A nested grid for INSPIRE Orthoimagery and gridded data Guillermo Villa. IGN Spain April 2016.

Slides:



Advertisements
Similar presentations
A predictive model for frequently viewed tiles in a Web map Sterling Quinn MGIS Candidate ESRI ArcGIS Server Product Engineer Mark Gahegan Faculty Advisor.
Advertisements

Concurrent Web Map Cache Server Zao Liu, Marlon Pierce, Geoffrey Fox Community Grids Laboratory Indiana University.
Advanced Information Systems Laboratory Department of Computer Science and Systems Engineering Müesteraner GI-Tage 03 GIS COTS.
Cadcorp SIS ® - Spatial Information System ® Normes de OGC: Passé, Présent et Futur Martin Daly Technical Director Cadcorp Ltd SIG et Interopérabilité.
NDIIPP Project Update NC Geospatial Data Archiving Project (NCGDAP) North Carolina State University Libraries North Carolina Center for Geographic Information.
Portraying Earth Data types File types
Applied Cartography and Introduction to GIS GEOG 2017 EL
InSAR Data and GeoServer IU QuakeSim Team October 26, 2011.
Development of a database of intensively monitored groundwater systems in Australia Barry Croke National Centre for Groundwater Research and Training Australian.
Mercator/Coronelli ArcGIS Server 9.3 Data Management GIS Web Services Mapping Application Developer Tools Spatial Analysis Publishing to Clients Image.
Raster Data in ArcSDE 8.2 Why Put Images in a Database? What are Basic Raster Concepts? How Raster data stored in Database?
Gunnar Misund1 REAL TIME MANAGEMENT OF MASSIVE 2D DATASETS Gunnar Misund.
So What is GIS??? “A collection of computer hardware, software and procedures that are used to organize, manage, analyze and display.
Introduction to ArcGIS for Environmental Scientists Module 2 – GIS Fundamentals Lecture 5 – Coordinate Systems and Map Projections.
LizardTech Geospatial Products April, LiDAR Compressor Compress point cloud data to MrSID Generation 4 (MG4) Lossless 25% of the original size.
Prepared by Abzamiyeva Laura Candidate of the department of KKGU named after Al-Farabi Kizilorda, Kazakstan 2012.
Considerations: –Unzip data –Data in Digimap – what data formats? –Data conversion –Applying a style to the data Desktop sharing – Working with OS MasterMap.
1 - 50 Web Service and Geographical Information Integration —— Peking Spatial Applications Integrating Infrastructure, A Research.
Sharing imagery and raster data in ArcGIS
January 25, th APAN Meeting in Bangkok 1 Development of NOAA and Landsat Image Server using Web Map Service Mr. Sarawut Ninsawat and Dr. Kiyoshi.
NASA World Wind Java SDK 3D Earth in Your Applications and Web Pages
Creating Web based Thematic Maps using Open Source Platforms 2009 Ohio GIS Conference September 16-18, 2009 Crowne Plaza North Hotel Columbus, Ohio 2009.
Karl Hennermann School of Environment and Development Session 2: What you absolutely need to know about spatial data Geographic Information Systems.
Ign.fr 23/06/2014. ign.fr THE FRENCH GEOPORTAL GI STANDARDS APPROACH 23/06/2014.
Unidata’s TDS Workshop TDS Overview – Part II October 2012.
The OpenGIS Consortium Geog 516 Presentation #2 Rueben Schulz March 2004.
Data Scrounging 101 Steve Signell, Instructor Robert Poirier, TA School of Science Rensselaer Polytechnic Institute Monday,
MapServer Support for Web Coverage Services Stephen Lime - Minnesota DNR Dr. Thomas E. Burk - University of Minnesota MUM Ottawa, Canada.
The world of RASTER data Modeling... Elevation....etc. The Spatial Analyst Extension.
Esri UC2013. Technical Workshop. Technical Workshop 2013 Esri International User Conference July 8–12, 2013 | San Diego, California Caching Imagery Using.
Introduction to CacheWorx Lucian Plesea - Esri Robert Jensen - Esri.
Scalable Web Server on Heterogeneous Cluster CHEN Ge.
“OnEarth” WMS Server WMS Global Mosaic Lucian Plesea Jet Propulsion Laboratory California Institute of Technology.
By Millie and Ellece. D IFFERENT T YPES OF G RAPHICS Bitmap Formats JPEG GIF PNG PSD TIFF.
GEOG 2007A An Introduction to Geographic Information SystemsFall, 2004 C. Earl A model is a ‘synthesis of data’ + information about how the data interact.
Geospatial Interoperability Jeff de La Beaujardière, PhD NASA Geospatial Interoperability Office.
RSISIPL1 SERVICE ORIENTED ARCHITECTURE (SOA) By Pavan By Pavan.
U.S. Department of the Interior U.S. Geological Survey Exploring New Ground Data Sources GFSAD30 April 2015 Meeting Justin Poehnelt, Student Developer.
GIS in the cloud: implementing a Web Map Service on Google App Engine Jon Blower Reading e-Science Centre University of Reading United Kingdom
Predicting popular areas of a tiled Web map as a strategy for server-side caching Sterling Quinn.
Geodata conversion & interoperability Dr Nigel Trodd Coventry University.
Introduction to Geographic Information Systems
Structure: Overview Geocoding Coordinate System Overlays Conclusion Questions November 07 Computational Aspects of GIS Oliver Walzer Analyzing Google Maps.
Serving society Stimulating innovation Supporting legislation Proposal for a new MIWP action on GML-related aspects Michael Lutz MIG-T.
ORNL DAAC SPATIAL DATA ACCESS TOOL Open Geospatial Consortium (OGC) Services Bruce E. Wilson Suresh K. Santhana Vannan Yaxing Wei Tammy W. Beaty National.
Serving society Stimulating innovation Supporting legislation INSPIRE Thematic Cluster on Elevation, Orthoimagery, Reference systems.
What’s new at ArcGIS for INSPIRE Roberto Lucchi Guenther Pichler.
Uploading Data Matthew Hanson  GeoNode made up of several components  Web Framework – Django  OGC Server – GeoServer  Database – PostGIS.
Serving society Stimulating innovation Supporting legislation INSPIRE Thematic Cluster on Land Cover and Land Use - State of Play.
GeoServer Prof. Wenwen Li School of Geographical Sciences and Urban Planning 5644 Coor Hall
SSE WebMapViewer Recent Developments Steven Smolders SSE Workshop ESA - ESRIN, Frascati, Rome.
® Sponsored by Improving Access to Point Cloud Data 98th OGC Technical Committee Washington DC, USA 8 March 2016 Keith Ryden Esri Software Development.
Geospatial Data Abstraction Library(GDAL) Sabya Sachi.
Defence Geospatial Information Working Group (DGIWG) P5: Geospatial Web Services Program Proposed Extension for Multi-resolution Vector Data in OGC GeoPackage.
Best Practices for Managing and Serving Lidar and Elevation Data Cody Benkelman.
MOBILE AND DISCONNECTED FIELD DATA COLLECTION
Components People Technology Policies Standards Spatial Data.
Distributed Cache Technology in Cloud Computing and its Application in the GIS Software Wang Qi Zhu Yitong Peng Cheng
Data Sharing We all need data
Jordi Escriu - facilitator
COORDINATE SYSTEMS AND MAP PROJECTIONS
Pushing implementation of European coverage data and services forward
Issues implementing INSPIRE coverages
Problems with INSPIRE WMS
Implementation of INSPIRE Coverages
Workshop “TRANSFORMATION OF THEMEs EL and OI”
Jordi Escriu - facilitator
SDI from a technological perspective: Standards
Creating Digital Graphics
Michael L. Dennis, RLS, PE G67940_UC15_Tmplt_4x3_4-15
Presentation transcript:

A nested grid for INSPIRE Orthoimagery and gridded data Guillermo Villa. IGN Spain April 2016

1. Efficient visualization -> “cached” tiled services The most efficient web visualization of raster data is achieved through “cached” “tiled web services” (e.g. WMTS) The same is true for rasterized maps People is used to this kind of performance and no longer accept the slowness of “non- tiled” services (e.g. WMS)

2. Tiling Schemas and nested grids A “tiling schema” is necessary to obtain a coherent multiresolution coverage of an area An optimal tiling schema should be a nested grid: a space allocation schema that assures completely coherent and consistent multiresolution coverage of the whole working area by organizing image footprints, pixel sizes and pixel positions at all pyramid levels.

3. Web Mercator: “de facto” standard projection In the last times a “de facto” standard has emerged in web mapping: “Web Mercator” projection (EPSG:3857) It is used and supported by a great number of geospatial data and API providers ( e.g. Google, Microsoft, ESRI,…) and very important Open Source and Open Data initiatives (Open Street Maps, Mapbox, etc.)

The reasons for this massive adoption are multiple: -Almost conformal: locally maintains the shapes of objects that have a natural aspect at all latitudes (e.g: buildings, roundabouts) -Rectangular : allows the whole Earth (or the biggest part of inhabited areas) in one single square tile -No different zones. One single projection -North is always straight up (Geographic North equal projection North) -Very efficient “Quad-tree” computation rectangular buildings look rectangular, not rhomboidal as in geographic projection roundabouts look round not ellipsoidal

4. OGC Standard: WMTS Simple Profile WMTS Simple Profile has recently been approved as official OGC standard. The objective is to solve the frequent incompatibilities between different implementations of WMTS standard. It defines Web Mercator as compulsory map projection It defines a tiling schema: “GoogleMapsCompatible Tilematrixset” This tiling schema is a nested grid. Most of the requests that WMTS services receive are for Web Mercator tiles, so they are “obliged” to support it

It is much more efficient to produce raster datasets thinking on tiled services publication right from the beginning In this way, we avoid a lot of problems: ‐ empty wedges ‐non aligned pixels ‐multiple reprojections ‐multiple resamplings ‐multiple compression and storage processes, etc. Light web clients do not reproject or resample on the fly, so in order to be able to overlap several web layers in one light web client, all data sources must be in the same projection and the have the same pixel sizes and positions 5. Interoperability of Map Projections

6. Proposals for Inspire Data Specifications (I) Web Mercator is not among map projections allowed by Inspire In order to assure interoperability with a high number of tiled web services, the list of recommended Spatial Reference Systems should include Web Mercator Data Specifications recommend a common grid (Zoned Geographic Grid) for Orthoimagery and Elevation (Annex D of both DS). However, it does not include a tiling schema In order to assure interoperability of different datasets and efficient tiled web services, we propose to include WMTS Simple Implementation tiling schema in the list of recommended common grids for IO and EL

7. Problem of the huge number of WMTS tiles WMTS services require a huge number of tiles: hundreds of millions of individual “tiny” 256x256 JPEG files must be produced (either pre-cached or “on the fly”) in one or several “projections” These tiles are very difficult to manage in current computing environments, because operating systems are not prepared for such a large number of files. A possible solution is to store many of the 256x256 tiles “inside” a bigger file: TiledTIFF (internal file-based tiling) is the best place to store tiles of an WMTS service. We only need to compress them in JPEG. If we generate a TiledTIFF with JPEG compression using the footprints and the pixel sizes of WMTS-SP we obtain WMTS tiles ready to be directly sent without the need to decompress and recompress them before the delivery This approach has already been implemented by Mapserver opensource project (

8. Proposals for Inspire Data Specifications (II) “TiledTIFF” and JPEG compressed TIFF are not accepted in Inspire DS In order to allow this efficient production -> publication workflow, Tiled and JPEG compressed TIFFs should be accepted. “BigTIFF” and “Pyramidal TIFF” should also be accepted in order to ease this workflow.

9. Discussion document Document describing the proposal uploaded to the INSPIRE Thematic Cluster collaboration platform: 29-a-nested-grid-for-inspire-ortoimagesdocx Discussion topic: sability-of-the-zoned-geographic-grid-grid-etrs89-grs80 Look forward for receiving your feedback!