KML in the North

Welcome

John E. Bailey

Arctic Region Supercomputing Center & Alaska Volcano Observatory, UAF

Introduction

Michael Weiss-Malik

KML Product Manager, Google Inc.

Volcano Monitoring Tools Using KML

Jon Dehn

Alaska Volcano Observatory & Geophysical Institute, UAF

In order to compare the varied data streams used to monitor volcanoes a series of KML generating scripts are employed by the Alaska Volcano Observatory for each data type. This allows analysts to compare what were once disparate data in the same application, namely a virtual globe or geobrowser. At the Alaska Volcano Observatory a number of tools are available that produce KML to help observatory staff and researchers react to volcanic activity and perform interdisciplinary studies of volcanic processes.

Interactive Earthquake Visualization as a Tool for Predicting Volcanic Eruptions

Mike West

Alaska Volcano Observatory & Geophysical Institute, UAF

Earthquake monitoring is one of the more powerful tools for forecasting volcanic eruptions. For many decades, volcanic earthquakes have been monitored for changes in rate and location that might signal the arrival of magma at shallow depths beneath volcanoes. Accurate assessment of these trends requires visualizing data in a minimum of five dimensions - 3D space plus time plus earthquake magnitude. Historically this has been accomplished via a suite of static plots in 2D or in ad hoc 3D formats. The KML protocol, and the tools to digest it, have provided a simple unified environment for visualizing earthquakes precursory to volcanic eruptions.

Weather Research and Forecasting Model Visualized Using KML

Patrick Webb

Arctic Region Supercomputing Center, UAF

The Arctic Region Supercomputing Center generates a twice-daily run of the Weather Research and Forecasting model on ARSC's Sun-Opteron Cluster, "Midnight". These runs are used for a variety of research purposes and include a 16km resolution forecast over the western arctic, a Fairbanks NWS forecast area forecast at 6km and a experimental forecast over the Interior at 2km. To make the weather data accessible to a broader audience, ARSC uses Google Earth and KML as a visualization option for the output of the WRF tool.

Statewide Digital Mapping Initiative base-layers as KML

Dayne Broderson

Geographic Network of Alaska, UAF

The Alaska Statewide Digital Mapping Program's goal is to acquire new and better maps for Alaska and make existing map products more easily available. Towards this goal the project has recently made available KMLs allowing access to some of the SDMI's WMS feeds: An orthoimagery layer called 'Best Data Layer' (BDL) that provides the best resolution imagery for a given zoom level and a USGS topographic maps layer (DRG).

Break

KML, Climate Change and the Yukon Quest

Kate Riffey

University of Alaska Geography Program

In February of 2008 I strapped a GPS unit and a HOBO (temperature recorder) on the sled of Lance Mackey as he ran the Yukon Quest. The Quest is a 1000 mile long race starting in Fairbanks, heading up to north Alaska, over into Canada and down to Whitehorse. The purpose of this project was to see what kind of climate information we could get from the sled and from human observations at each of the eight checkpoints. With the data we could compare it to past data and future data from the same area and track local climate changes and what affects those changes are having on the ecosystems involved. I used Google Earth to visualize the data and provide a learning tool for people around the world that are interested in dog mushing and what climate change might be doing to Alaska. Climate change is having a faster and heavier impact on the polar regions and this is a way of getting an idea of those changes and how it could impact humans.

KML and Biodiversity Informatics

Zach Meyers

Museum of the North Herbarium & Department of Wildlife and Biology, UAF

Biodiversity informatics aims to develop over-arching hypotheses that span the entire tree of life. Continual improvement in technology and online resources across a wide spectrum of life has major implications to how biological data are viewed, discussed, and analyzed. Currently, there is a vast amount of information already collected about the world's biodiversity,mainly stored in natural history collections. However, to date most of this information has not been digitized and is thus not easily accessible. Using established search engines of biodiversity data one can mine the large quantities of digitized biodiversity data at GBIF, but a visually appealing way of exploring these data is still lacking. Google-Earth offers one media outlet for these components of data. In this presentation, I will demonstrate the relative ease of creating KML's with botanical specimen data from the UA Museum of the North Herbarium database (ARCTOS). KML of biodiversity data will be an outstanding tool for scientists, natural resource managers, and policy-makers and will promote the open sharing of biodiversity information in support of environmental and biodiversity protection and conservation.

Volcanic Ash Tracking and Dispersion Model Predictions Within Virtual Globes

Peter Webley

Arctic Region Supercomputing Center & Alaska Volcano Observatory, UAF

Volcanic ash tracking and dispersion models are routinely used by volcano observatories and volcanic ash advisory centers to analyze and predict the movement of airborne ash world-wide. These models play an important role by complementing both remote sensing data and visual observations from the ground and aircraft. Alaska Volcano Observatory (AVO) uses Puff, a three dimensional dispersion model primarily designed for forecasting volcanic ash dispersion. The Puff model predictions are displayed in both two and three dimensions, using Google Earth and Maps, for volcanoes across the NOPAC and selected volcanoes in Europe, Indonesia, Central and South America. New predictions are automatically generated every 3 - 6 hrs. The KML 'timestamp' option allows the model simulations to be displayed in real-time as image overlays or as animations that show the predicted position of the ash clouds. The ash clouds' proximity to local population, airports and any possible air traffic can then be assessed.

Tsunami Inundation Mapping with KML

Dave West and Elena Suleimani

Alaska Earthquake Information Center, UAF

The Alaska Earthquake Information Center participates in the National Tsunami Hazard Mitigation Program by evaluating and mapping potential inundation for Alaska coastal communities through numerical modeling of tsunami wave dynamics. Tsunami waves are a threat for many Alaska coastal locations and community preparedness plays a vital role in saving lives and property. While we spend most of our days mired in processing elevation data and producing predictive models of tsunami events, we are faced as well with the equally thorny challenge of determining how this data will be disseminated to the general public in at-risk areas. We have found the simplicity and flexibility of the KML/Google Earth platform to be instrumental for presenting our data in a portable and instructive way. We have recently moved to presenting many of our illustrations and animations within the Google Earth environment and we will give a brief demo of some of these, including on-earth animations of tsunami waves within Resurrection Bay.

Using KML in Science

John E. Bailey

Arctic Region Supercomputing Center & Alaska Volcano Observatory, UAF

Researchers from University of Alaska Fairbanks are involved in a number of projects that promote the use of Keyhole Markup Language in science. As a conclusion to the presentations part of the symposium, an overview of these projects will be given.