map integration ppt_f
TRANSCRIPT
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.