The USGS Community for Data Integration Workshop will feature presentations from six 2014 CDI projects on July 8 at the summer meeting of the Federation of Earth Science Information Partners (ESIP).
The sessions will broadcast the presentations via webex and recorded and the community is welcome to join the meeting via webinar at no cost. To register for free remote access, go to: https://www.regonline.com/esipfederationsummermeeting2014 and select Remote Participant.
For more information about the ESIP Summer Meeting, see: http://commons.esipfed.org/2014SummerMeeting
|Session 1: 9:00am-10:30am MT||Title and Abstract||Presenter||Recordings|
Kevin Gallagher, USGS Associate Director for Core Science Systems
Moderator: Jennifer Carlino, CDI Coordinator
Characterization of Earthquake Damage and Effects Using Social Media Data
The U.S. Geological Survey (USGS) operates a real time system that detects felt earthquakes, using only data from Twitter—a service for sending and reading public text-based messages, known as tweets. The detector algorithm scans for significant increases in tweets containing the word “earthquake” or its counterpart in several non-English languages and then sends internal alerts with the detection time, representative tweet texts, and the location of the population center where most of the tweets originated. The system has been running in real-time for over two years and finds, on average, three felt events per day with a false detection rate of 8%. The main benefit of the tweet-based detections is speed, with most detections occurring between 20 and 120 seconds after the earthquake origin time. This is considerably faster than seismic detections in poorly instrumented regions of the world. The detections have reasonable coverage of populated, earthquake prone, areas globally. The number of tweet-based detections is small compared to the number of earthquakes detected seismically, and only a rough location and qualitative assessment of shaking can be determined based on tweet data alone. However, the tweet-based detections are generally caused by widely felt events that are of more immediate interest than those with no human impact. We will provide a technical overview of the system and investigate the potential for rapid characterization of earthquake damage and effects using the 22 million “earthquake” tweets that the system has so far amassed. We will also investigate the potential use of other social media sources such as Instagram for rapid impact assessment. Additionally, this effort looks towards establishing a data feed of the tweet-based detections for sharing with collaborators and integrating derived products, such as event characterization, with seismically derived solutions for sharing with collaborators and USGS seismic monitoring and analysis systems.
Michelle Guy, USGS National Earthquake Information Center (303.273.8650); email@example.com)
Online, on demand access to coastal digital elevation models
Scientists working in the coastal environment use bathymetric and topographic data to evaluate storm-induced coastal change, shoreline change, and ecosystem vulnerability. Moreover, forecast models for waves and water levels require gridded elevation surfaces that seamlessly span the land-water interface. The USGS performs copious amounts of lidar surveys and conducts geophysical surveys of the nearshore bathymetry to help address these needs. However, inadequate tools to merge these data which are collected at varying temporal and spatial resolutions, and from a variety of instrument platforms, limit the availability and applicability of the data. The focus of this work is to address the immediate need of integrating land and water-based elevation data sources so they are readily accessible to coastal scientists and decision makers requiring a seamless data surface that spans the terrestrial-marine boundary. The two primary products will be 1) a geoprocessing service that merges and interpolates the data sources; and 2) a map-based web interface and associated information management platform that allows users to identify an area of interest to implement the interpolation algorithms, access the final gridded data derivative, and save and document the configuration parameters for future reference. The resulting products and tools could be adapted to future data sources and projects beyond the coastal environment.
|Joseph Long, USGS St. Petersburg Coastal and Marine Science Center (727.502.8024); firstname.lastname@example.org)|
NASWeb API – Web Services Access to the Nonindigenous Aquatic Species Database
|Matt Neilson, USGS Southeast Ecological Science Center (352.264.3519; email@example.com) |
|Session 2: 11:00am-12:30pm MT|
Summarization of National NEXRAD Data for use in Biological Applications
The US network of weather radars known as NEXRAD (NEXt generation RADar) is one of the largest and most comprehensive terrestrial sensor networks in the world with the ability to detect the movements and densities of hundreds of species of birds, bats, and insects. These radars have been shown to provide biologically useful data related to the ecology, behavior, conservation, and management of flying animals. Such data often includes but is not limited to altitude-specific measures of speed, direction, orientation, and the intensity of the movement. Currently, however, considerable post processing is required to enable the biological potential of these data, and this has limited their accessibility to the wider biological community. This project proposes a proof-of-concept to advance methods of processing, summarizing, and distributing biological radar data of flying animals in a form more accessible and meaningful to the larger biological science community. Processed and summarized data will be integrated into ScienceBase, an interdisciplinary data server and repository, where it will support current and future biological research applications. We are currently working with collaborators to develop algorithms to automate the collection and processing of NEXRAD datasets, which will initially be done manually using CDI funds. Manual summaries, in addition to providing biologically relevant NEXRAD data for the two fall migratory seasons covered, will provide a valuable resource to QA/QC algorithm performance prior to complete automation.
Tara Chesley-Preston, USGS Northern Rocky Mountain Science Center & Montana State University (406.994.7158; firstname.lastname@example.org)
Robert Diehl, USGS Northern Rocky Mountain Science Center
Todd Preston, Parallel, Inc.
North American Bat Data IntegrationBats are essential to the health of our natural world. They help control pests and are vital pollinators and seed-dispersers for countless plants. Bat populations are in trouble, however. Since 2006, more than 5 million bats have died due to a fungal disease called White-nose Syndrome (WNS). At the same time, several migratory tree-dwelling species are being killed in unprecedented numbers by wind turbines. This project will integrate two important datasets into an online web application called the USGS Bat Population Data (BPD) Project so that they are available to bat researchers and can inform conservation efforts for bats. The first dataset is WNS diagnostic data, which are used to better understand the distribution and spread of WNS, as well as the fungus that causes the disease. The second dataset is the Bat Banding Program files. For 40 years, the U.S. Government administered a bat banding program and the files have never been consolidated and entered into a searchable database. There is much interest in the bat conservation community for easy access to these historical records of banding at sites now infected with WNS or potentially threatened by wind energy development and climate change. This project will also develop the application programming interfaces (APIs), data services, and data management workflows to share the public government bat data and metadata with BISON (Biodiversity Information Serving Our Nation) and Sciencebase.
Laura Ellison, USGS Fort Collins Science Center (970.226.9494; email@example.com)
Lance Everette, USGS Fort Collins Science Center (970.226.9225; firstname.lastname@example.org)
Anne Ballmann, USGS-National Wildlife Health Center, (608.270.2445; email@example.com)
Suzanne Peurach, USGS Patuxent Wildlife Research Center, Smithsonian Institution (202.633.1277; firstname.lastname@example.org)
Jeremy Coleman, U.S. Fish and Wildlife Service (413.253.8223; email@example.com)
Adopt a Pixel – Data Infrastructure
Adopt a Pixel is a ground-reference data acquisition system engaging citizen scientists to serve operational and research needs of the Landsat science community. CDI funding will support the establishment of the data infrastructure within the Operational Science group of the USGS Earth Resources Observation and Science (EROS) Center. Currently, the Adopt a Pixel initiative resides in a pilot state. CDI funding will be utilized to create a user upload capability, a data ingest process and a data management system for storage of imagery and metadata; and to enable incorporation into the USGS Earth Explorer web-based user interface for the query and download by the end user. Once the system is developed, tested, and released, users will be able to efficiently search and download numerous USGS-supported remote sensing datasets with the addition of linked ground reference photos provided by the user community.
|Ryan Longhenry, USGS EROS Data Center (605.594.6179; firstname.lastname@example.org)|