft.

Interpolate Points

This tool allows you to predict values at new locations based on measurements from a collection of points. The tool takes point data with values at each point and returns areas classified by predicted values.

For example, you can do the following:

• Predict pollution levels at locations that don't have air quality management district sensors that measure pollution levels, such as locations with at-risk populations—schools or hospitals, for example.
• Predict heavy metal concentrations in crops based on samples taken from individual plants.
• Predict soil nutrient levels (nitrogen, phosphorus, potassium, and so on) and other indicators (such as electrical conductivity) in order to study their relationships to crop yield and prescribe precise amounts of fertilizer for each location in the field.
• Predict temperatures, rainfall, and associated variables (such as acid rain) and other meteorological applications.

Create Buffers

This tool creates buffers. 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 1 mile of the school?, you can find the answer by creating a 1-mile buffer around the school and overlaying the buffer with the layer containing building footprints. The result is a layer of those buildings within 1 mile of the school.

Create Drive-Time Areas

This tool creates areas that can be reached within a specified drive time or drive distance. It measures from one or many points (up to 1,000), along roads, to create a layer that can help you answer questions such as the following:

• Where can I go from here within a 30-minute drive?
• Where can I go from here within a 30-minute drive at 5:30 p.m. during rush hour?
• What areas of town can the fire department reach in 5 minutes?
• How would fire-response coverage improve by building a fire station here?
• What market areas does my business cover?

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 example, you can run the Aggregate Points tool using drive-time areas with demographic data to determine the potential store location that will likely provide the best customer base for your type of business.

Find Nearest

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 or a selected travel mode. 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 questions such as the following:

• What park is nearest to me?
• Which hospital can I reach in the shortest drive time? How long will the trip take on a Tuesday at 5:30 p.m. during rush hour?
• What are the road distances between these major cities?
• Which of these patients reside within 2 miles of these chemical plants?

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.

Plan Routes

This tool efficiently divides tasks among a mobile workforce.

You provide the tool with a set of stops and the number of vehicles available to visit the stops. The tool assigns the stops to vehicles and returns routes showing how each vehicle can reach their assigned stops in the least amount of time.

With Plan Routes, mobile workforces can reach more job sites in less time, which increases productivity and improves customer service. For example, they can do the following:

• Inspect homes, restaurants, or construction sites.
• Provide repair, installation, or technical services.
• Deliver items and small packages.
• Make sales calls.
• Transport people from their homes to an event.

The output from Plan Routes includes a layer of stops coded by the routes to which they are assigned, a layer of routes showing the shortest paths to visit assigned stops, and, depending on whether any stops could not be reached, a layer of unassigned stops.

Connect Origins to Destinations

This tool measures the travel time or distance between pairs of points. The tool can identify straight-line distances, road distances, or travel times. You provide starting and ending points, and the tool returns a layer containing route lines, including measurements, between the paired origins and destinations. If many origins go to one destination, a table summarizing multiple trips to the destination is included in the output.

Extract Data

This tool extracts data that you select for a specified area of interest. Layers that you select are added to a .zip file or layer package.

Dissolve Boundaries

This tool merges areas that overlap or share a common boundary 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 are merged if they have the same State_Name value. The result is a layer of state boundaries.

Generate Tessellations

This tool creates bins of a specified shape and size for the study area.

Bins can be square, hexagonal, transverse hexagonal, triangular, or diamond shaped.

Merge Layers

This tool copies features from two layers into a new single 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, you can do the following:

• Merge a layer of public schools and a layer of private schools into a single layer showing all schools.
• Merge two layers which each contain parcel information for contiguous townships into a single layer, keeping only the fields that have the same name and data type for the two input layers.

Overlay Layers

This tool combines two or more layers into a 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. 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, you can answer the following questions:

• What parcels are within the 100-year floodplain? (Within is just another way of saying on top of.)
• What roads are within what counties?
• What land use is on top of what soil type?
• What wells are within abandoned military bases?