Geon 2004 Annual Report: Arizona State University



Geon 2006 Annual Report: Arizona State University

J Ramón Arrowsmith, P.I.

Associate Professor of Geology at Arizona State University

Department of Geological Sciences

Arizona State University

Tempe, AZ 85287-1404, U.S.A.

(480) 965-3541 OFFICE (480) 965-8102 FAX

ramon.arrowsmith@asu.edu

Additional personnel:

Jeffrey Conner—Technical Support Systems Analyst (GEON Node set up and System Administration; Java, Javascript, Apache, and Tomcat programming and implementation)

Chris Crosby (Graduate Research Assistant)—GRASS GIS and LIDAR technology

Web site:

We have significantly upgraded our web site in basic conformity with the other GEON sites.

Presentations

(most are available digitally at ):

Crosby, C.J., Conner, J., Frank, E., Arrowsmith, J R., Memon, A., Nandigam, V., Wurman, G., Baru, C., The GEON LiDAR Workflow: An Internet-Based Tool for the Distribution and Processing of LiDAR Point Cloud Data, Geoinformatics 2006, Reston, VA May 11, 2006.

Crosby, C.J. and Arrowsmith, J R., Utilization of LiDAR / ALSM Point Cloud Data for Earthquake Geology and Tectonic Geomorphic Mapping, Analysis, and Visualization, Presented at the 100th Anniversary Earthquake Conference, San Francisco, CA April 18-21, 2006.

Arrowsmith, J R. and Crosby, C.J., New Looks at Active Faults: Tectonic Geomorphology using Airborne Laser Swath Mapping (ALSM), Presented at the 100th Anniversary Earthquake Conference, San Francisco, CA April 18-21, 2006.

Crosby, C.J., Conner, J., Frank, E., Arrowsmith, J R., Memon, A., Nandigam, V., Wurman, G., Baru, C., The GEON LiDAR Workflow: An Internet-Based Tool for the Distribution and Processing of LiDAR Point Cloud Data, 2006 UNAVCO Science Workshop, Denver, CO.

Crosby, C.J., Conner, J., Frank, E., Arrowsmith, J R., Memon, A., Nandigam, V., Wurman, G., Baru, C., A Geoinformatics Approach to LiDAR / ALSM Data Distribution, Interpolation, and Analysis, Eos Trans. AGU, 86(52), Fall Meet. Suppl., Abstract H31E-1349.

Arrowsmith, J R., 2005a, NEW DIRECTIONS AND CHALLENGES IN TECTONIC GEOMORPHOLOGY, Geological Society of America Abstracts with Programs, Vol. 37, No. 7, p. 313

Arrowsmith, J R., 2005b, TESTING HYPOTHESES ABOUT GEOLOGIC PROCESSES IN THE COLORADO PLATEAU-BASIN AND RANGE TRANSITION ZONE USING AN INTEGRATED GEOSPATIAL DATA SYSTEM, Geological Society of America Abstracts with Programs, Vol. 37, No. 7, p. 204

Crosby, C.J., Conner, J., Frank, E., Arrowsmith, J R., Memon, A., Nandigam, V., Wurman, G., Baru, C., A Geoinformatics Approach to LiDAR / ALSM Data Distribution, Interpolation and Analysis, Southern California Earthquake Center Annual Meeting, Proceedings and Abstracts, v. 15, Palm Springs, CA, September, 2005.

Arrowsmith, J R., Crosby, C.J., Conner, J., Wurman, G., Image processing, LiDAR and high resolution 2D interpolation, and 3D visualization for data integration: GEON Annual Meeting, May 2005, San Diego, CA.

Crosby, C.J., Arrowsmith, J R., Conner, J., Wurman, G., LiDAR data distribution and processing on the GEON Grid – Beyond Proof of Concept: GEON Annual Meeting, May 2005, San Diego, CA.

Publications:

Efrat Jaeger-Frank, Christopher J. Crosby, Ashraf Memon, Viswanath Nandigam, J. Ramon Arrowsmith, Jeffery Conner, Ilkay Altintas, Chaitan Baru, A Three Tier Architecture for LiDAR Interpolation and Analysis, Lecture Notes in Computer Science, Volume 3993, Apr 2006, Pages 920-927, DOI: 10.1007/11758532_123.

Arrowsmith, J R., Active tectonics, tectonic geomorphology, and fault system dynamics: how geoinformatics can help, in Sinha, A. K., ed., Geoinformatics: Data to Knowledge: Geological Society of America Special Paper 397, p. 131{139, doi: 10.1130/2006.2397(09), 2006. [PDF]

Yoburn, J. B., Fouch, M. J., Arrowsmith, J R., Keller, G. R., A new GIS-driven geophysical database for the southwestern United States, in Sinha, A. K., ed., Geoinformatics: Data to Knowledge: Geological Society of America Special Paper 397, p. 249{267, doi: 10.1130/2006.2397(20), 2006. [PDF]

Major activities:

Web-based interaction with datasets and models is essential for knowledge development in Earth Science. We have developed a series of tools for image processing, LiDAR and high resolution 2D interpolation, and 3D visualization for data integration using servlet technologies. Servlets provide a component-based, platform-independent method for building Web-based applications, without the performance limitations of CGI programs.

SWGEONET data server: A tool for interactive inquiry and earth science data delivery for the southern Rocky Mountains GEON testbed. In particular this tool enables the user to interact with diverse earth science data including geology and geophysics, not to mention remotely sense data. The remote sensing data are an important innovation in our delivery system. We had found that it was challenging for "typical" earth scientists to find and process ASTER satellite imagery. The tool enables the user to do just that: find the images of interest and quickly and on the fly produce very usable GEOTIFF output at full and low resolution. While the emphasis of our data collection is the southern Rockies, we do have imagery for the Mid Atlantic testbed, parts of the northern Rockies, and California. We have processed and delivered more than 1400 images in the last year and half or about 2-4 images per day (see figure 1). This tool is also the entry point for a international collaboration (iGEON) with the Japanese colleagues at AIST where Jeff Conner from ASU visited in January 2006 and helped them build similar tools for Japan.

Our image processing tool is accessible from . Through a map interface, a user selects a satellite image footprint, and then invokes the servlet which provides metadata about the image and permits the user to select several processing options (visible-near infrared, normalized difference vegetation index, short wave infrared, and thermal infrared). These choices are bundled and sent to one of the compute nodes on our GEON cluster where image processing is done by IDL, and the results returned with a browse image and full resolution GEOTIFF for download. In order to track usage, we have developed another servlet () that logs the images chosen, the processing options, and privately the IP addresses of the clients (see figure 1). Importantly, we see use of these images by users outside of 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, US Army Fort Bliss, University of Montana, etc.).

Scientific analysis using those data and others from the Colorado Plateau-Basin and Range Transition Zone were presented by Arrowsmith at the 2005 Annual Meeting of the Geological Society of America meeting (Arrowsmith, 2005b; Figure 2). Much of these data were also part of the Active Faulting and Earthquakes in Arizona talk that Arrowsmith developed for outreach.

GEON LiDAR Workflow: LiDAR (Light Distance And Ranging, a.k.a. ALSM (Airborne Laser Swath Mapping)) data is quickly becoming one of the hottest tools in the Geosciences for studying the earth’s surface. Capable of generating digital elevation models (DEMs) more than an order of magnitude more accurate than those currently available, LiDAR data offers geologists the opportunity to study the processes the shape the earth’s surface at resolutions not previously possible (see Figure 3). For more information see these pages: .

Unfortunately, access to these datasets for the average geoscience user is currently difficult because of the massive volumes of data generated by LiDAR. Distribution, interpolation and analysis of large LiDAR datasets, which frequently exceed a billion data-points, present significant computational challenges. We are using a geoinformatics approach to the distribution, interpolation and analysis of LiDAR data that capitalizes on cyberinfrastructure being developed as part of the GEON project. We utilize a comprehensive workflow-based solution that begins with user-defined selection of a subset of point cloud data and ends with download and visualization of interpolated surfaces and derived products.

In this GEON-based workflow (the GEON LiDAR Workflow--GLW), the billions of points within a LiDAR point cloud are hosted in an IBM DB2 spatial database running on the DataStar terascale computer at San Diego Supercomputer Center; a machine designed specifically for data intensive computations. Data selection is performed via an interactive-map interface that allows users to execute spatial and attribute subset queries on the larger dataset. The subset of data is then passed to a GRASS Open Source GIS-based web service that handles interpolation to grid and analysis of the data. Users may choose to download their results in ESRI or ascii grid formats as well as geo tiff. The workflow also feeds into GEON web services in development that will allow visualization of workflow outputs in either a web browser window or in 3D. We have 4 data sets online now (comprising more than 2.5 billion lidar returns with more in the queue). More than 60 users have been registered to use the GLW. Its development and the scientific applications from it are the focus of the M.S. thesis of Chris Crosby at ASU. It will be completed in summer 2006.

In addition, LViz is a tool developed by Jeffrey Conner in the Active Tectonics Research Group at Arizona State University. Designed for 3D visualization of LiDAR / ALSM point and interpolated data, the tool offers import of LiDAR point cloud data (delimited text file) or interpolated surfaces (in ascii or arc ascii grid formats). LViz also offers texture mapping and user control over display settings such as data and background color. LViz was originally written for visualization of outputs from the GEON LiDAR Workflow (GLW) (additional GLW information here) and is designed to run on Windows platforms. Although originally conceived for the 3D visualization of LiDAR data, LViz can be used to view any 3D point cloud data such as seismicity or gravity. LVIZ is available here: .

Additional Activities:

• Arrowsmith developed a major outreach talk: Active Faulting and Earthquakes in Arizona, which was first presented to the Arizona Geological Society September, 2005. It has subsequently used in numerous talks across Arizona and New Mexico by various colleagues. See figure 2.

• ASU team member traveled to work with Japanese colleagues at the AIST in January 2006 and helped them build similar tools as we have built for the southwestern US for Japan.

• We have worked in the last year with the United States Geological Survey teams at Pasadena and the EROS Data Center on developing a national framework for Airborne Laser Swath Mapping data. We have also collaborated with the Ohio State University group headed by Mike Bevis on the processing of the B4 airborne laser swath mapping dataset.

• Arrowsmith and graduate student Crosby have consulted with numerous earth science colleagues on the processing of Airborne Laser Swath Mapping data, building on our GEON Lidar Workflow efforts.

• Arrowsmith has continuted to work with the National Center For Airborne Laser Mapping group (; including some sample data analysis) to evaluate if GEON might work with them to support their data analysis efforts in association with planned Earthscope GEO-Plate Boundary Observatory laser mapping data collection.

• Our work was also featured on the GEON main web page for several months:



and it was featured in the 2006 San Diego SuperComputer Center Calendar, and in the SDSC magazine Envision:

• ASU team member Chris Crosby and Kurt Frankel from USC deployed a lidar listserv: .

Figures

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Figure 1. Imagery processing at ASU using the Aster Imagery Service developed with SWGEONET/GEON support. We processed about 1400 images in the last year, averaging about 3-4 per day (including numerous ones used in classes at ASU and elsewhere—see steep parts of curves in spring 2006).

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Figure 2. Various measures of the southern “edge” of the Colorado Plateau (Arrowsmith, 2005b). The upper image shows topography as shaded relief, Plio-Quaternary geologic units, and active faults from the US Geological Survey. The Colorado Plateau is surrounded by active faults and is bounded by them on the west and east. The lower image shows that the various indications of the Plateau margin are generally coincident in the southwest probably because of active faulting there, whereas, the southern margin is more diffuse with the crustal thickness indicating the Plateau margin much further south than the volcanic front. The other measures (faults, the last outcrops of Mesozoic and Paleozoic units, and the topographic edge) are between the crustal and volcanic “edges.”

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Figure 3. GEON Lidar Workflow outputs (). The top view shows an oblique view toward the northeast over the San Andreas Fault (1906 earthquake traces in red) southeast of Point Arena in northern California. Long term offset of Mill Gulch (major drainage in the center of the view) is easily measured in these high resolution topographic data. The lower row shows the full feature (all LiDAR returns) digital elevation model (DEM) shaded relief, bare earth (only ground returns) DEM shaded relief, and a measure of canopy thickness computed by subtracting the bare earth DEM from the full feature DEM. Those color-coded canopy heights are actually displayed in the oblique view in the top image, showing that some tall trees are growing in the lower portions of the Mill Gulch.

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