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FME Around the World


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Lizard Island: On Location …

Lizard Island: On Location
FME Stories From Around the World

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  • 1. CONNECT. TRANSFORM. AUTOMATE. Lizard Island: On Location FME Stories From Around the World
  • 2. CONNECT. TRANSFORM. AUTOMATE. Iowa, USA Snow Plows, ArcGIS Online, an iPhone, and FME
  • 3. CONNECT. TRANSFORM. AUTOMATE. Snow Plows, ArcGIS Online, an iPhone, and FME  Eric Abrams, Iowa Department of Transportation  901 Snow Plows  32 – 34 inches of snow  9400 miles of road  15 million gallons of brine  120,000 tons of salt on 45 inches of snowfall in 2013  ROI - Every dollar spent on AVL returns $6.40  A 10% reduction of salt is $1.4 million dollars in savings
  • 5. CONNECT. TRANSFORM. AUTOMATE. Automatic Vehicle Location  Invisible to driver  Real-time flow of data – position, status, material usage, conditions  Data uploading to Amazon cloud  FME moves data to Oracle Spatial for internal usage, then to AGOL for public viewing
  • 6. CONNECT. TRANSFORM. AUTOMATE. Dashcams  Dash-mounted iPhones send image stream when vehicle is in motion  FME handles KML generation and upload to Windows Azure
  • 7. CONNECT. TRANSFORM. AUTOMATE. AGOL Public Data Access  ArcGIS Online keeps public informed with current plow status and conditions
  • 8. CONNECT. TRANSFORM. AUTOMATE. Dashcam Feeds  Public can also see what the driver is seeing for better awareness of road and weather conditions – making winter driving safer.
  • 9. CONNECT. TRANSFORM. AUTOMATE. Safer Winter Driving
  • 10. CONNECT. TRANSFORM. AUTOMATE. Sharing Open Data on GitHub with FME La Rioja, Spain
  • 11. CONNECT. TRANSFORM. AUTOMATE. Sharing Public Data  Ide Rioja committed to sharing and collaborating on public data.  Spatial Data Sharing taken to the next level  Creative Commons License  Enter GitHub
  • 12. CONNECT. TRANSFORM. AUTOMATE. Why GitHub  GitHub is a web-based Version Control System (VCS) which records changes to a file or set of files over time.  Allows:  commit files to a public repository  revert files back to a previous state  review changes made over time  see who last modified something, and more...
  • 14. CONNECT. TRANSFORM. AUTOMATE. Sharing Public Data
  • 15. CONNECT. TRANSFORM. AUTOMATE. How does FME Help?  Of course FME translates data from Oracle Spatial to GeoJSON for GitHub  But first!  FME reads the layer list from GitHub using Python Scripted Parameter – git pull  And after!  FME commits updated GeoJSON to GitHub in Shut Down Script – git push  Scheduled Job on FME Server
  • 17. CONNECT. TRANSFORM. AUTOMATE. The Beauty of GeoJSON in GitHub  GitHub supports automatic rendering of GeoJSON repositories using Leaflet.js  Looking ahead  a Chrome extension for editing  IDE Rioja plans open collaboration on spatial data with GitHub  FME can include links to image data when writing GeoJSON (automatic download service)
  • 18. CONNECT. TRANSFORM. AUTOMATE. Learn More at FME User Conference  Extended Version of this topic will be presented at the FME International User Conference
  • 19. CONNECT. TRANSFORM. AUTOMATE.CC BY-SA 3.0 Tony Nordin FME Server and the Gävle Data Portal Gävle, Sweden
  • 20. CONNECT. TRANSFORM. AUTOMATE. FME Server and the Gävle Data Portal  Peter Jäderkvist, GIS Developer & FME Certified Professional, Community Development Gävle  Provides services and centralized workspace organization, FME usage tracking  Dynamic forms via client communication with FME Server REST API An evolving UI: Peter recently added upload an irregular polygon to clip
  • 21. CONNECT. TRANSFORM. AUTOMATE. Various Maps to DWG  Most popular workspace  Map type (5), contours, metadata, AutoCAD version  XML geometry + parameters triggers FeatureReaders  SchemaMapper, clip & output Example output DWG basemap
  • 22. CONNECT. TRANSFORM. AUTOMATE. Specialty DWG Requests  Custom workspaces generate specialty DWG output for other users  Water & sewer mains for local water company  Power distribution grid for local provider
  • 23. CONNECT. TRANSFORM. AUTOMATE. 3D Model to PDF, Sketchup or DWG  Output: Sketchup 8, 3D-PDF and DWG  Add streets and water, yes/no  Drape roof tops with aerial photography, yes/no  Drape elevation model with aerial photography, yes/no  Add roof models if they exist, yes/no  Some buildings don’t have heights, a parameter decides how to treat those, e.g. “extrude by 7 meters”
  • 24. CONNECT. TRANSFORM. AUTOMATE. 1. all parameters set to yes except for “add roof models”. 2. all parameters set to no. 3. streets water and roof models set to yes Example output sketchup files 1 2 3
  • 25. CONNECT. TRANSFORM. AUTOMATE. Reprojection Services  On-demand coordinate reprojection  File reprojection with error checking and format conversion
  • 26. CONNECT. TRANSFORM. AUTOMATE. FME Portal Job History  Job details written to history database  Over 2100 run since launch  Web app shows usage
  • 27. CONNECT. TRANSFORM. AUTOMATE. Linear Referencing and Pipe Video with FME Los Altos, CA, USA
  • 28. CONNECT. TRANSFORM. AUTOMATE. Linear Referencing and Pipe Video with FME  Amanda Graf and Raymond Kinser, FME Certified Professionals, California CAD Solutions  Challenge: Map and share non-spatial inspection video footage of all sewer lines for the City of Los Altos.  Approach: Use FME and linear referencing methods to QA and position video, creating an automated, repeatable process.
  • 29. CONNECT. TRANSFORM. AUTOMATE. Data QA Issues  No spatial coordinates or geometry  Data inconsistencies across video data vendors and databases  Differences between measured pipe lengths from the vendors and the City  Inconsistent data entry of defect types
  • 30. CONNECT. TRANSFORM. AUTOMATE. Data Cleanup & Homogenization  Filter for unwanted and bad data  Time stamp formatting  Defect notation standardization  Match to best known good City records  QA for flow direction  Catch issues for manual intervention
  • 31. CONNECT. TRANSFORM. AUTOMATE. Geometry Creation  Adjust video session data for best pipe length  Adjust for directionality (video with/against flow)  Create geometry using linear measures, chopper, and NeighborFinder
  • 32. CONNECT. TRANSFORM. AUTOMATE. Video Data Sharing
  • 33. CONNECT. TRANSFORM. AUTOMATE. Results  Easy access to data for all  Future processing of new observation video automated  City saves money on future contracts
  • 34. CONNECT. TRANSFORM. AUTOMATE. Tableau Dataset Creation Birmingham, UK
  • 35. CONNECT. TRANSFORM. AUTOMATE. Tableau Dataset Creation  Dami Sonoiki, FME Certified Professional, Dotted Eyes (Miso)  Problem: Tableau does great data visualization, but lacks good mapping capabilities  Solution: Use FME to break down polygons
  • 36. CONNECT. TRANSFORM. AUTOMATE. Geometry Manipulation  Separate individual boundaries with Deaggregator  Generalize and reduce vertices  Deal with donuts  Produce OGC Well Known Text values for polys
  • 37. CONNECT. TRANSFORM. AUTOMATE. String Manipulation  Format WKT values to extract coordinate strings  StringConcatenator appends _part_number supplied by Deaggregator with Code_Count to provide unique ID PolygonPart  PolygonPart defines Detail for Tableau reconstruction
  • 38. CONNECT. TRANSFORM. AUTOMATE. List Creation  ListExploder and ListIndexer create x,y coords for each polygon  Tableau-ready format
  • 39. CONNECT. TRANSFORM. AUTOMATE. Address Point Frontage Movement Australia
  • 40. CONNECT. TRANSFORM. AUTOMATE. Address Point Frontage Movement  Rajesh Dhull, FME Certified Professional & Senior Data Engineer, Data Development Asia – Pacific, Pitney Bowes Software  Problem: Addresses are pinpointed by lot centroids, but services are provided at the street.  Solution: Create a value- added, dynamic geocoding dataset with addresses located at the front of the property. It’s (almost) always best that your taxi arrives at the front door rather than the living room.
  • 41. CONNECT. TRANSFORM. AUTOMATE. Requirements  Close to 14 million address points need to be moved to a new position – property frontage.  The process should be robust, reliable and repeatable every quarter.  The process should be able to handle heavy datasets.  The process should be able to fit in the existing processes smoothly and should not lead to extra times or delays in the product releases.  Source address points in Oracle, referential data (boundaries, streets) in MapInfo Tab files
  • 42. CONNECT. TRANSFORM. AUTOMATE. The Approach 1. Create state-wise views in oracle as handling 14 million records in 1 process is not desirable. 2. Create single FME workspace for frontage movement process for states with smaller datasets. 3. Split this process in smaller manageable processes for states with bigger datasets as FME performance varies greatly based on the size of the datasets.
  • 43. CONNECT. TRANSFORM. AUTOMATE. FME Workflow Overview Filtered, Buffered Roads Lot Boundary Polygons Candidates for movement Pull address centroids from Oracle Update Oracle
  • 44. CONNECT. TRANSFORM. AUTOMATE. Output  14 Million points processed each quarter, automatically.
  • 45. CONNECT. TRANSFORM. AUTOMATE. Railway Platform Profiling Brno, Czech Republic Photo Credit: Roman Báča, CSmap
  • 46. CONNECT. TRANSFORM. AUTOMATE. Railway Platform Profiling  Rudolf Stastny, FME Certified Professional, CSmap, s.r.o.  Challenge: Process hundreds of railway platform profile DXF files derived from laser scans to look for areas outside tolerances (preventing collisions)  Solution: Automate it with FME
  • 47. CONNECT. TRANSFORM. AUTOMATE. Platform Profiles
  • 49. CONNECT. TRANSFORM. AUTOMATE. Point Selection
  • 51. CONNECT. TRANSFORM. AUTOMATE. Telco Spatial Data Portal United Arab Emirates Telco Spatial Data Portal
  • 52. CONNECT. TRANSFORM. AUTOMATE. Telco Spatial Data Portal  Business Requirement: A Telecom customer wanted a web portal for secure internal data sharing/downloading.  Layer and coordinate system selections needed  Sources included imagery, vectors, and proprietary data, updated daily by external contractors
  • 53. CONNECT. TRANSFORM. AUTOMATE. System Architecture Secure access ArcGIS Server Geodata base FME Download Page FME Server Firewall Users
  • 54. CONNECT. TRANSFORM. AUTOMATE. Secure Interface
  • 55. CONNECT. TRANSFORM. AUTOMATE. FME Server Processing  Single workspace with Custom Transformers  Geodatabase Reader  Bounding Box  create  Clip  Write to choice of format and projection
  • 56. CONNECT. TRANSFORM. AUTOMATE. Budapest, Hungary Laser Scanning Roads and FME
  • 57. CONNECT. TRANSFORM. AUTOMATE. Laser Scanning Roads and FME  Gyula Sz. Fekete, Head of GIS Development and Data Production, BKK Közút Zrt. (a company of the Municipality of Budapest) 1. Management of Mobile Laser Scanning (MLS) missions and post-processing 2. Data conversion from CAD-based data capture system to Oracle ArcSDE GDB 3. Point cloud data analysis
  • 58. CONNECT. TRANSFORM. AUTOMATE. MLS Mission Management  Aim  visualize MLS (Mobile Laser Scanning) trajectories  locations of MLS projects  attribute information of each scanning project – project metadata  (scanner, driver, acquisition time, etc.)  positions of all exposed images  attribute information of each images comes from image header information.  provide a GDB where post-processing steps can be visualized and modified on a WebGIS GUI.
  • 59. CONNECT. TRANSFORM. AUTOMATE. Source Data  MLS Trajectory Data  Riegl MLS Project Log File  Image Headers  Post Processing Workflow Tasks
  • 60. CONNECT. TRANSFORM. AUTOMATE. Output  GDB with -  Trajectory information  Image information  Post-processing workflow tasks  WebGIS GUI with editable workflow tasks
  • 61. CONNECT. TRANSFORM. AUTOMATE. CAD to 3D Geodatabase Conversion  DGN + MDB  Tables linked to DGN geometry
  • 62. CONNECT. TRANSFORM. AUTOMATE. CAD to 3D Geodatabase Conversion
  • 63. CONNECT. TRANSFORM. AUTOMATE. Point Cloud Analysis  Find road surface errors based on MLS scanned 3D point clouds  Generate vector data to be used for further spatial analysis  Read: 3D point clouds and parameters
  • 64. CONNECT. TRANSFORM. AUTOMATE. Analyze & Write: Road Surface Errors
  • 65. CONNECT. TRANSFORM. AUTOMATE. Analyze & Write: Rugs
  • 66. CONNECT. TRANSFORM. AUTOMATE.CC BY-SA Juhanson Belgium Comprehensive Waterways Data QA
  • 67. CONNECT. TRANSFORM. AUTOMATE. Comprehensive Waterways Data QA  Rob Vangeneugden, FME Certified Professional, GIM nv  Challenge: Simplify and automate a complex data validation process for waterways authorities  Solution: Create a Django user interface and use FME Server to validate, manage results, and perform database updates
  • 68. CONNECT. TRANSFORM. AUTOMATE. The Project  Spans multiple waterways authorities  3 primary workspaces  9 embedded custom transformers  27 linked custom transformers  +/- 3000 transformers
  • 69. CONNECT. TRANSFORM. AUTOMATE. Custom Transformers  Uses both linked and embedded  Each data type has a specific custom transformer that identifies Update/Insert/Delete by comparing geometry and attributes to operational tables:  Terminal  Bridge  Bollard  Fairway  Berth  Node  Lock  Lock Chamber
  • 70. CONNECT. TRANSFORM. AUTOMATE. Using Parameters  Published –  Passed by Django application  Format-specific (3-GML, 9-shape) and user credentials, verify authority  Private –  PostGIS connections  Schema parameters  Output location
  • 71. CONNECT. TRANSFORM. AUTOMATE. Database Updates Example update database process (lock chamber)
  • 72. CONNECT. TRANSFORM. AUTOMATE. Benefits  Central storage  Divided management  Detailed validation feedback  Summary table  Geographic files (downloads)  Full update history  Easy to expand (data formats, validation rules…)  Fast data update / Up-to-date database
  • 73. CONNECT. TRANSFORM. AUTOMATE. Thank You!  Questions?  For more information:  