Spatial Center Receives NSF Grant

Center for Spatial Studies at the University of California, Santa Barbara participating in NSF C-Accel Pilot

View the complete news release at: https://www.news.ucsb.edu/2019/019651/breaking-data-out-silos

The Center of Spatial Studies at the University of California, Santa Barbara is receiving research funding under the Open Knowledge Network track of the new Convergence Accelerator Pilot (C-Accel) by the National Science Foundation (NSF). Prof. Krzysztof Janowicz leads a diverse team of partners from academia, industry, and federal agencies. The team will develop Artificial Intelligence based models, methods, and services for representing,  retrieving, linking, and predicting spatial and temporal data from a highly diverse set of public knowledge graphs that range across topics such as soil health and the historic slave trade. 

This new NSF Convergence Accelerator Pilot program is set to “bring teams together to focus on grand challenges of national importance that require a convergence approach […] and have a high probability of resulting in deliverables that will benefit society within a fixed term.” NSF is funding several teams under this program in an effort that will lead to the development of public knowledge graphs which in turn have “the potential to drive innovation across all areas of science and engineering, and unleash the power of data and artificial intelligence to achieve scientific discovery and economic growth.” The funding program is highly competitive and had an acceptance rate of only 8.5%.

UCSB Creates eScholarship Spatial Archives for NCGIA, CSISS, and spatial@ucsb

escholarship-logoThe Center for Spatial Studies at the University of California, Santa Barbara (spatial@ucsb) announces the launch of its Spatial Archives. The project is hosted on eScholarship, an online library of downloadable publications of the University of California, which is now home to nearly 500 documents associated with the research and education initiatives of the following:

The collections feature technical, program, and meeting reports (including more than 1,600 position papers by meeting participants over a span of 27 years), special publications, and curricula and other educational resources. Each document is assigned a unique permalink, which, unlike a regular website address, is a permanent URL for access in perpetuity. All materials submitted to eScholarship are automatically deposited in the California Digital Library’s Merritt Preservation Repository, thus ensuring their long-term security and accessibility.

This project was initiated by Werner Kuhn, Director of spatial@ucsb, and carried out under the direction of Professor/Researcher Emeritus Donald Janelle, with technical support from Ph.D. Candidates Kitty Currier and Jessica Marter-Kenyon; eScholarship support from Katrina Romanowsky; and advice and assistance from Andrea Ballatore, Guylene Gadal, and Karen Doehner.
The intent of this year-long effort has been to:

1) provide the community with reliable access to a primary collection of geographic information science;

2) remove the risk associated with the uncertain sustainability of program-based websites; and

3) position these resources for integration within the broader literature to help document a period when geographic information science was taking flight.

The Center for Spatial Studies is especially interested in learning about similar projects and of plans by other organizations to document long-term programs in geographic information science and related fields. Please send comments and questions to Werner Kuhn (kuhn@geog.ucsb.edu) and Don Janelle (janelle@geog.ucsb.edu).

FlowMapper

 

Tobler’s Flow MapperFlowmap icon

[learn_more caption=”Background” state=”open”] Geographical movement is of crucial importance. This is because much change in the world is due to movement; the movement of people, ideas, money, or material. One way of depicting and analyzing geographical movement is by way of geographical maps. A convenient and rapid method of displaying movement data on such maps is therefore very useful. A flow mapping program is one approach to this objective. For in depth information see:

About Flow Mapper
In 2003 CSISS supported an effort to produce an interactive flow mapping program. The result is an updated Windows-based version of a program originally designed and programmed by Waldo Tobler in 1987. Tobler’s original application was updated by David Jones using Microsoft Visual Basic .Net and SVG (Scaleable Vector Graphics) for map rendering. It requires as input locational coordinates and a table of interaction between places. Additional input may include place names for the location coordinates and a file of boundary coordinates (the background map). The user has several menu options for producing a map. The program allows for the production of a total movement map shown by volume-scaled bands, net movement given by scaled arrows, or simultaneous two-way moves.

Flow Mapper Functionality in ArcGIS Flow Data Model Tools consist of several ArcGIS 9.x VBA macros. The prototype software integrates the functionality of Flow Mapper into ArcGIS, and allows ArcGIS interaction with the Flow Data Model. Source code and further information.
[/learn_more] [learn_more caption=”Flow Mapper Requirements” state=”close”]

  • Microsoft Windows 98SE, ME, 2000 or XP
  • Microsoft Dot.Net Framework Installed
  • Microsoft Internet Explorer (Required to display maps properly)
  • Scalable Vector Graphics Support for Internet Explorer: Adobe SVG Plugin 3.x or higher
  • C:temp folder
[/learn_more] [learn_more caption=”Installng Flow Mapper” state=”close”]
  • Remove any existing version of Flow Mapper (Start > Control Panel > Add/Remove Programs).
  • Verify that your operating system meets the requirements above.
  • Install the .Net Framework if necessary. Many newer Windows machines already come pre-installed with it. Go to Start > Control Panel, the .Net Framework Management Icon will be visible if it is installed (you may need to look in Administrative Tools.) If not visible you will need to Download and install the .Net Framework (21MB)
  • If you you have not done so previously, install Adobe SVG Plugin. If you are unsure, install it again.
    Download and install Adobe SVG Viewer (2.4MB)
  • Make sure C:Temp (c:temp) exists, the application uses this directory to write temporary files.
  • Download and install Flow Mapper (22MB), unzip the files on temporary directory and run setup.exe. Flow mapper will be installed and a shortcut will be placed in the Start Menu under Flow Mapper and on your desktop. The documentation, and Data_Sets will be automatically installed and links placed in the Flow Mapper folder.
  • After installing Flow Mapper, Download the Documents and Data update (8.5MB, 7-19-05) and unzip it to your installation folder (the default folder is C:Program FilesToblerFlow Mapper).
[/learn_more] [learn_more caption=”Flow Mapper Examples” state=”close”]




Example 1




Example 2




Example 3




Example 4




Example 5




Example 6




Example 7




Example 8




Example 9

User Contributions

Boundary Files from GeoDa to FlowMapper PDF
[/learn_more]

Please send questions and comments to Waldo Tobler

Tools Clearinghouse: Kevin Konty
Search Engines: Eric White

The information on this page was last updated on
July 19.2005

Gigalopolis

Project Gigalopolis

Project Gigalopolis

Project Gigalopolis is the growing urban structure containing billions of people worldwide. Urban settlements and their connectivity will be the dominant driver of global change during the twenty-first century. Intensely impacting land, atmospheric, and hydrologic resources, urban dynamics has now surpassed the regional scale of megaloplolis and must now be considered as a continental and global scale phenomenon. Project Gigalopolis extends and refines the Clarke urban growth model enabling predictions at regional, continental and eventually global scales.

For more information, visit Project Gigalopolis.

Varenius

Project Varenius



Project Varenius

Project Varenius aims to foster research in the following areas of geographic information science:

  • computational implementation of geographic concepts
  • cognitive models of geographic space
  • geographies of the information society

For more information, visit Project Varenius


Battuta

Project Battuta



Project Battuta

Project Battuta is an interdisciplinary research initiative to investigate the potential of emerging technologies and geospatial information resources to bring new functionalities to mobile field data collection. Research projects are underway in four main areas:

  • Infrastructure designs to support use of geospatial information in heterogeneous mobile field computing environments
  • Scientific software tools for sampling and conflation in limited field computing environments
  • Wearable computing environments and interface designs
  • Methodological approaches to using and collecting geospatial data in federal statistical surveys

Research is being prototyped and explored using a testbed environment. A variety of geospatial data sources have been assembled for a small area in Iowa that is undergoing urban development and experiencing a reduction in wetlands and prime farmland.

The concepts created under Project Battuta are being developed with environmental and demographic applications in mind. The infrastructure design readily extends to less structured information gathering settings such as crisis management and law enforcement.

For more information, visit Project Battuta


Prior NCGIA Research Programs

Prior NCGIA Research Programs
National Center for Geographic Information & Analysis

The National Center for Geographic Information and Analysis is an independent research consortium dedicated to basic research and education in geographic information science and its related technologies, including geographic information systems (GIS). The three member institutions are the University of California, Santa Barbara; the University at Buffalo; and the University of Maine. The consortium was formed in 1988 to respond to a competition for funding from the National Science Foundation. The three institutions have functioned independently since 1999, but they come together on a regular basis for cooperative initiatives that promote the original objectives of NCGIA. For more information, visit National Center for Geographic Information & Analysis

[learn_more caption=”Project Battuta” state=”close”]
battuta.jpg

Project Battuta

2000–2004

Principal Investigators:

Sarah Nusser and Les Miller

Iowa State University,

Mike Goodchild and Keith Clarke

University of California, Santa Barbara

Project Battuta was an interdisciplinary research initiative to investigate the potential of emerging technologies and geospatial information resources to bring new functionalities to mobile field data collection. Research projects were undertaken in four main areas:

  • Infrastructure designs to support use of geospatial information in heterogeneous mobile field computing environments
  • Scientific software tools for sampling and conflation in limited field computing environments
  • Wearable computing environments and interface designs
  • Methodological approaches to using and collecting geospatial data in federal statistical surveys

Research was prototyped and explored using a testbed environment. A variety of geospatial data sources were assembled for a small area in Iowa undergoing urban development and experiencing a reduction in wetlands and prime farmland.

The concepts created under Project Battuta were developed with environmental and demographic applications in mind. The infrastructure design readily extends to less structured information gathering settings such as crisis management and law enforcement.

For more information, visit Project Battuta
[/learn_more] [learn_more caption=”Project Varenius” state=”close”]
varenius.gif

Project Varenius

1997–1999

Principal Investigators:

Michael F. Goodchild and Karen K. Kemp

University of California, Santa Barbara

David M. Mark SUNY, Buffalo and Max J. Egenhofer

University of Maine, Orono

Motivated by scientific, technical, and societal concerns, the objective of NCGIA’s Project Varenius was to advance geographic information science through basic research, education, and outreach. The research was aimed to:

  • Serve science and scientists in two ways, focusing on areas in which our knowledge of formalizable geographic concepts is currently incomplete, and contributing to the development and refinement of tools and methods that scientists can use to study geographically distributed phenomena;
  • Provide basic understanding of geographic concepts, which is required for the production of new technologies;
  • Examines the impacts that these technologies have on individuals, organizations, and society, and that other digital technologies have in the context provided by geographic space.

For more information, visit Project Varenius
[/learn_more] [learn_more caption=”Project Gigalopolis” state=”close”]

gigalopolis.gif

Project Gigalopolis

1994–2002

Principal Investigators:

Keith C. Clarke

University of California, Santa Barbara

Gigalopolis is the growing urban structure containing billions of people worldwide. Urban settlements and their connectivity will be the dominant driver of global change during the twenty-first century. Intensely impacting land, atmospheric, and hydrologic resources, urban dynamics has now surpassed the regional scale of megalopolis and is now considered a continental and global-scale phenomenon.

Developed by Keith C. Clarke, Project Gigalopolis extended and refined the Clarke urban growth model, enabling predictions at regional, continental and eventually global scales. This work began through sponsorship from the United States Geological Survey’s Urban Dynamics program, and continued under the NSF-funded Urban Research Initiative.

For more information, visit Project Gigalopolis

[/learn_more] [learn_more caption=”Additional NCGIA Information” state=”close”] NCGIA Meetings

NCGIA Publications & Products

NCGIA Education

National Consortium on Remote Sensing in Transportation

Strategic Enhancement of NGA’s Geographic Information Science Infrastructure

Vehicle Intelligence & Transportation Analysis Laboratory
[/learn_more]

NGA

NGA

Strategic Enhancement of NGA’s Geographic Information Science Infrastructure

Partners:
University of Redlands (UR), lead institution
University of California, Santa Barbara (UCSB), research partner
Environmental Systems Research Institute (ESRI), corporate partner
National Geospatial-Intelligence Agency (NGA)

Started in 2000, Strategic Enhancement of NGA’€™s Geographic Information Science Infrastructure is focused on strategically enhancing the human and scientific infrastructure of the National Geospatial-Intelligence Agency (NGA). It involves a partnership between the University of Redlands (UR), the University of California, Santa Barbara (UCSB), Environmental Systems Research Institute (ESRI), and the National Geospatial-Intelligence Agency (NGA). This collaborative program links professionally-oriented graduate education, development of learning materials, and basic research in geographic information science (GIScience) through a number of initiatives designed to streamline the flow of knowledge and experience from research and education activities to practical implementation by NGA’s professionals.

 
For more information, visit Strategic Enhancement of NGA’s Geographic Information Science Infrastructure
View Major NGA Grant Awarded to Goodchild & Raubal

NGA Geospatial Feature Conflation

Geospatial Feature Conflation:
Conceptual, Statistical, and Optimization Approaches

NGA Grant Award image Before Conflation
Before Conflation
NGA Grant Award image After Conflation
After Conflation
NGA Grant Award Real World Image
Real World Image

Funding for Geospatial Feature Conflation:
Conceptual, Statistical, and Optimization
Approaches

A two-year research award to Mike Goodchild and Martin Raubal
10/1/2009–€“9/30/2011, with potential for renewal until 9/30/2014

Abstract
This research proposes to: design a relational-algebra framework for conflating geospatial data from diverse sources; develop statistical and optimization approaches for multi-source data integration; and develop new methods of spatiotemporal reasoning. The research will extend across different time instants and different data standards. It pertains to NGA’s 2009 NURI solicitation Topic #4.3: “Harvesting and Using Data from Heterogeneous Digital Sources” and is also partially relevant to Topic #4.6: “Using Qualitative Descriptions of Spatio-Temporal Entities.”

Four research themes will be addressed in this project: (i) development of a relational-algebra framework and formalization for conflating heterogeneous geospatial data; (ii) statistical and optimization approaches for conflating multiple geospatial data sources; (iii) provenance characterization and uncertainty evaluation in geospatial data conflation; and (iv) conflation-based approaches to spatiotemporal reasoning.

By describing and modeling the process systematically in a consistent manner, theme (i) is critical for understanding major components in heterogeneous data conflation and for providing guidelines for choosing appropriate methods. Theme (ii) addresses the issues of non-optimality in existing conflation techniques and of increasing data accuracy using statistical and optimization approaches. Theme (iii) aims to represent uncertainty propagation and quality assessment in conflation through provenance characterization and modeling. Theme (iv) proposes to facilitate spatiotemporal reasoning by developing conflation-based approaches that take into consideration geospatial data from various sources to construct multiple constraints about geographic features in a multi-dimensional space-time context.

Project findings will be disseminated through: (i) presentations at academic conferences and NGA meetings, (ii) publications in relevant journals, (iii) development of open-source prototypes using the proposed approaches, (iv) development of a Web service for conflation that can be incorporated into service-oriented architectures, and (v) applications of these techniques and approaches to several real-world case studies.

The proposed research will provide a theoretical foundation to the integration of incompatible geospatial data. This problem is currently addressed by ad hoc solutions using dataset-sensitive techniques. It will develop novel approaches to implementing the conceptual framework, thus improving conflation results and enhancing spatiotemporal reasoning. The findings of this project will not only meet the requirement of creating higher-accuracy data from multiple sources, but will also offer a new direction for utilizing rich yet incompatible geospatial data to facilitate spatial reasoning. Its results will be of substantial benefit to NGA, scientific researchers, policy makers, and the general public.

Objectives
The increasing and rapid development of remote sensing and other technologies as well as the growth of the Internet provide abundant opportunities to collect and access vast volumes of geospatial data. In addition to well-known datasets provided by government, such as US Census TIGER/Line files and free data services like Google Earth, large amounts of geospatial information are being generated daily by individuals worldwide, which creates an increasingly extensive net of volunteered geographic information. Large volumes of geospatial data have the potential to benefit scientific research, decision making, and everyday life. However, it is not always straightforward to take advantage of this abundance due to inconsistency, incompatibility, and heterogeneity among various datasets. Rather than a visual overlay of data from diverse sources, conflation of heterogeneous datasets provides a better solution since it opens possibilities for updating, averaging to obtain better estimates, and analysis and modeling. (Many terms are routinely used to describe different forms of geospatial data integration. Fusion is the accepted term when dealing with imagery, but here conflation is preferred as an umbrella term since the primary emphasis in this project will be on vector and mixed vector/raster integration.)

The difficulty of conflation depends on many factors, such as complexity of representation and the volume and accuracy of the datasets involved. Specifically, incompleteness and inaccuracy of the original datasets, different reference systems, distinct generalizations and representations of reality, semantic issues of terminology and classification, various scales, and different purposes, as well as various time frames all create challenges in the use of geospatial data from heterogeneous digital sources.

Although there are several ad hoc solutions of digital geospatial data integration designed for particular datasets (e.g., Saalfeld, 1988; Samal, Seth, and Cueto, 2004; Walter and Fritsch, 1999), geospatial data conflation has not been systematically and adequately studied as a general and fundamental problem in geographic information science. This project seeks to investigate integration and assessment of incompatible geospatial data by developing a comprehensive framework for conflation from diverse sources, and by creating methods that can effectively and efficiently incorporate multiple-source data into a consistent structure. Specifically, we propose to address the following four research themes, and to extend to other research questions if time permits:

  • A general conceptual and theoretical framework for conflation
  • Statistical and optimization approaches to conflation
  • Provenance characterization and uncertainty evaluation
  • A conflation-based approach to spatiotemporal reasoning

For more information about this project, please see NGA research grant to Goodchild and Raubal.
http://www.geog.ucsb.edu/events/department-news/