Operation

Returns point geometries for addresses in a table, i.e. geocoding. This operation requires a special license. Addresses that could not be found for any reason are not returned in the result. Specify either an address string in the Search Text property or structured parts in the corresponding properties, such as Country, Street etc. Combinations are also allowed. A recommendation is to not specify redundant parts which might confuse more than they help. If you for instance have both postal code and postal city and you trust that postal code is correct, then it is best to not specify postal city.

Most parameters comes in two versions, one that specifies the actual value, like country="SWE", and one that specifies a field name where to retrieve the actual value from, like countryField="CountryIso2".

Note: To geocode English or Pinyin addresses in China, the Country parameter must be set to "CHN".

Returns the following columns:

• <dataset key column> - the key column from the input dataset
• Address - The found address, formatted to address standards of the country
• Geometry - The point for the found item
• HouseNumber - The house number for the found item
• Street - The street for the found item
• PostalCode - The postal code for the found item
• City - The name of the city-level administrative division for the found item
• Adm1 - The name or abbreviated name for the first order administrative division (state) for the found item
• CountryIso2 - The country code for the found item
• Match - A value between 0 and 1 that tells how good the match was. 1 means perfect.
• All columns except the key column from dataset, prefixed with the dataset name.

Note that the returned fields might be empty where not applicable or where data is not available.

Supports:

• ScriptEval in load scripts

Example that geocodes some Swedish addresses where each item is in each own field:

This example shows geocoding in a more free text style:

Generates rectangular or hexagonal bins for a point dataset. This is a way to aggregate point data so that an overview of the data can be displayed efficiently.

Returns the following columns:

• <dataset key column> - the key column from the input dataset
• BinId - identity for the bin
• BinTable.BinPolygon - the polygon for the bin
• BinTable.CenterPoint - point in center of the bin
• All columns except the key column from dataset, prefixed with the dataset name.

Supports:

• ScriptEval in load scripts

Example that loads hexagonal bins from US airports:

Returns relations and distances between objects in one dataset and the closest n objects in another, if any is closer than the maximum distance. The cost may also be calculated along roads and in that case optionally use travel time. This operation is useful in many cases, not only for getting the relations to the closest but also for getting distance matrices between a set of points.

Returns the following columns:

• <dataset1 name>_<dataset2 name>_RelationId - a key generated for the relation between the two geometries
• <dataset1 key column> - the key column from the input dataset1
• <dataset2 key column> - the key column from the input dataset2
• Distance - the distance in the unit specified in costUnit
• Status - the returned status is either "ok" or "failed:" followed by an error message.
• LowResLine - a low resolution version of the route line, only available for non bird distance types.
• All columns except the key column from the input dataset1 dataset, prefixed with the dataset name.
• All columns except the key column from the input dataset2 dataset, prefixed with the dataset name.

Supports:

• ScriptEval in load scripts

This example finds the closest airports to points in a table:

Produces clusters from a point dataset based on geographic closeness between points. The cluster generation is controlled by the distance parameter that defines how far away a point may be from the cluster it belongs to. Returns a table with relations between points and clusters. Also returns a joined in table named Clusters with cluster geometries. It contains the fields ClusterID, ClusterCenter (point geometry) and PointCount. The count field contains the number of points in the cluster.

Returns the following columns:

• <dataset key column> - the key column from the input dataset
• ClusterID - Id of the cluster the point belongs to
• Clusters.ClusterPoint - Center point for cluster
• Clusters.PointCount - Number of original point belonging to the cluster
• All columns except the key column from the input dataset, prefixed with the dataset name.

Supports:

• ScriptEval in load scripts

This example clusters airports in the US so that airports closer than 50 km belongs to one cluster:

Dissolves and simplifies areas to form larger areas based on a mapping between old area identities (or geometries) and new area identities. This is typically used for building custom areas that are build up by smaller well defined areas, such as postal areas or administrative areas.

Returns the following columns:

• <dissolveField> - the field specified as dissolveField in indata
• DissolvedPolygon - the geometries of the new dissolved areas

Supports:

• ScriptEval in load scripts

The geometry dataset is optional. If not provided, geometries are supposed to be available in the dissolve definition dataset.

Note that overlaps of polygons are removed in all resolutions except Source.

This example creates two regions, one consisting of CA and AZ and one consisting of WA and OR:

Returns a table that maps between the key in dataset1 and the key in dataset2 for all objects that intersects. If both datasets contain polygons, the relative overlap area compared to the areas in respective dataset are returned.

It is possible to limit the number of intersecting geometries in the second dataset that should be mapped to each geometry in the first dataset by specifying intersectsCount. Then the most intersecting geometries are returned in order. The operation is symmetric if intersectsCount is not specified.

Returns the following columns:

• <dataset1 name>_<dataset2 name>_RelationId - a key generated for the relation between the two geometries
• <dataset1 key column> - the key column from the input dataset1
• <dataset2 key column> - the key column from the input dataset2
• <dataset1 name>.RelativeOverlap - the overlap compared to the polygon in dataset1, only returned if both datasets contain polygons. There is a performance penalty for requesting this field.
• <dataset2 name>.RelativeOverlap - the overlap compared to the polygon in dataset2, only returned if both datasets contain polygons. There is a performance penalty for requesting this field.
• All columns except the key column from the input dataset1 dataset, prefixed with the dataset name.
• All columns except the key column from the input dataset2 dataset, prefixed with the dataset name.

Supports:

• ScriptEval in load scripts

This example calculates which states some lines intersects:

• Key field - same as the key field for the name table
• <Address Table Ip Field> - same as the ip field that was looked up, only available if not same as key field
• IpPoint - The point for the found item
• CountryIso2 - The country code for the found item
• Adm1Code - The code for the first order administrative area for the found item. Note that this code is not always compatible with the code returned by the location service.
• City - The city for the found item
• All columns except the key column from the input dataset, prefixed with the dataset name.

IP geolocation is inherently imprecise. For many IP-addresses it is possible to pinpoint a city but for others only country can be resolved.

Best practise is to only send the Ip-column to the IpLookup operation. Example that looks up some IP addresses:

It is common that the same IP is repeated in many rows. It then improves performance to first filter out only the unique IPs like in this example:

This product includes GeoLite2 data created by MaxMind, available from http://www.maxmind.com.

Just loads the dataset, no operation applied. This makes it possible to load all the formats that GeoOperations supports. Note that Simplify can be a good alternative to Load if geometries are detailed and slow to display.

Returns the following columns:

• All columns from dataset.

Supports:

• ScriptEval in load scripts

Example that loads postal codes from Sweden:

Since WKT is supported as geometry format for data in INTABLE, the Load operation is excellent for converting geographic geometries loaded from a database into the Sense geometry format so that it can be displayed. The following example shows how to convert WKT data, in this case from the MyWKTData table:

Returns closest address for points in the list, also known as reverse geocoding. This operation requires a special license. Points that are close to streets will get street level addresses, otherwise it will fall back to return postal area or city level hits. For points too far away, no data is returned.

Returns the following columns:

• <dataset key column> - the key column from the input dataset
• Address - The found address, formatted to address standards of the country
• Geometry - The point for the found item
• HouseNumber - The house number for the found item
• Street - The street for the found item
• PostalCode - The postal code for the found item
• City - The name of the city-level administrative division for the found item
• Adm1 - The name or abbreviated name for the first order administrative division (state) for the found item
• CountryIso2 - The country code for the found item
• Distance - Distance in meters to the found address.
• All columns except the key column from dataset, prefixed with the dataset name.

Note that the returned fields might be empty where not applicable or where data is not available.

Example that gets the addresses for some points:

Calculates routes, including length and duration, between two locations in a table.

Note that the origin is the geometry column in the dataset. The destination column is specified in operation parameters since datasets only know of one geometry column.

If you use bird as transportation type it generates great circle arcs between origins and destinations.

Returns the following columns:

• <dataset key column> - the key column from the input dataset
• Distance - the route distance in meters
• Duration - the estimated route travel time in seconds
• Status - the returned status is either "ok" or "failed:" followed by an error message.
• LowResLine - a low resolution version of the route line
• All columns except the key column from the input dataset, prefixed with the dataset name.

Supports:

• ScriptEval in load scripts
• ScriptEvalStr in chart scripts for getting the route
• ScriptEval in chart scripts for getting the distance or duration

This is an example that calculates routes between points in a dataset:

This is an example that calculates routes directly in a Line Layer. The operation is called for the selection every time the selection changes. Normally there should be a calculation condition that is true if only a few points are selected (otherwise it is better to calculate the routes in the load script). This should be put in the load script to load the data for the example:

Use the following dimension in the Line Layer:

Use a calculation condition in the Line Layer:

In the Location property, which should be set to Line geometry, put this to calculate the routes from a fixed position to the selected points:

Simplifies line and area geometries in a dataset. It is often a useful to load geographic data with the Simplify operation instead of the Load operation to get more efficient geometries that are faster to display.

The degree of simplification is calculated automatically based on area, number of objects and size of objects. It is then possible to adjust that to a higher or lower resolution with the resolution parameter.

Area simplification is done with an algorithm that handles topologies and can remove gaps and join islands.

Line simplification is done with a breakpoint reduction algorithm.

Note that overlaps of polygons are removed. There will be no overlapping polygons in the output.

Returns the following columns:

• <dataset key column> - the key column from the input dataset1
• Simplified_<geometry column name> - simplified versions of the original geometries
• All columns except the key column from dataset, prefixed with the dataset name.

Supports:

• ScriptEval in load scripts

Example that loads simplified versions of US states:

Calculates travel time iso areas. All locations within the returned area can be reached within a certain time or is closer than a certain distance along roads. Returns a table with id, travel area geometry, center point, cost, cost unit and status (OK or failed).

If you use "bird" as transportation type it generates geographically correct circles around the origins.

Returns the following columns:

• <dataset key column> - the key column from the input dataset
• TravelArea - the polygon geometry that defines the travel area
• Cost - the cost as specified in the costValue or costField
• CostUnit - the cost unit as specified in costUnit
• Status - the returned status is either "ok" or "failed:" followed by an error message.
• All columns except the key column from the input dataset, prefixed with the dataset name.

Supports:

• ScriptEval in load scripts
• ScriptEvalStr in chart scripts for getting the travel area geometry
• ScriptEval in chart scripts for getting cost

This load script example generate 10 minute travel areas in Miami and Orlando from coordinates:

This load script example generate 10 minute travel areas in Miami and Orlando using named points:

This is an example that calculates Travel Areas around points directly in an Area Layer. The operation is called for the selection every time the selection changes. This should be put in the load script to load the data for the example:

Use the following dimension in the Area Layer:

Use a calculation condition in the Area Layer:

In the Location property put this:

Returns the relations between two datasets where a geometry in one dataset (enclosed) is completely inside the area in the other dataset (enclosing). Returns a table which maps between the key in enclosed and the key in enclosing for all found relations.

Use within typically for finding which areas the data is in. For example to test GPS-position for which administrative area they are in. This is a kind of reverse geocoding.

Returns the following columns:

• <enclosed name>_<enclosing name>_RelationId - a key generated for the relation between the two geometries
• <enclosed key column> - the key column from the input dataset1
• <enclosing key column> - the key column from the input dataset2
• All columns except the key column from the enclosed dataset, prefixed with the dataset name.
• All columns except the key column from the enclosing dataset, prefixed with the dataset name.

Supports:

• ScriptEval in load scripts

To compensate for inaccuracies in data it is sometimes better to use Closest instead of Within. For instance if you have point data in costal areas which you want to relate to administrative areas, small inaccuracies can make points fall slightly outside of the areas.

This is a load script example that calculates which points are within which states: