The document provides guidance for a project to implement 3D visualization and analysis tools in an open source web GIS. It outlines objectives to render local terrain data and 3D building models in a web GIS, and develop 3D analysis tools. It describes related work in terrain visualization and 3D city models. Methods discussed include using SRTM data to create terrain tiles, developing techniques to dynamically render 3D building models, and algorithms for terrain profiling and viewshed analysis. The results demonstrate terrain and 3D models rendered on a local server and profile/viewshed tools. Limitations and potential for future work are also discussed.

1. Project Guidance,
Shri M. Arulraj
Manager,
Bhuvan Web Services Development,
NRSC Hyderabad
Presented by,
Parthesh B.,
IIST, Trivandrum

2. 1. Objectives
2. Related Work
3. Methods
4. Results
5. Discussion
6. Conclusions
7. References
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3.  To implement method to render local terrain data
on server side to be made 3D visualisable in
Open Source Web GIS at client side.
 To develop a method to visualise 3D models of
built structures in Open Source Web GIS
dynamically, hierarchically and with speedy
rendering.
 To develop 3D GIS analysis tools for Open Source
Web GIS.
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4. 4

5. Related Work:
 STK-terrain[1] service is provided by Analytical Graphics
Inc. which uses a combination of multiple sources like
NED, EU-DEM, USGS-SRTM, CGIAR-SRTM and GTOPO30.
 3D CityDB webclient[2] facilitates interactive 3D
visualization and exploration of large semantic 3D city
models.
 Geocontext Profiler[3] which is an online resource which
allows to make topographic profiles anywhere on Earth in
the seabed and ocean floor. Various scientific graphs are
available such as Median line, Trend Line, First fresnal
zone, etc.
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6. 6
Fig. STK-terrain example [2]

7. 7
Fig. 3D cityDB web client

8. 8
Fig. Geocontext Online Elevation Profiler

9. 9

10.  SRTM 90m DEM download
◦ Geotiff files downloaded in tiled form for entire globe from
http://www.cgiar-csi.org/data/srtm-90m-digital-elevation-
database-v4-1
◦ Compressed files with total size accounting to around 57 GB
 Mosaic operation
◦ All the uncompressed tiles of Geotiff DEM files were mosaiced using
“Mosaic Images” tool
◦ The final size of the mosaiced global DEM Geotiff file was around 125
GB
 Create Image Pyramid using gdal
◦ Using gdal_retile[4] tool image pyramid was created with parameters:
 Resampling method: Bilinear
 Levels: 6
 Pixel Size: 1024 x 1024
◦ Total tiled image accounting to size of around 154 GB
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11.  Geotifftranslate Utility
This utility is included in the GTP[5] plugin and was used to convert
“int16 grayscale” images to “int8 RGB” geotiff images from the image
pyramid.
 Used GeoserverTerrainProvider(GTP) javascript plugin
 Cesium Terrain Provider (javascript)
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Fig. Image Pyramid Layer of RGB DEM in Geoserver

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Fig. Terrain rendered on local server

13. 13
Fig. Flowchart for dynamics creation
of 3D models of buildings

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Fig. CZML[7] code snippet for a single building

15. 15
Fig. 3D models of buildings rendered on
Local server within bounding box

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Class Limits Colour
Class 1 36.38m < Building ht.<= 172m
and Footprint area > 150sq.m,
Dark Orange
Class 2 21.58m < Building ht.<=36.38m
and Footprint area > 150sq.m
Orange
Class 3 9.85m < Building ht <= 21.58m
and Footprint area
Green
Class 4 Building height <= 9.85m and
Footprint area > 150sq.m,
Dark Green
Table. Classification of 3D building models

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Level Camera Altitude Classes included
Level 1 2000m < Camera Height<= 5000m Class 1
Level 2 1000m < Camera Height<= 2000m Class 2
Level 3 Camera Height<=1000m Class 3 and Class 4
Table. Hierarchy of 3D building models

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20. 20
Fig. Flowchart to create Terrain Profile

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22. 22
Fig. Flowchart for Viewshed analysis

23. Algorithm used in the QGIS plugin “Viewshed Analysis”[7]:
1. Parameters used are:
i. Observation point location
ii. Observer height
iii. Target height
iv. Viewshed Radius
v. Earth Curvature (Boolean) - optional
vi. Atmospheric refraction - optional
2. The perimeter pixel positions of the viewshed area are identified.
3. The target pixels’ positions are stored in a matrix.
4. Rays are casted from centre of viewpoint pixel to the pixels on the
perimeter.
5. Based on angle calculations, visibility is decided for each pixel in
binary and a visibility matrix is created.
6. Based on this visibility matrix, Binary Viewshed Raster is created.
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Fig. Horizontal error
Fig. Ray casting
Fig. Line of sight anatomy

25. Sr. No. Type Software
1 Servers Apache Tomcat, Web Server in
Bhuvan, XAMPP Apache during
development, Geoserver
2 Database PostgreSQL 9.1 + PostGIS 2.0
3 Libraries Cesium-1.20 javascript lib.,
GDAL and OGR python libs.
4 Programming Languages Javascript, PHP, HTML, Python,
cURL
5 Packages QGIS Essen
6 OS Windows-7 64-bit used for
development
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Fig. List of software used while development

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29. 29
Fig. Screenshot of hilly area in Bhuvan 3D

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Fig. 3D models rendered in Bhuvan 3D at location Powai, Mumbai

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Fig. Level 1 of 3D models
2000m < Camera Ht. <= 5000m
Fig. Level 2 of 3D models
1000m < Camera Ht. <= 2000m
Fig. Level 1 of 3D models
Camera Ht. <= 1000m

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Fig. Choice of points for terrain profile in Bhuvan 3D

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Fig. Terrain profile plotted for path created from selected points

34. 34
Fig. Terrain profile data downloaded as text file

35. 35
Fig. Far view of the entities created on Cesium globe
corresponding to parameters for viewshed analysis chosen

36. 36
Fig. Close view of entities created

37. 37
Fig. Binary Viewshed Raster
Observation
Point
Parameters:
1. Observer Height: 150m
2. Target Height: 1.6m
3. Radius: 5000m

38. 38
Fig. Far view of the draped vector layer of the visible region
from observation point with given parameters

39. 39
Fig. Close view of the viewshed analyzed area

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41.  Choice of DEM used for terrain data is merely
experimental and updating DEM source is on the
roadmap.
 High res. of DEM will need more number of levels
to be created in image pyramid which in turn
asks for more tiles to be transferred from server.
 Performance of terrain loading depends on the
web service used such as WMS, WMTS, TMS etc.
 Terrain Profile will be accurate if process is
initiated after the terrain tiles are loaded.
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Property Open Source 3D
Terrain Profile
Geocontext Terrain
Profile
Sampling
Distance
> (Total Dist./5000) (Total Dist./512)
Selection of
points
By mouse click only Mouse click, KML or GPX
import
Path
Visualization
3D 2D
Other Scientific
Graphs
NA Median line, Trend line
and First Fresnal Zone.
Elevation for
Oceanic region
NA Seabed
Table. Comparison of Geocontext Profiler and Developed Open Source 3D Terrain Profile

43.  Zonal Statistics was performed on the
building footprints shapefile to get elevation
data for each building. But the models are not
exactly seated on the terrain. This
observation points to two possible reasons.
◦ The draping of terrain is not occurring accurately
due to either ambiguity in GeoserverTerrainProvider
or rendering process of Cesium itself OR
◦ There is some issue with the parsing of CZML
scripts in Cesium
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Fig. Floating models even after using elevation used by performing
Zonal Statistics on the polygon shapefile

45.  All the proposed methods have been successfully implemented.
 3 out of the 4 proposed methods are being used by Bhuvan 3D platform and the
4th method is also on the verge of being applied.
 Except the Terrain rendering method, other 3 methods are genuinely created with
no such implementation found anywhere else during research.
 The implemented system can be further modified to include more analysis tools
like analysis of 3D models (proximity, volume, etc.), solar potential mapping,
cumulative viewshed, etc.
 Since the applications developed with the use of Cesium library heavily use
graphics, both client and server side processing amount should be balanced.
 There is need of better standardization of 3D models’ data types and modeling
methods so that cross-platform compatibility could be achieved.
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46. 1. STK world terrain (http://cesiumjs.org/data-and-assets/terrain/stk-world-terrain.html)
2. Cloud-based 3D Web Client based on 3D City Database: By Chair of Geoinformatics, Technische Universität
München.(http://www.3dcitydb.net/3dcitydb/fileadmin/3DWebClient/index.html)
3. Geocontext Profiler (http://www.geocontext.org/publ/2010/04/profiler/en/)
4. gdal_retile (http://www.gdal.org/gdal_retile.html)
5. Geoserver Terrain Provider plugin https://github.com/kaktus40/Cesium-GeoserverTerrainProvider
6. QGIS Plugin “Viewshed Analysis algorithm ” http://hub.qgis.org/wiki/viewshed/Algorithm
7. CZML data format https://github.com/AnalyticalGraphicsInc/cesium/wiki/CZML-Structure
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