GeoTech Center and URISA Announce 2015 Undergraduate Geospatial Technology Skills Competition

URISAThe GeoTech Center and URISA are pleased to announce the 2015 Undergraduate Geospatial Technology Skills Competition! The intent of the competition is to showcase the geospatial technology skills of U.S. undergraduate students. Competing students will create a project that utilizes geospatial technology to address a real-world problem. The student will then present the project and the resulting deliverables as a video (approximately 10-15 minutes in length) which not only highlights their use of geospatial technology, but also demonstrates their communication and presentation skills. As Rodney Jackson, Dean of Business, Engineering & Technical Studies at Davidson County Community College states:

“The ability to provide a competition for students to demonstrate their geospatial competency to industry partners, within the context of a national conference, has significant value within their educational experience.”

More details to follow in the coming months; updates will be posted to the competition website.

Eligibility

Students who are at least 18 years old and currently enrolled during Spring 2015 in a geospatial technology course (e.g., geographic information systems, remote sensing, or GPS/GNSS) or geospatial technology program at an accredited 2-year or 4-year U.S. institution are eligible to enter. Questions regarding eligibility can be directed to either Tom Mueller at mueller@calu.edu or Scott Jeffrey at sjeffrey@ccbcmd.edu. One entry per student and only individual student submissions allowed (no group projects).

Judging

Entries will be due by Friday, June 12, 2015 and will be judged by a panel of experienced geospatial specialists. The combined scores from all judges will determine the top five (5) student finalists. These finalists will win an all-expense-paid trip to the GIS-Pro & NWGIS 2015: Geography at the Nexus of Collaboration international conference in Spokane, WA on October 18-22, 2015, where they will be required to present their project. Judges will then determine the competitors’ final place ranking. It is anticipated that three (3) of the student finalists will be from two-year colleges and two (2) from four-year institutions. The exact split will depend upon the number of students who enter the competition and the quality of the work submitted (judges also reserve the right to invite fewer than five student finalists).

[Source: URISA news release]

Real-time GIS Data Model and Sensor Web Service Platform for Environmental Data Management

International Journal of Health GeographicsInternational Journal of Health Geographics, Published Online 09 January 2015

By Jianya Gong, Jing Geng, and Zeqiang Chen

Background
Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework.

Methods
A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies.

Results
To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s.

Conclusions
The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework.”

Geographically Weighted Regression to Measure Spatial Variations in Correlations between Water Pollution versus Land Use in a Coastal Watershed

OCMOcean & Coastal Management, Volume 103, January 2015, Pages 14–24

By Jinliang Huang, Yaling Huang,Robert Gilmore Pontius Jr., and Zhenyu Zhang

“Highlights

  • GWR reveals spatial variation in water pollution-land use linkages.
  • Water pollution is associated more with built-up than with cropland or forest.
  • More built-up is associated with more pollution for less urbanized sub-watersheds.
  • Forest has a stronger negative association with pollution in urban sub-watersheds.
  • Cropland has a weak association with water pollution among 21 sub-watersheds.

“Land use can influence river pollution and such relationships might or might not vary spatially. Conventional global statistics assume one relationship for the entire study extent, and are not designed to consider whether a relationship varies across space. We used geographically weighted regression to consider whether relationships between land use and water pollution vary spatially across a subtropical coastal watershed of Southeast China. Surface water samples of baseflow for seven pollutants were collected twelve times during 2010–2013 from headwater sub-watersheds. We computed 21 univariate regressions, which consisted of three regressions for each of the seven pollutants. Each of the three regressions considered one of three independent variables, i.e. the percent of the sub-watershed that was cropland, built-up, or forest.

Local R2 values and local parameter estimates for GWR cropland models among three types of sub-watershed.

Local R2 values and local parameter estimates for GWR cropland models among three types of sub-watershed.

“Cropland had a local R2 less than 0.2 for most pollutants, while it had a positive association with water pollution in the agricultural sub-watersheds and a negative association with water pollution in the non-agricultural sub-watersheds. Built-up had a positive association with all pollutants consistently across space, while the increase in pollution per increase in built-up density was largest in the sub-watersheds with low built-up density. The local R2 values were stronger with built-up than with cropland and forest. The local R2 values for built-up varied spatially, and the pattern of the spatial variation was not consistent among the seven pollutants. Forest had a negative association with most pollutants across space. Forest had a stronger negative association with water pollution in the urban sub-watersheds than in the agricultural sub-watersheds. This research provides an insight into land-water linkages, which we discuss with respect to other watersheds in the literature.”

A GIS-based Relational Data Model for Multi-dimensional Representation of River Hydrodynamics and Morphodynamics

EMS-S13648152Environmental Modelling & Software, Volume 65, March 2015, Pages 79–93

By Dongsu Kim, Marian Muste, and Venkatesh Merwade

“Highlights

  • Represent river data in a curvilinear coordinate system to support river channel oriented spatial analyses.
  • Represent multidimensional river features through points, lines, polygons, and volumes.
  • Represent simulated gridded data for river channels that can be readily coupled with observed data.
  • Represent spatio-temporal evolution of dynamic river objects using Eulerian or Lagrangian observational frameworks.
  • Efficiently store and retrieve data acquired in-situ along with the ancillary metadata.

“The emerging capabilities of the geo-based information systems to integrate spatial and temporal attributes of in-situ measurements is a long-waited solution to efficiently organize, visualize, and analyze the vast amount of data produced by the new generations of river instruments. This paper describes the construct of a river data model linked to a relational database that can be populated with both measured and simulated river data to facilitate descriptions of river features and processes using hydraulic/hydrologic terminology.

Diagram of the connectivity between multidimensional river objects in a cross-section and the river network: Relationship between the CrossSection3DPoint and CrossSection2DPoint in 3D cross-sections.

Diagram of the connectivity between multidimensional river objects in a cross-section and the river network: Relationship between the CrossSection3DPoint and CrossSection2DPoint in 3D cross-sections.

“The proposed model, labeled Arc River, is built in close connection with the existing Arc Hydro data model developed for water-related features to ensure the connection of the river characteristics with their floodplains and watersheds. This paper illustrates Arc River data model capabilities in conjunction with Acoustic Doppler Current Profiler measurements to demonstrate that essential river morphodynamics and hydrodynamics aspects can be described using data on the flow and its boundaries.”

What’s New in ArcGIS for Maritime: Bathymetry? Free Webinars in January

Would you like to learn more about the new capabilities in ArcGIS 10.3 for managing and modeling your bathymetric data? Our free webinar explores the latest developments in ArcGIS for Maritime: Bathymetry. Spend an hour with us and learn how to make your bathymetric data work harder for you. Pick your date and register today.

Session 1
Tuesday, January 20
9:00 p.m.-10:00 p.m. PST

More info: http://events.esri.com/info/index.cfm?fuseaction=seminarRegForm&shownumber=18837&utm_source=esri&utm_medium=email&utm_term=77901&utm_content=article&utm_campaign=bathymetric_webinar_2014

Session 2
Thursday, January 22
6:00 a.m.-7:00 a.m. PST

More info: http://events.esri.com/info/index.cfm?fuseaction=seminarRegForm&shownumber=18849&utm_source=esri&utm_medium=email&utm_term=77901&utm_content=button&utm_campaign=bathymetric_webinar_2014

HIV and Hepatitis C Mortality in Massachusetts, 2002–2011: Spatial Cluster and Trend Analysis of HIV and HCV Using Multiple Cause of Death

PLOS One, Published Online 11 December 2014

By David J. Meyers, Maria Elena Hood, and Thomas J. Stopka

Background
Infectious diseases, while associated with a much smaller proportion of deaths than they were 50 years ago, still play a significant role in mortality across the state of Massachusetts. Most analysis of infectious disease mortality in the state only take into account the underlying cause of death, rather than contributing causes of death, which may not capture the full extent of mortality trends for infectious diseases such as HIV and the Hepatitis C virus (HCV).

Methods
In this study we sought to evaluate current trends in infectious disease mortality across the state using a multiple cause of death methodology. We performed a mortality trend analysis, identified spatial clusters of disease using a 5-step geoprocessing approach and examined spatial-temporal clustering trends in infectious disease mortality in Massachusetts from 2002–2011, with a focus on HIV/AIDS and HCV.

HCV Mortality rates by census tract, 2002–2011. Crude Mortality Rates were calculated based on the 2010 census population estimates at the census tract level for all-causes of HCV. Rates were classified by quintile. Shapefiles were provided by MassGIS, death data were provided by the Massachusetts Department of Public Health, and population estimates were provided by the US Census Bureau. NAD 1983 Massachusetts State Plain was used for projection. Maps created in ArcGIS 10.2.

HCV Mortality rates by census tract, 2002–2011. Crude Mortality Rates were calculated based on the 2010 census population estimates at the census tract level for all-causes of HCV. Rates were classified by quintile. Shapefiles were provided by MassGIS, death data were provided by the Massachusetts Department of Public Health, and population estimates were provided by the US Census Bureau. NAD 1983 Massachusetts State Plain was used for projection. Maps created in ArcGIS 10.2.

Results
Significant clusters of high infectious disease mortality in space and time throughout the state were detected through both spatial and space time cluster analysis. The most significant clusters occurred in Springfield, Worcester, South Boston, the Merrimack Valley, and New Bedford with other smaller clusters detected across the state. Multiple cause of death mortality rates were much higher than underlying cause mortality alone, and significant disparities existed across race and age groups.

Conclusions
We found that our multi-method analyses, which focused on contributing causes of death, were more robust than analyses that focused on underlying cause of death alone. Our results may be used to inform public health resource allocation for infectious disease prevention and treatment programs, provide novel insight into the current state of infectious disease mortality throughout the state, and benefited from approaches that may more accurately document mortality trends.”

Two New Maps that Could Change the World

Maps have long been used by people to help navigate and understand our world. Early maps guided early humans to basic necessities such as food and water.

Today, the world is changing rapidly, and it’s difficult for traditional maps to keep up with the pace of that change. To help us keep pace with our evolving planet, we need something better. We need new, more comprehensive maps.

Esri has developed two new maps—the most detailed population map in the world and the most detailed ecological land unit map in the world—to help address the challenges we face and make our world a better place.


A New Map of World Population

Esri has compiled a human geography database of demographics and statistics about all countries in the world and has mapped this data using a new, innovative methodology.

Advances in technology are changing the type, quantity, quality, and timeliness of information available. The ideal human geography database would include uniform social and demographic information about all human populations on the globe. It would include population, household, housing unit, business, and economic information that would allow determination of societal characteristics at any scale from macro to micro.

pop-new-york_600

Esri has developed the most detailed population map in the world.

Esri’s new world population map takes advantage of this new information to track and estimate populations to support better decision making. This new model of world population will allow comparative studies and accurate depiction of statistics to ad hoc areas. Population is modeled from imagery, road networks, and populated place locations to create an urbanization likelihood score.

“The global model is currently complete for approximately 130 countries, allowing for detailed reporting that will show the demographics for any desired geography such as a watershed, drive-time area, or an area affected by a disaster,” said Earl Nordstrand, Data Product Manager, Esri. “Additionally, the likelihood surface has been used to create a global population map by obtaining the latest census population data for the remaining areas of the world.”


A New Map of World Ecology

The U.S. Geological Survey (USGS) and Esri recently announced the publication of the most detailed global ecological land units (ELUs) map in the world.

“The Global ELUs map portrays a systematic division and classification of the biosphere using ecological and physiographic land surface features,” notes Roger Sayre, Ph.D., Senior Scientist for Ecosystems, USGS.

gelu_img

Esri and USGS have developed the most detailed global ecological land units (ELUs) map in the world.

This exciting new global content provides a science platform for better understanding and accounting of the world’s resources.  Scientists, land managers, conservationists, developers and the public will use this map to improve regional, national and global resource management, planning and decision making.

“The ELUs provide an accounting framework to assess ecosystem services, such as carbon storage, soil formation, as well as risks such as, environmental degradation,” said Randy Vaughan, Manager of Content Engineering, Esri.  “The ELUs also lend themselves to the study of ecological diversity, rarity and evolutionary isolation.  For example we can identify whether the most diverse landscapes in terms of proximity to the most unique ELUs are protected. Understanding diversity can point the way to conservation and preservation planning.”

While ELUs do not definitively characterize ecosystems at multiple scales, they do provide information and pointers to the ecological patterns of the globe.  “They will be useful for constructing research agendas and for understanding global processes such as climate change,” added Sayre. “For example, the data will be important to the study of environmental change.  The automated approach to the objective classification of ELUs means that the mapping can be updated as better or more current input layers become available.”


Working Together

Separately, these two maps are important, and can be used in a variety of ways to address important local, regional, and global issues. Used together, these two new maps can give us an even better picture of the links between the human and natural components of our evolving world. “Population density and distributions are important indicator of both the demands and impacts on landscape,” said Vaughan.  “As such, population data can be used as another parameter to infer and understand the environmental processes expressed in the ecological land units.”

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How can you get access to the Global population map?

  1. You can access the map here http://pm.maps.arcgis.com/home/item.html?id=ac0401d78fa24a10a9151ffe50f35afe

How can you get access to the Global ELUs map?

  1. Introductory Story Map to the ecological land units: esriurl.com/elu
  2. Explore the online application: esriurl.com/EcoTapestry
  3. Learn more about ecological land units: www.aag.org/global_ecosystems
  4. Get started using this content in ArcGIS: ArcGIS Online Landscape Layers Group