Development of a GIS-Based Tool for Aquaculture Siting

isprsISPRS International Journal of Geo-Information, 2014, 3(2), 800-816

By Noelani Puniwai, Lisa Canale, Maria Haws, James Potemra, Christopher Lepczyk, and Steven Gray

“Nearshore aquaculture siting requires the integration of a range of physical, environmental, and social factors. As a result, the information demand often presents coastal managers with a range of complex issues regarding where specific types of aquaculture should be ideally located that reduce environmental and social impacts. Here we provide a framework and tool for managers faced with these issues that incorporate physical and biological parameters along with geospatial infrastructure.

Summary of attributes for selected hexagons with legend and layer options visible on the right.

Summary of attributes for selected hexagons with legend and layer options visible on right.

“In addition, the development of the tool and underlying data included was undertaken with careful input and consideration of local population concerns and cultural practices. Using Hawaiʻi as a model system, we discuss the various considerations that were integrated into an end-user tool for aquaculture siting.”

URISA Recommends the Addition of Addresses as a Framework Data Theme

URISAThe URISA Board of Directors recently recommended that the Federal Geographic Data Committee (FGDC) add addresses as an eighth framework data theme to the National Spatial Data Infrastructure (NSDI), and, in support of that, incorporate the FGDC address data standard into the Geographic Information Framework Data Content Standard. In addition, URISA recommends that the FGDC specify procedures for adding other new data themes to the NSDI, and proposes criteria to assure that new data themes will be significant, well-defined, and consistent with other NSDI data themes.

The recommendation is intended to strengthen other FGDC NSDI and address data initiatives.To review the recommendation in detail, visit http://www.urisa.org/main/advocacy/#policystatements.

Additional Resource: United States Thoroughfare, Landmark, and Postal Address Data Standard

{Source: URISA press release]

OGC Calls for Public Comment on Candidate Standard for Encoding Coverages in JPEG2000

OGC_Logo_Border_Blue_3DThe Open Geospatial Consortium (OGC®) membership seeks public comment on the candidate OGC GML Application Schema – Coverages – JPEG2000 Coverage Encoding Extension (abbreviated as “GMLCOV for JPEG2000”). This candidate standard can be downloaded from http://www.opengeospatial.org/standards/requests/123

GIS coverages (including the special case of Earth images) are two- (and sometimes higher-) dimensional metaphors for phenomena found on or near a portion of the Earth’s surface. Coverage instances may be encoded using the OGC GML Application Schema – Coverages (GMLCOV) Encoding Standard, which is based on the Geography Markup Language (GML), an XML grammar written in XML Schema for the transport and storage of geographic information. GMLCOV for JPEG2000 specifies an encoding of GML coverages for the JPEG2000 data exchange formats for still imagery (i.e. JPC, JP2, JPX). This document is the basis for the GML in JPEG2000 encoding standard v2.0 and a future format extension for WCS.

Suggested additions, changes, and comments on this candidate standard are welcomed and encouraged. Such suggestions may be submitted at by 20 August 2014.

The OGC® is an international consortium of more than 475 companies, government agencies, research organizations, and universities participating in a consensus process to develop publicly available geospatial standards. OGC standards support interoperable solutions that “geo-enable” the Web, wireless and location-based services, and mainstream IT. Visit the OGC website at http://www.opengeospatial.org/.

[Source: OGC press release]

A Flexible Spatial Framework for Modeling Spread of Pathogens in Animals with Biosurveillance and Disease Control Applications

isprsISPRS International Journal of Geo-Information, 2014, 3(2), 638-661

By Montiago LaBute, Benjamin McMahon, Mac Brown, Carrie Manore, and Jeanne Fair

“Biosurveillance activities focus on acquiring and analyzing epidemiological and biological data to interpret unfolding events and predict outcomes in infectious disease outbreaks. We describe a mathematical modeling framework based on geographically aligned data sources and with appropriate flexibility that partitions the modeling of disease spread into two distinct but coupled levels. A top-level stochastic simulation is defined on a network with nodes representing user-configurable geospatial “patches”. Intra-patch disease spread is treated with differential equations that assume uniform mixing within the patch. We use U.S. county-level aggregated data on animal populations and parameters from the literature to simulate epidemic spread of two strikingly different animal diseases agents: foot-and-mouth disease and highly pathogenic avian influenza.

Inter-county level spread of FMD. Green dots indicate where there are susceptible populations of cattle, hogs and/or sheep according to the 2007 USDA NASS agricultural census data. Blue dots indicate where there are 10 or greater asymptomatic animals, red dots indicate where there are one or more symptomatic animals. Black crosses indicate counties which either had no initial susceptible populations or that are depopulated of susceptibles by mitigative measures, i.e., quarantine, culling and/or vaccination.

Inter-county level spread of FMD. Green dots indicate where there are susceptible populations of cattle, hogs and/or sheep according to the 2007 USDA NASS agricultural census data. Blue dots indicate where there are 10 or greater asymptomatic animals, red dots indicate where there are one or more symptomatic animals. Black crosses indicate counties which either had no initial susceptible populations or that are depopulated of susceptibles by mitigative measures, i.e., quarantine, culling and/or vaccination.

“Results demonstrate the capability of this framework to leverage low-fidelity data while producing meaningful output to inform biosurveillance and disease control measures. For example, we show that the possible magnitude of an outbreak is sensitive to the starting location of the outbreak, highlighting the strong geographic dependence of livestock and poultry infectious disease epidemics and the usefulness of effective biosurveillance policy. The ability to compare different diseases and host populations across the geographic landscape is important for decision support applications and for assessing the impact of surveillance, detection, and mitigation protocols. “

Esri Celebrates Outstanding Applications of Geographic Technology

Esri logoMore than 170 Organizations Recognized for Innovative Maps and Apps

Esri celebrated more than 170 organizations during the Special Achievement in GIS (SAG) Awards ceremony yesterday at the Esri User Conference (Esri UC) in San Diego, California. The SAG Awards highlight users that have shown vision, leadership, hard work, and innovation in their use of Esri’s geographic information system (GIS) technology.

“Every day, people and organizations are improving our world and driving change through geospatial technology,” says Esri president Jack Dangermond. “We are humbled by their passion and deeply appreciative of their tireless work. It’s an honor for us to recognize their efforts and it’s something that I personally look forward to every year.”

Organizations from around the world honored at the Esri UC span industries including environmental management, education, government, health and human services, natural resources, nonprofits, telecommunications, transportation, and utilities.

The SAG Awards ceremony was held at the San Diego Convention Center on July 16, 2014. For more information about the 2014 Special Achievement in GIS Award winners, including project information and photos, visit esri.com/sag.

[Source: Esri press release]

What’s the Deal with 3DEP?

USGSReplacing Outdated and Inconsistent Elevation Data Will Save Lives and Improve Prosperity Across Our Nation

The USGS, along with other federal, state, local and private agencies is establishing a new 3D Elevation Program (3DEP) designed to respond to the growing needs for three-dimensional mapping data of the United States. This coordinated partnership can help meet the country’s needs for high-quality, 3D elevation data.

Current and accurate 3D elevation data are essential to help communities cope with natural hazards and disasters such as floods and landslides, support infrastructure, ensure agricultural success, strengthen environmental decision-making and bolster national security.

The primary goal of the 3DEP partnership is to systematically collect 3D elevation data across the Nation, using lidar, a remote sensing detection system that works on the principle of radar, but uses light from a laser.

A comparison of an air photo and a lidar image of an area along Secondary Road and Camp Creek, 12 miles north of John Day, OR. The lidar image allows identification of landslide activity that is otherwise masked by trees. (Photo courtesy of the Oregon Department of Geology and Mineral Industries).

A comparison of an air photo and a lidar image of an area along Secondary Road and Camp Creek, 12 miles north of John Day, OR. The lidar image allows identification of landslide activity that is otherwise masked by trees. (Photo courtesy of the Oregon Department of Geology and Mineral Industries).

“We are excited about working with partners to apply the game-changing technology of lidar to benefit many critical needs of national importance,” said Kevin Gallagher, USGS Associate Director of Core Science Systems. “For example, FEMA and NOAA are some of our strongest partners because they rely on this type of data to significantly improve floodplain mapping and to better communicate flood risks to communities and citizens.”

The 3DEP initiative is based on the results of the National Enhanced Elevation Assessment that documented more than 600 business and science uses across 34 Federal agencies, all 50 States, selected local government and Tribal offices, and private and nonprofit organizations.  The assessment also shows that 3DEP would provide more than $690 million annually in new benefits to government entities, the private sector, and citizens.

A recent White House fact sheet described how accessibility of accurate, high-quality 3D elevation data provides the foundation to the Administration’s overall plan to assist populations in the areas of flood risk management, water resource planning, mitigation of coastal erosion and storm surge impacts, and identification of landslide hazards.

The USGS will host a briefing on Capitol Hill on July 25 to further describe the importance, benefits and growing needs for 3D elevation data.

More information about 3DEP and state specific fact sheets is available online.

[Source: USGS press release]

Mapping Sleeping Bees within Their Nest: Spatial and Temporal Analysis of Worker Honey Bee Sleep

PLOS_ONEPLOS One, Published 16 July 2014

Barrett Anthony Klein, Martin Stiegler, Arno Klein, and Jürgen Tautz

“Patterns of behavior within societies have long been visualized and interpreted using maps. Mapping the occurrence of sleep across individuals within a society could offer clues as to functional aspects of sleep. In spite of this, a detailed spatial analysis of sleep has never been conducted on an invertebrate society. We introduce the concept of mapping sleep across an insect society, and provide an empirical example, mapping sleep patterns within colonies of European honey bees (Apis mellifera L.). Honey bees face variables such as temperature and position of resources within their colony’s nest that may impact their sleep.

Infrared images revealing thermal activity across beehives. (A) Sequence of colony-scale changes across the entrance side of Colony 1. In clockwise order from the upper left corner, 1700, 0400, 0900 and 1500 h, respectively. Entrance/exit is in the lower left corner of the hive, leading out tube at left of each image. Brood comb is most easily seen as the glowing warm area at 0400 h. (B) Observation hive containing Colony 2, with filter-covered lamp at upper right, and bees visibly exiting hive tunnel at lower right. (C) Exposed nest composed of parallel sheets of comb, set up by Dirk Ahrens-Lagast to induce bees to construct a more natural nest architecture; not used in study. B.A.K. took all images with FLIR thermal cameras on non-experiment days under different ambient temperature conditions. Temperature scale values (°C) were adjusted for thermal camera settings.

Infrared image revealing thermal activity across beehives. Exposed nest composed of parallel sheets of comb, set up by Dirk Ahrens-Lagast to induce bees to construct a more natural nest architecture; not used in study. B.A.K. took all images with FLIR thermal cameras on non-experiment days under different ambient temperature conditions. Temperature scale values (°C) were adjusted for thermal camera settings.

“We mapped sleep behavior and temperature of worker bees and produced maps of their nest’s comb contents as the colony grew and contents changed. By following marked bees, we discovered that individuals slept in many locations, but bees of different worker castes slept in different areas of the nest relative to position of the brood and surrounding temperature. Older worker bees generally slept outside cells, closer to the perimeter of the nest, in colder regions, and away from uncapped brood. Younger worker bees generally slept inside cells and closer to the center of the nest, and spent more time asleep than awake when surrounded by uncapped brood. The average surface temperature of sleeping foragers was lower than the surface temperature of their surroundings, offering a possible indicator of sleep for this caste. We propose mechanisms that could generate caste-dependent sleep patterns and discuss functional significance of these patterns.”