Laserdata i skyen - Geomatikkdagene 2013

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Laserdata i skyen - Geomatikkdagene 2013

  1. 1. Laserdata i skyen Distribusjon og analyserStåle Kristiansen
  2. 2. En frustrert laser-fagansvarlig fra et vilkårlig blomstrende kartleggingsfrima
  3. 3. Agenda• Innledende om støtte for laserdata i ArcGIS• En forvaltningshistorie• En annen forvaltningshistorie• Analyseeksempler (hvis det blir tid)
  4. 4. Overview of LAS Support in ArcGIS 10.1 P Analyze / R Update Data O J E LAS Dataset C LAS Dataset 2 T 1File01.las S LAS DatasetFile02.las… Manage OFile99.las R Serve / Share G AMultiple Files N / Folders Tiled / Overlapping I Extents Z E Mosaic Dataset (Location / Time)
  5. 5. LAS Dataset
  6. 6. LAS Dataset• New data type• File based• Stores references to LAS files on disk• Optionally reference breakline data• Treats a collection of LAS files as one logical dataset
  7. 7. LAS Dataset Strengths• Scalability – Works directly on LAS files• Data Integration – Point cloud and breakline support – Storage efficient• Data Management – I/O efficient – Edit LAS classifications
  8. 8. LAS Dataset – Creation• Interactively via Catalog – File folder context menu• Using scripts and models with geoprocessing tools
  9. 9. LAS Dataset – Analysis• Derive surfaces – As raster – As TIN• Direct surface analysis – Interpolate shape – Add surface information – Line of sight – Skyline – Locate outliers• Rasterize on point metrics – LAS point statistics as a surface
  10. 10. LAS Dataset – LAS File Extents
  11. 11. LAS Dataset – Point display
  12. 12. LAS Dataset – Surface Display
  13. 13. LAS Dataset – Point Filters
  14. 14. LAS Dataset – 3D Display inArcScene Data courtesy Merrick & Co.
  15. 15. Mosaic Dataset• Optimum Model for Image Data Management • Manage • Multiple projects as single dataset • Metadata • Visualize • On the fly representation as surface or point cloud • View as 2D or 3D • Share • As a single dataset • As Image Service • WMS/WCS
  16. 16. Sharing LiDAR Data• Share via ArcGIS Server• An image service – Access – Discover – Download• A map service
  17. 17. LiDAR Data dissemination View and download your source data for further uses http://www.oregongeology.org/dogamilidarviewer/
  18. 18. Rasterdataforvaltning i Geodata• Geodata har opprettet et forvaltningsprosjekt i Amazon• En prosjektgruppe utarbeider «Best Practise» for «alle» typer rasterdataforvaltning • LiDAR • Bilder • Batymetri
  19. 19. En dataforvaltningshistorie – Tenkt scenario Dataleverandør Kunde/Datamottaker Sjef
  20. 20. ...bla bla.....LAS...bla bla Superduper GIS-ekspert
  21. 21. LAS_f02y2007k510s25832_TT0705X_Eidsvoll File geodatabase XML Metadata LAS dataset Original Data LAS SOSI ASCII
  22. 22. Kontroll av dataleveranse
  23. 23. f fMetadata f f
  24. 24. Multiple Elevation Data Sources ConstraintsLAS files LAS Dataset Terrains Raster grids • Catalog of data Mosaic Dataset sources • Contains metadata • Defines processing • Serve to many applications Desktop Web Mobile
  25. 25. Extended Workflow Source Derived: Master Referenced Source Mosaic Mosaic Dataset MosaicImagery Datasets (Use Table Rater Type) Datasets Product 1Collection1 f Product 2 f fColection2 Multi-Product ff fCollection3
  26. 26. f fMetadata f f
  27. 27. Fornøyd fagansvarlig
  28. 28. f f f f ? f f f ? f fMetadata f f
  29. 29. Broen er bygget mellomutilgjengelige laserdata og ArcGIS’funksjonsrike analysebibliotek
  30. 30. Big Data – LiDAR DataManagement and Dissemination in the Amazon Cloud
  31. 31. Case Study – State of Oregon (US)Department of Administrative Services(DAS)• Challenged to Make LiDAR Data Available to Constituents• Need Scalable Solution to Support Data Growth• Ability to Deploy Multiple Content Types• Support Direct Download of Source LAS files• Deploy Web Application to Permit Search & Discover & Visualization
  32. 32. Oregon Hosting Data Statistics • Imagery Data Sources – 2011 3355 Images – 2009 2930 Images – 2005 1913 Images – 2000 1784 Images – 1995 1962 Images • LiDAR data – 49 Projects – 59,680 LAS Files – LAS 1.0 – 1.2 Formats – Multiple Projects, Units – Most data not classified – Some Derived Surfaces (DEM, DSM)
  33. 33. DAS High Level Tasks• Configure & Deploy Temporary Processing Environment in Amazon• Configure & Deploy Hosting Environment in Amazon• Migrate Existing Web App (View & CZS)• Process Source Imagery Data – Author Mosaic Data Sets for Each Epoch – Create Image Caches for Each Epoch, Two Projections
  34. 34. DAS High Level Tasks• Process LiDAR Source Data – Author Mosaic Datasets for LAS Files / Las Datasets – Define Mosaic Functions for LAS Data• Deploy Web Services – 20 Imagery Web Services – 3 Web Services for LiDAR Data • Tinted Hillshade (Bare Earth) • Slope • Aspect – 1 Feature Service for LAS Catalog
  35. 35. DAS Oregon Storage Volumes• Imagery Data Sources – 5 Epochs – 15.5 TB• LiDAR – Raw LAS Data required for CZS Application • Raw Data = 23 TB • Bare Earth Surface as DEM Raster (400 GB) • Raster Size Depends on Post Spacing • Panchromatic Raster • Mosaic Data Set
  36. 36. Amazon Cloud Components Simple Elastic EBS Amazon Config Storage Block Snapshot Machine OperationService (S3) Storage (EBS) (S3) Instance Buckets Volumes (AMI) (1 TB Max) S/S Source Scaled Internet S3 Object Object Key Data Instances (5GB Limit)Transport
  37. 37. DAS Oregon Delivery Architecture Options Cache http S3 S3 Web Service https S3 S3 API Service Browser Web Server Image As DAS Service EBS EBS EBS Limit 7 TB PerSource Server Map (xvdb – xvdh) Service EBS EBS EBS Uses WMS Windows Client Service EBS Shares ArcGIS Server As Lustre ImageCache EBS … EBS No Limit Shared FS Service Map EBS … EBS Extensible Uses Samba for Windows Service WMS EBS … EBS Clients Or Lustre LFS Hosts ArcGIS Server Service Client for Linux
  38. 38. Hvorfor Amazon Cloud?• Kostnadsreduserende – Mindre driftsbemanning – Ikke alle kostnadene up-front• Skalerbarhet• Sikrere oppetid• Fleksibilitet ift trafikk auto-oppskalering på peakbelastning• Enklere prosjekt da IT-rammeverket er klart
  39. 39. Eksempler på analyser
  40. 40. Sun analysis – World Championchip inHolmenkollen
  41. 41. Sun analysis – World Championchip inHolmenkollen
  42. 42. Supporting Hurricane Preparations
  43. 43. Building Footprints and Finished Floor Elevations100YR Flood Elevation = 13 ft. FFE = 5.2 ft.
  44. 44. Damage Assessments
  45. 45. Emergency managementPotential tsunami inundation: Bandon, Oregon Data courtesy of DOGAMI
  46. 46. Takk for meg

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