map analysis with feature datasets

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Map Analysis with Feature Datasets Francisco Olivera, Ph.D., P.E. Department of Civil Engineering Texas A&M University

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Map Analysis with Feature Datasets. Francisco Olivera, Ph.D., P.E. Department of Civil Engineering Texas A&M University. Map Analysis. - PowerPoint PPT Presentation

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Page 1: Map Analysis with Feature Datasets

Map Analysis with Feature Datasets

Francisco Olivera, Ph.D., P.E.Department of Civil Engineering

Texas A&M University

Page 2: Map Analysis with Feature Datasets

Map Analysis

Map analysis consists of inferring information -- necessary for a given engineering/scientific task -- from general information contained in digital spatial datasets. In map analysis with feature datasets, the digital spatial datasets consist of features (i.e., points, lines and polygons).

Page 3: Map Analysis with Feature Datasets

Sample Dataset

Four feature datasets are used to explain the analysis tools:

A: polygon dataset

B: polygon dataset

C: line dataset

D: point dataset

E: point dataset

Page 4: Map Analysis with Feature Datasets

Sample DatasetIn addition to geometric information (area, perimeter and length), the datasets have the following fields:

AConc: Mass of a certain fertilizer per unit area (mgr/Km2) (I)

ATrees: Number of trees (E)

BOwner: Land owner (I)

CName: Road name (I)

DRain: Annual precipitation depth (mm) (I)

ERain: Annual precipitation depth (mm) (I)

Page 5: Map Analysis with Feature Datasets

GeoProcessing Wizard

The GeoProcessing Wizard ArcView extension allows one to modify the features of spatial datasets.

Load the extension by clicking on File/Extensions and then checking the Geoprocessing box. The extension creates the View/GeoProcessing Wizard menu.

Page 6: Map Analysis with Feature Datasets

GeoProcessing - Dissolve

Creates a new dataset in which all features that have the same value for a given attribute are aggregated into a single record.

Applies to one dataset only.

User has the option of defining how attributes are recalculated.

Page 7: Map Analysis with Feature Datasets

GeoProcessing - Dissolve

Dissolving B so that all land that belongs to the same person is represented by a single polygon.

Select the dataset you want to dissolve; select the key attribute, which will be used to aggregate the features; and enter the path and name of the new dataset.

Select how the attributes shall be calculated (more than one option is allowed). The key attribute is copied by default.

Page 8: Map Analysis with Feature Datasets

GeoProcessing - Dissolve

After dissolving the dataset, boundaries between adjacent polygons that are aggregated disappear.

If aggregated polygons are not next to each other, the effect of dissolving will not be obvious in the View, but in the Table.

The figure shows only one record selected. The two polygons were two different records before dissolving.

Page 9: Map Analysis with Feature Datasets

GeoProcessing - Dissolve

After dissolving the dataset, the key attribute (i.e., BOwner) is copied, and two new attributes are created:

Count: number of polygons aggregated

Sum_Area: sum of the previous attribute Area (as requested in previous window)

Attributes Area, Perimeter, and Recno have been lost, but can be recalculated.

Page 10: Map Analysis with Feature Datasets

GeoProcessing - MergeCreates a new dataset from features of two or more datasets.

Attributes of only one of the datasets are retained. Attributes of the other datasets are retained only if they have the same name.

Applies to two or more datasets.

User has the option of selecting the dataset whose attributes will be retained.

Page 11: Map Analysis with Feature Datasets

GeoProcessing - Merge

Merging D and E so that all precipitation stations are in a single dataset.

Select the datasets you want to merge; select the dataset whose attributes will be retained; and enter the path and name of the new dataset.

Page 12: Map Analysis with Feature Datasets

GeoProcessing - Merge

After merging the datasets, all points are features of a single dataset.

Page 13: Map Analysis with Feature Datasets

GeoProcessing - Merge

After merging the datasets, the resulting dataset table has the attributes Recno and Drain, because those are the attributes of D (the datasets whose attributes are retained).

Attribute ERain of E is not transferred, while Recno is transferred. If Recno refers to the record number, it would be advisable to update it.

Page 14: Map Analysis with Feature Datasets

GeoProcessing - Clip

Creates a new feature dataset by clipping an input feature dataset with another clipping polygon dataset. The attributes of the input dataset are not altered (including the geometry).

Applies to two dataset.

Page 15: Map Analysis with Feature Datasets

GeoProcessing - Clip

Clipping out C with the selected polygons of BDisslv to identify the road segments that are in Kelly's, Mary's , and Melissa's property.

Select the dataset you want to clip; select the polygon dataset you want to use to clip; and enter the path and name of the new dataset. Check the Use Selected Features Only boxes if applies.

Page 16: Map Analysis with Feature Datasets

GeoProcessing - Clip

After clipping out the C dataset, only those segment within the selected polygons of BDisslv are considered.

Note that features in the resulting dataset are obtained by intersection of the input and the outline of the clipping datasets.

Page 17: Map Analysis with Feature Datasets

GeoProcessing - Clip

After clipping, the attributes of the input dataset are copied and not updated.

Record number, length, area and perimeter need to be recalculated.

Page 18: Map Analysis with Feature Datasets

GeoProcessing - Intersect

Creates a new dataset in which the features are the result of intersecting the features an input dataset with the polygons of an overlay dataset. Resulting features have attributes from both datasets.

Applies to two dataset.

Page 19: Map Analysis with Feature Datasets

GeoProcessing - Intersect

Intersecting A (input) by B (overlay) so that for each resulting polygon the mass of fertilizer per unit area and the owner are a unique combination of values.

Select the input and overlay datasets you want to intersect; and enter the path and name of the new dataset. Check the Use Selected Features Only boxes if applies.

Page 20: Map Analysis with Feature Datasets

GeoProcessing - Intersect

After intersecting the datasets, the number of polygons significantly increases, and the resulting dataset includes attribute data from both sources.

Page 21: Map Analysis with Feature Datasets

GeoProcessing - Intersect

After intersecting, all attributes from both datasets are copied.

Attributes Length, Area, Perimeter, and Recno correspond to the original datasets, and have to be recalculated.

Page 22: Map Analysis with Feature Datasets

GeoProcessing - Union

Creates a new dataset by combining the polygons of an input dataset with the polygons of an overlay dataset. The resulting dataset has the extent of both.

Applies to two polygon datasets.

Union is very similar to Intersect, but in Union the parts of the polygons that do not intersect have zero for the non-defined attributes.

Page 23: Map Analysis with Feature Datasets

GeoProcessing - Union

Union of A (input) and B (overlay) so that for each resulting polygon the mass of fertilizer per unit area and the owner are a unique combination of values.

Select the input dataset; select the overlay dataset; and enter the path and name of the new dataset. Check the Use Selected Features Only boxes if applies.

Page 24: Map Analysis with Feature Datasets

GeoProcessing - Union

After "unioning" the datasets, the number of polygons significantly increases, and the resulting dataset includes attribute data from both sources.

Page 25: Map Analysis with Feature Datasets

GeoProcessing - Union

After "unioning", all attributes from both datasets are copied. Polygons that correspond to only one dataset get zero for the attributes of the other dataset.

Attributes Length, Area, Perimeter, and Recno correspond to the original datasets, and have to be recalculated.

Page 26: Map Analysis with Feature Datasets

GeoProcessing – Spatial Join

Appends the attributes of a record of a source dataset to a record of a target dataset, with which it shares the same location.

Applies to two datasets.

Page 27: Map Analysis with Feature Datasets

GeoProcessing – Spatial Join

Spatially joining D (target) and C (source) so that for each precipitation station the nearest road is known.

Select the target and the source datasets.

The word "nearest" changes depending on the feature type of the target and source datasets.

Page 28: Map Analysis with Feature Datasets

GeoProcessing – Spatial Join

After spatially joining the source and target datasets, attributes from the source datasets are copied to the attribute table of the target dataset.

Appended attributes Length, Area, Perimeter, and Recno from the source dataset do not reflect the values of the target dataset.

Page 29: Map Analysis with Feature Datasets

GeoProcessing – Spatial Join

The spatial relation between features of the target and source datasets changes depending on their type.

Target Source Spatial Relation

Point Point Nearest

Point Line Nearest

Point Polygon Inside

Line Point Nearest

Line Line Part of

Line Polygon Inside

Polygon Point N/A

Polygon Line N/A

Polygon Polygon Inside

Page 30: Map Analysis with Feature Datasets

BuffersCreates a polygon graphic or a new polygon dataset, in which the outlines are at a given distance from the buffered graphics or features of a dataset.

Applies to one dataset only.

Select what you want to buffer (could be graphics or a feature dataset). Check the Use only selected features box if necessary.

Page 31: Map Analysis with Feature Datasets

Buffers

Buffers can be created in three different ways:

Single area at a given distance.

Single area at a distance defined in a attribute of the buffered features.

Multiple areas at distances multiple of a given value.

The window gives the chance to defined the View distance units without having to open the View Properties window

Page 32: Map Analysis with Feature Datasets

Buffers

Buffering polygons can intersect or be just the outline.

Buffering polygons can be graphics, polygons appended to an existing polygon dataset, or a new polygon dataset.

Page 33: Map Analysis with Feature Datasets

Buffers

Buffers allow one to identify which areas are within a certain distance from the buffered features.

It can be used to identify optimal areas for building schools, residential areas, etc.

Page 34: Map Analysis with Feature Datasets

Theissen Polygons

Theissen polygons are a simple way of defining a "surface" out of station point data.

Polygons are defined in such a way that all points of a polygon are closer to their station point than to any other station point.

Page 35: Map Analysis with Feature Datasets

Theissen Polygons

Traditionally, Theissen polygons have been used to define the "area of influence" of a precipitation station.

Polygons are assigned the precipitation value of their corresponding station.

Load the CRWR-Vector extension, make the point theme active, and click on CRWR-Vector/Theissen polygons.

Page 36: Map Analysis with Feature Datasets

Property Transfer

Property transfer consists of calculating an intensive property of a polygon dataset (target), given that it is defined on a different polygon dataset (source).

Creates a new field in the attribute table of the target dataset and populates it with the area-weighted average of the property.

Page 37: Map Analysis with Feature Datasets

Property Transfer

To calculate the precipitation depth in each person's lot, the precipitation depth has to be transferred from the Thiessen polygons to the lot polygons.

A1 A2

A3

P1 P2

P3

ii

iii

A

APP

Page 38: Map Analysis with Feature Datasets

Property Transfer

After transferring the property precipitation depth stored in the Drain field of the attribute table of Th (i.e., Theissen polygons), the precipitation in each person's lot is known.

Page 39: Map Analysis with Feature Datasets

Attribute Statistics

Statistics of the attributes of selected records for a given field are obtained by clicking on the field header and then on the Field/Statistics menu.

Page 40: Map Analysis with Feature Datasets

Joining Tables

Joining tables consists of appending the attributes of a source table to a target table, where the records are related through key fields in each table. The tables do not have to be attribute tables necessarily.

Page 41: Map Analysis with Feature Datasets

Joining Tables

To join tables, click on the header of the key field of each table and then click on the Join button.

Each record in the source table can be related to one or many records in the target table, but not vice versa. This type of relation is called one-to-one or many-to-one (target-to-source). ArcView will allow you to join tables under a one-to-many situation, but it will append the first of the many records in the source table that satisfy the relation.

Joined tables are not modified. The tables will be joined only in the current ArcView project, but they can be used in their original format in other applications, including the current project itself.

Page 42: Map Analysis with Feature Datasets

Linking Tables

Linking tables consists of relating the records of a source table to the records of a target table through key fields defined for each of the two tables.

When two tables are linked, selecting a record in the target table, automatically selects the related record or records in the source table.

Page 43: Map Analysis with Feature Datasets

Linking Tables

To link tables, click on the header of the key field of each table and then click on the Table/Link menu.

In case of a one-to-many relation, in which joining tables fails, linking tables is an alternative solution.

Linked tables are not modified. The tables will be linked only in the current ArcView project, but they can be used in their original format in other applications, including the current project itself.

Page 44: Map Analysis with Feature Datasets

Summarizing Tables

Summarizing tables consists of aggregating all the records that have the same value for a user-defined key field into a single record. The values of other fields are aggregated based on user defined options.

To join tables, click on the header of the key field of the table and then click on the Summarize button.

Page 45: Map Analysis with Feature Datasets

Summarizing Tables

Summary tables are new tables in dbf format. The summarized table, however, has not been modified.

A field Count stores the number of records in the original table that have been aggregated.

Page 46: Map Analysis with Feature Datasets

Summarizing Tables

Summarizing tables consists of aggregating all the records that have the same value for a user-defined key field into a single record. The values of other fields are aggregated based on user defined options.

To join tables, click on the header of the key field of the table and then click on the Summarize button.

Page 47: Map Analysis with Feature Datasets

Summarizing Tables

Summary tables are new tables in dbf format. The summarized table, however, has not been modified.

A field Count stores the number of records in the original table that have been aggregated.