map integration ppt_f

Annual Meeting 2016

Understanding Map Integration

Using GIS Software

Michelle Pasco

USRIP Symposium

Introduction to GIS Geographic Information

System (GIS)

Used to study all kinds of data with a geospatial component

Digitizes maps using vector components (points, lines, polygons)

Representation of the real world and its attributes Credit: desktop.arcgis.com

Map Integration Also known as “conflation”

Combination of two or more datasets to provide new perspectives and insight on existent geo-enabled data sets

May result in a number of problems

This project attempted to research and conflate two data sets within GIS Virginia Department of Transportation’s (VDOT) Linear

Referencing System (LRS) INRIX XD (XD)

Study Area

Issues faced Spatial displacement and attribute disparity

Length, position, direction, size, shape Feature representation

Unequal updating periods, equal data models acquired by different operators, unequal data models, and content differences

Methods of Conflation Spatial Join – combines two datasets by comparing their

digitized geometries and creating a count recording either features in close proximity or complete matches

Methods of Conflation Transfer Attributes – matches a feature from one

dataset to another feature by selecting one attribute that is similar in both datasets within a certain distance

Comparison CasesSpatial Join

Matching Geographic Coordinate Systems (GCS) vs Original = possibly different GCS (ORG)

LRS EDGE (EDGE) vs LRS Non-EDGE (NON)

Transfer Attributes

Search Distances 0.1 miles 0.3 miles 0.5 miles 1 mile

Accuracy Assessment Spatial Join:

Transfer Attributes:

Results: Spatial Join

Visual representation of spatial join cases on part of I-64.

EDGE_ORG

EDGE_GCS

NON_ORG

NON_GCS

LRS EDGE = EDGELRS Non-EDGE = NON

XD Original = ORGXD Geographic Coordinate System = GCS

Results: Spatial JoinRoad Name & Spatial Join # of features (count>0)

featuresConflation

Accuracy, ca (%)

I-64 EDGE_ORG 728 632 86.81

I-564 EDGE_ORG 12 10 83.33

I-95 EDGE_ORG 573 452 78.88

I-395 EDGE_ORG 136 89 65.44

I-495 EDGE_ORG 167 102 61.08

Road Name & Spatial Join # of features (count>0)

featuresConflation

Accuracy, ca (%)

I-64 EDGE_GCS 728 359 49.31

I-564 EDGE_GCS 12 10 83.33

I-95 EDGE_GCS 573 287 50.09

I-395 EDGE_GCS 136 27 19.85

I-495 EDGE_GCS 167 30 17.96

Results: Transfer Attributes

Visual representation of transfer attribute cases on part of I-64.

0.1 mile Search Distance

0.3 mile Search Distance

0.5 mile Search Distance

1 mile Search Distance

Road Name & Search

Distance# of features No <Null>

featuresConflation

Accuracy, ca (%)

I-64_0.1 mi 754 686 90.98

I-564_0.1 mi 11 8 72.73

I-95_0.1 mi 477 435 97.32

I-395_0.1 mi 64 60 93.75

I-495_0.1 mi 52 50 96.15Road Name &

Search Distance

# of features No <Null> features

Conflation Accuracy, ca

(%)

I-64_0.3 mi 754 689 91.38

I-564_0.3 mi 11 8 72.73

I-95_0.3 mi 477 435 97.32

I-395_0.3 mi 64 61 95.31

I-495_0.3 mi 52 50 96.15

Results: Transfer Attributes

Results: Buffer Tool

0.1 0.3 0.5 FlatSeg 1

1 1 1 1

Seg 2

3 3 3 2

Seg 3

2 2 2 2

Seg 4

2 2 2 1

0.1 0.3 0.5 Flat4100330

2 2 2 2

4100331

3 3 3 2

4100515

3 3 3 2

Visual representation of the types of buffers on part of I-64.

LRS Matching XD Matching

Conclusions Transfer attributes is overall more accurate

Covers the two most important aspects in the conflation process: spatial data and attributes

Spatial joining is better to use if the datasets are comprised of many, potentially small, features

Either way, larger-scale projects will be more vulnerable to issues

Questions?

Acknowledgements Simona Babiceanu, who advised me and

kept me on the right track Dr. Emily Parkany, for the constant

support Daniela Gonzales, for encouraging me to

apply to this program

References Davis, Curt H., Haithcoat, Timothy L., Keller, James M., Song, Wenbo.

Relaxation- Based Point Feature Matching for Vector Map Conflation, 2011. Transactions in GIS, 15(1), pg. 43-60. http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9671.2010.01243.x/full. Accessed June 20, 2016.

Environmental Systems Research Institute (ESRI). ArcGIS for Desktop, 2016. arcgis.com. Accessed July 18, 2016.

G. v. Gösseln, M. Sester. Integration of Geoscientific Data Sets and the German Digital Map Using A Matching Approach. Commission IV, WG IV/7. http:// www.cartesia.org/geodoc/isprs2004/comm4/papers/534.pdf. Accessed June 15, 2016.

INRIX. I-95 Vehicle Protection Project II Interface Guide, 2014. http://i95coalition.org/projects/vehicle-probe-project/. Accessed June 17, 2016.

Virginia Department of Transportation. Roadway Network System. Release Notes, Linear Referencing System, Version 15.2, 2015. https://www.arcgis.com/ home/item.html?id=60916ea827544412ad209ea5192ad7fd. Accessed June 2, 2016.