Www.geongrid.org CYBERINFRASTRUCTURE FOR THE GEOSCIENCES Image processing, LiDAR and high resolution 2D interpolation and 3D visualization for data integration

www.geongrid.orgCYBERINFRASTRUCTURE FOR THE GEOSCIENCES

Image processing, LiDAR and high resolution 2D interpolation and 3D visualization for data integration

J Ramón Arrowsmith Department of Geological Sciences, Arizona State University, [email protected] http://activetectonics.la.asu.edu/GEONatASU/index.htm

http://www.geoinformaticsnetwork.org/swgeonet/

With Jeff Conner, Chris Crosby, and Gilead Wurman


Java servlets on ASU GEON NODElservlet

gservlet

imsservlet

logservlet


http://asterweb.jpl.nasa.gov/

Very useful data, but difficult to locate appropriate scenes, acquire, process and manipulate data for many users.

So, we built a system to do “on-the-fly” processing and delivery in a variety of useful formats


ASTER level-1B data have had system radiometric corrections and geometric coefficients applied and are reprojected to a given map projection. 2300 images and counting.


Connection Method• ArcIMS, Java Servlet, Manager Program,

Java Implemented Server


Java Servlet – Welcome Screen

Display information to user and communicates with the Manager program, relaying relevant information


Java Servlet - Results Screen

Display results of IDL processing to user and offer for download processed information (thumbnail and larger *.jpg; *.tar.gz contains full and 8x reduced GEOTIFF [*.tif and *.tfw])


CIR = 3, 2, 1 as Red-Green-Blue (RGB) at 15 m/pixel. Actively photosynthesizing vegetation is red (near-infrared band). Undisturbed bedrock and soils appear as browns, greens, and greys. Built materials and regions typically exhibit blue-green, reddish - purple, and white colors.

Downloaded GEOTIFF in ArcScene with DEM base heights.


Users besides ASU: University of New Mexico, University of Nevada Las Vegas, Mesa State University, Texas A&M University, US Forest Service, NASA, University of Arizona, Los Alamos National Laboratory, US Geological Survey, Wisconsin Charter School, University of Nevada Reno Desert Research Institute, Southwest Research Institute

+40 in May



http://agassiz.la.asu.edu:8080/gservlet



LIght Detection And Ranging• Airborne scanning laser

rangefinder• Differential GPS• Inertial Navigation System

30,000 points per second at ~15 cm accuracy

• $400–$1000/mi2, 106 points/mi2, or 0.04–0.1 cents/point

Extensive filtering to remove tree canopy (virtual defor-estation)

Figure from R. Haugerud, U.S.G.S - http://duff.geology.washington.edu/data/raster/lidar/About_LIDAR.html


LiDAR data handling and processing - the challenges

• Huge datasets:

– 8.79 million pts

– Files getting larger with higher pulse rate instruments

• How do we grid and distribute these data?– ArcGIS can’t handle it

easily– Expensive commercial

software not an option for most data consumers

Hector Mine Earthquake ALSM coverage (Mojave Desert)




GRASS as a processing tool for LiDAR

• GRASS: Open source GIS– Interpolation commands designed for large data sets– Splines use local pt density to segment data into

rectangular areas for interpolation– Can control spline tension and smoothness

• Modular configuration could be easily implemented with in the GEON work flow– EX: User uploads point data to remote site where

GRASS interpolation module runs on super computer and returns user a raster file.

• Ultimately a gridding utility for all large, computationally intensive data - gravity




lservlet performance

0:00:00

2:24:00

4:48:00

7:12:00

9:36:00

12:00:00

0 500,000 1,000,000 1,500,000 2,000,000

# of data points

proc

essi

ng ti

me

(hrs

:min

:sec

)

idw

spline v2

all functions


What’s next?• Build projection library• Add functionality - TIN, Kriging, “Oskin”-type local plane fits, etc.• More performance testing• Comparison of interpolation algorithms for different landscapes• Migrate to SDSC HP cluster for improved performance• Database import and query

•Ties to NCALM and Earthscope

•Web-based front end for data distribution

San Andreas Laser Scan (Bevis, Hudnut)


Current Architecture Web Services Architecture

• JSPs

• Socket Connections

• Messages passed are a custom Java container class.

• Portlets

• SOAP

• Messages passed are XML

Web services become workflow building blocks


Acknowledgements• Colleagues and organizations who have shared data with

us. • This work was supported by the US National Science

Foundation grants: ITR/IM+AP (GEO) Collaborative research: Creation of a geospatial data system for the transition between the Colorado Plateau and the Basin and Range Provinces (Geoinformatics in Action)--EAR-0112960; and ITR Collaborative research: GEON: a research project to create cyberinfrastructure for the geosciences--EAR-0225543.

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Www.geongrid.org CYBERINFRASTRUCTURE FOR THE GEOSCIENCES Image processing, LiDAR and high resolution 2D interpolation and 3D visualization for data integration