Difference between revisions of "GeoForAll UrbanScience CityAnalytics"

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** All participants aim to reuse, optimize, extend and add new components (in that order)
 
** All participants aim to reuse, optimize, extend and add new components (in that order)
  
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Our intent here is that we soon will have one or a few '''core platform(s)''' each architected with an open API for functionalities (the menu system). This effort will benefit from friendly competition, with the best features of each 'competing' platform eventually residing in our collective decision for a '''core platform'''.
+
Our intent here is that we soon will have one or a few '''core platform(s)''' each architected with an open API for functionalities (the menu system). This effort will benefit from friendly competition, with the best features of each 'competing' platform eventually residing in our collective decision for a '''core platform'''. What's a '''core platform''' look like? [http://nsdinow.org/SDI_Now_02/Technical_Support_files/SDI-Now_v01.pdf Click here!]
  
  

Revision as of 12:04, 22 June 2015

Welcome to "Geo for All" Urban Science and City Analytics: 'CitySmart'. . .'Urban Resilience'

CitySmart will be a suite of tools to maximize effective government operations, such as management of infrastructure (utilities, traffic, services, etc.). CitySmart will combine continual advances in efficient operations with ultimate consideration for increasing sustainability and the quality of urban life.

  • Chairs: Chris Pettit (Australia) and Patrick Hogan (USA)
  • We support the 'Open Cities Guiding Principles:'
    • All material created is made available for all under an Open License
    • All material is carefully designed so that it can be extended by others, i.e., API-centric, modular componentry, etc.
    • All participants aim to reuse, optimize, extend and add new components (in that order)

Our intent here is that we soon will have one or a few core platform(s) each architected with an open API for functionalities (the menu system). This effort will benefit from friendly competition, with the best features of each 'competing' platform eventually residing in our collective decision for a core platform. What's a core platform look like? Click here!


Who's Who Here?

  • Please let us know of your interest to participate by adding yourself to this list.
  • Please identify yourself in one or more categories: U: User/practitioner; D: Developer; R: Researcher/Scientist; E: Educator.


  1. Chris Pettit, UNSW,
    1. Participant categories:
    2. Coordinate the implementation of eResearch tools to support urban researchers across Australia under the auspices of the Australian Urban Research Infrastructure Network (AURIN).
  2. Charlie Schweik and Alexander (Sasha) Stepanov,
    1. Participant categories: R, E
    2. University of Massachusetts Amherst. Trying to build educational service learning opportunities for students on advanced GIS using our campus as a "testbed."
  3. Tom Mueller, California University of Pennsylvania
    1. Participant categories: E - Educator
    2. Similar to Charlie, I want to build educational exercises and service learning opportunities for my students.
  4. Jim Miller, University of Kansas, Computer Science
    1. Participant categories: D, E (also R in terms of computer science and visualization techniques)
    2. Using NASA World Wind for several open source geo-visualization efforts, including Lidar and multivariate scalar and vector field visualization.
  5. Brandt Melick, Information Technology Department Director, Springfield Oregon USA.
    1. Participant categories: U
    2. Manage IT and GIS in support of community development, involving public works, and fire and life safety. Coordinate NSDI exchanges of cadastral, elevation and environmental information between local, state and federal agencies in the Pacific Northwest.
  6. Ant Beck, University of Nottingham Research Fellow.
    1. Currently transitioning into CityAnalytics looking at city wide entropy based energy management simulations. Have aspirations for an open, big data environment.
  7. Phillip Davis, GeoAcademy.
    1. The GeoAcademy is using QGIS 2.8 to provide Massively Open Online Courses through the Canvas Network to students around the globe for free. We currently enroll over 4,000 students in our March 2015 cohort.
  8. Patrick Hogan, NASA World Wind Project Manager.
    1. Participant categories: D, R
    2. Building open source virtual globe technology meant to stimulate innovative solutions managing geospatial data, whether open or proprietary.
  9. Antoni Perez-Navarro, Universitat Oberta de Catalunya,
    1. Participant categories: R, E
    2. Currently working on indoor positioning systems. Previously developed the Context Aware Recommender System. In the GIS subjects we use gvSIG and QGIS, and Geomedia as proprietary software. Our students have also developed projects using Open Layers, GeoServer, Google Maps and Open Street Maps.
  10. Giuseppe Conti
    1. Participant categories: U, D, R
    2. Trilogis Srl, Italy. Working on the open standard for indoor/outdoor interoperable location services (http://www.i-locate.eu/) involving multiple cities, hospitals, museums, etc.
  11. Evangelos Mitsakis
    1. Participant categories:
    2. Centre for Research and Technology Hellas - Hellenic Institute of Transport, Greece. Working on climate change adaptation, urban resilience and smart cities, focusing on intelligent transport and mobility.
  12. Gábor Remetey, Secretary-general, Hungarian Association for Geo-information (HUNAGI),
    1. Participant categories: R
    2. Strategic planning, implementation and consultancy in geospatial IT, and building contacts at the domestic, regional and global levels for Hungarian GIS and the Earth Observation community.
  13. Maria A Brovelli, Politecnico di Milano
    1. Participant categories: D, R, E
    2. Applications of free and open-source spatial analytics to urban context and its development, Citizen Science and collaborative multidimensional platforms.
  14. Ron Fortunato, President of Trillium Learning LLC
    1. Participant categories: U, E
    2. Custom design and implement Project-Based Learning systems, networked region-wide and at the national scale, and guaranteed to provide a teacher-complimentary exciting learning experience for students, elementary through secondary education.
  15. Xinyue Ye, Computational Social Science Lab, Kent State University
    1. Participant categories: D, R, E
    2. My research focus is open source space-time analysis method development and its socio-economic application, especially on economic inequality, urban development, crime, and social media.
  16. Andrew Hunter, GIScience Group, University of Calgary
    1. Participant categories: R, E.
    2. Teach GIS, Land Use Planning and Cadastral Studies. Research focuses on the development of interoperable (open source) frameworks for land use planning, land development, and geospatial approaches for enhancing community engagement.
  17. Hande Demirel, Geomatics Engineering Department, Istanbul Technical University
    1. Participant categories:
    2. Lecturer for undergraduate and graduate students on spatial information systems. Research focus is spatial data acquisition, modelling spatial data, intelligent transportation and impact analysis for smart cities.
  18. Lucy Bastin, University of Aston and Joint Research Centre of the European Commission
    1. Participant categories:
    2. Focus: quality issues with geospatial data and VGI, e.g., making best use of cheap, plentiful but variable sensors such as weather stations for urban decision making on, e.g., dynamic routing of gritting trucks. I work on interoperable solutions for communicating data quality , e.g., UncertML and the OGC SWG on user feedback.
  19. GeoDa Center for Geospatial Analysis and Computation, Arizona State University,
    1. Participant categories:
    2. Applications of free and open-source spatial analytics and decision support systems to urban modeling and scenario planning (but who at GeoDa do we contact?).
  20. Sven Schade, Joint Research Centre of the European Commission
    1. Participant categories:
    2. I am a geospatial information scientist working on knowledge extraction from (big) data by using geospatial analytics capabilities, multidisciplinary interoperability, and open innovation. How can we make data from public, commercial and private sources usable for social good?
  21. Bob Basques, City of Saint Paul, Mn. USA,
    1. Participant categories:
    2. My background is in Spatial Information Management for the City of Saint Paul, Public Works, with just under 300,000 residents. Providing access to hundreds of spatial layers, originating from the City, the Metro Region, County, State, and Federal sources to both public and internal users. Big Open Source proponent and developer.
  22. Tuong-Thuy Vu, School of Geography, University of Nottingham, Malaysia campus.
    1. Participant categories:
    2. Big geospatial data analytics with applications to urban environment
  23. Helena Mitasova, North Carolina State University, Center for Geospatial Analytics, OSGeo REL
    1. Participant categories:
    2. Geospatial modeling and visualization for GRASS GIS, simulation of urban growth - incorporation of FUTURES model into GRASS GIS, Tangible landscape: collaborative modeling environment using interactive 3D printed or molded physical models
    3. The City of Raleigh strives to become a worldwide model for an open source city http://www.raleighnc.gov/open/
  24. Jeffrey Johnson, Independent Consultant, World Bank GFDRR,
    1. Participant categories:
    2. Geospatial Modeling for Disaster Risk Management
  25. Serena Coetzee, Centre for Geoinformation Science, University of Pretora, South Africa, and Chris Wray, Gauteng City Region Observatory (GCRO), South Africa
    1. Participant categories: R (UP and GCRO), E (UP)
    2. Open (big) geospatial data in the context of geovisual analytics for smart city planning
  26. Dimitris Kotzinos, ETIS Lab, University of Cergy Pontoise, France
    1. Participant categories:
    2. Trajectory mining, data semantics and integration of city data, data analytics with application to urban and domestic environments, personal data management
  27. Xingong Li, Department of Geography, University of Kansas
    1. Participant categories:
    2. My research interest in Urban Science and City Analytics is in water infrastructure and smart water use.
  28. Patricia Carbajales-Dale, Clemson Center for Geospatial Technologies, Clemson University
    1. Participant categories:
    2. High Performance Computing for geospatial analytics.
  29. Cameron Shorter, Co-coordinator of http://live.osgeo.org, which packages up ~50 of the best Open Source GIS applications, along with data and quickstarts;
    1. Participant categories:
    2. Also geospatial solutions architect at http://lisasoft.com, Sydney, Australia.
  30. Rick Smith, Spatial {Query} Lab at Texas A&M University - Corpus Christi
    1. Participant categories: R, E
    2. Use of mapping technology for emergency response and planning. Update and maintain freely-available university-level FOSS4G curriculum.
  31. Michael Starek, Geospatial Sensing and Analytics at Texas A&M University - Corpus Christi
    1. Participant categories: R, E
    2. My research interest in Urban Science and City Analytics is in the application of emergent geo-sensing techniques for monitoring of the 3D build environment.
  32. Rafael Moreno, Department of Geography and Environmental Sciences, University of Colorado Denver.
    1. Participant categories: E, R
    2. Incorporation of FOSS4G in Geography and Urban and Regional Planning curricula. Land use planning, natural resources management, GIS science and Technology.
  33. Austin Troy, Department of Planning and Design, College of Architecture and Plannig, University of Colorado Denver.
    1. Participant categories: E, R
    2. Land use policy, environmental planning, GIS, spatial analysis, remote sensing, land use change modeling and simulation?
  34. Farnoush Banaei-Kashani, Department of Computer Science and Engineering, University of Colorado Denver.
    1. Participant categories: E, R
    2. Big data management and mining, database systems, data-driven decision-making systems
  35. Ruslan Rainis, Geoinformatic Unit, School of Humanities, Universiti Sains Malaysia, Penang, Malaysia
    1. Participant categories: R
    2. Urban big data, spatial/land use modelling.
  36. Stephan Winter, Geomatics, The University of Melbourne
    1. Participant categories: R, E
    2. Coordinating the Melbourne Urban Connectedness research cluster.

Global Drivers for OSGEO Solutions


Key Research Questions

  • How can we transform existing cities or create new cities that are sustainable, productive and resilient?
    • Easy, we work together as one species to solve common problems.
  • How can we empower citizens, community groups, planners, policy and decision-makers to work cohesively in solving the problems our cities face such that they successfully engage in a sustainable urban future?
    • By making this Road Map a reality, all cities will share something they need yet each will also own.
    • This also gives them a way to share back the solutions they discover 'for the benefit of all.'


Urban Resilience 'The Road Map'

  • We also heap a world of praise upon Brandt Melick, Information Technology Department Director, Springfield Oregon USA for putting this CitySmart app idea into action! We need to help more cities step forward like this, lead by example!
  • 'CitySmart' App Themes/Data-type (feel free to expand):
  1. INSPIRE Data Specifications
  2. Urban Planning
  3. Intelligent Transportation
  4. Health & Medical Services
  5. Public Safety & Emergency Services
  6. Environmental Protection
  7. Intelligent Buildings
  8. Utilities: Smart Grid, Smart Water, Sanitation, etc.
  9. Location-Based Services
  10. Indoor Positioning System
  11. Context-aware Recommender Systems
  • Data sharing – Cities need to be able to share information with site developers, site constraint specialists (environmental scientists, planners and engineers), utility service providers and regulators. These data sets most often include:
  1. Data Models
  2. Imagery (3-inch pixel is preferred, 1 foot pixel is less preferred, 1 meter is getting much less preferred)
  3. Cadastral Information (parcel polygons, Rights of Way (ROW), property ownership, assessment and taxation information and property class)
  4. Address Information (house number, street name, City, zip, site location (coordinates) and zoning information)
  5. Jurisdictional boundaries (incorporated areas, city limits, county boundaries, etc.), urban growth boundaries, public safety response areas
  6. Elevation Information: DEM’s (raster), DTM’s (vector), contours and spot elevation points, as well as mass points and break lines
  7. Waterways and protected areas: wetlands, fish-bearing streams, endangered species habitat, well-head protection zones, etc.
  8. Infrastructure/utilities: waste-water, storm-water, transportation systems, power, drinking water, etc.
  9. Structures/facilities: bridges, building foot prints, complexes, monuments, etc., facility contacts, etc.
  10. Documents: reference material, procedures, regulations, metadata, etc.
  11. Lidar, everyone wants it, along with better tools to put it to good use. The City of Springfield has high resolution Lidar, 8 points per meter, and they know what to do with it. Though they still want for better tools to work with it (i.e., our CitySmart app).


  • Technical Challenges - there are many, here are just a few: raw data made useable, data dating, accurate georeference conversion, unit conversion (i.e., metric to standard), data storage, data security, firewalls, standardized metadata, etc.


  • Yet to be discussed:
  1. Legal challenges e.g. investigating and suggesting the required framework to preserve privacy, ensure equity (equality in access to data and computing capacities), protect IP and copyrights.
  2. Economic challenges e.g. creating sustainable Research Infrastructures (RI) for the public and private sector, investigate possibilities for Public Private Partnerships (PPP).
  3. Social challenges e.g. fostering public engagement in Big Data, participation in related debates, evaluation of current practices, data gathering, analysis and privacy issues.


  • Social dimension sub-roadmap

Any serious roadmap on urban science should certainly consider the social dimension. In this respect, we would need a subsequent actions such as:

  1. Identify in our Who's Who here what categories of participants we are and what are their incentives or barriers for participation. How can we organize to meet the needs of the participants involved? For instance, for academics, it might be how to utilize or create peer-review publication venues for contributed work. For practitioners, can we define their key or most pressing needs? For developers, are they in situations where their employer will see contributions to a global effort something they should be doing?
  2. Identify the intended direct beneficiaries (aka users, customers, consumers) - instead of focusing on producers of data, infrastructures, software and services. Possible beneficiaries might be: urban planners, scientists/academia, city councils and majors, citizen, young people (pupil and students), etc. While these intended audiences might partially overlap, all might have different needs and need a different approach for participation.
  3. Identify and get into contact with some representatives of the intended target group, e.g. with champions in digital social innovation and open minded individuals, or via associations that are directly connected to these communities, such as citizen associations.
  4. Engaging with these people in order to identify their real needs for city analytics, in order to first of all get their requirements, but also to co-develop products, get direct feedback (e.g. be including them in review panels for the NASA WW Challenge), etc.
  5. Expand from few collaborations into a wider network in which solutions are replicated or adopted for one city after the other - each time customized to the individual needs.
  • A couple important topics here that might be useful in future grant proposals.
    • First, the idea that we as a group are undertaking "transdisciplinary research around urban science" (Dedeurwaerdere, 2014). According to Dedeurwaerdere (2014: 138): 'Transdisciplinary implies that the precise nature of the problem... needs to be defined cooperatively by actors from science and the life-world.'
    • Second, perhaps we should focus on topics related to urban sustainability and resilience and the geospatial analytical processes and tools needed to support decision-makers in that capacity? Dedeurwaerdere (2014: 139) defines sustainability as the 'maintenance of capital," and is often used in the context of "environmental sustainability" -- the maintenance or non-declining of natural capital. So one question for our group might be what areas of "urban sustainability" might we want to focus our efforts on?


  • Key City Analytic Needs or Needs by our Community above. (Add topic entries or your name under existing entries)
    • Crime mapping analytics
      • Tom Mueller


  • Use-Case: Urban Planning and Site Review – Municipalities need to evaluate the impact of proposed development activity, on existing development and on the natural environment. This typically includes estimating how much cut and fill is proposed, how proposed land alteration impacts surface drainage, how proposed structures will connect to city services (waste-water, storm-water, drinking-water, power, etc.), how steep the roads will be (slope for fire trucks), and proximity to wetlands and other protected waters of the state. These data most often include:

Technologies Available In Our Network

  • NASA World Wind (Java, iOS and Android, Web version on its way)
  • GeoMoose
  • QGIS
  • i-Locate
  • Policrowd2.0
  • Europa Challenge Open Source Projects 2013, 2014, 2015
  • Open Transit Indicators Enable Cities to Design Better Transit Systems
  • Australia Urban Intelligence Network, AURIN Portal and workbench
  • Arizona State University (ASU) GeoDa
    • The GeoDa Center for Geospatial Analysis and Computation develops state-of-the-art methods for geospatial analysis, geovisualization, geosimulation, and spatial process modeling, implements them through open source software tools and applies them to policy-relevant research in the social and environmental sciences.
  • GRASS GIS
    • Multitemporal, full 3D GIS research platform with many processing, analytical, modeling and visualization tools relevant to Urban Science and city analytics (lidar-based models, solar energy, viewsheds, networks, water resources, full 3D visualization with animations and many others in the core package, with additional tools, including civil engineering design in add-ons)

Potential Partners

Urban Resilience 'The App'

The Task

Develop a CitySmart Urban Resilience App with your idea for the Requirements doc, essentially the 'specs' for what this Urban Science - City Analytics, CitySmart app looks like, and will likely be based on information in the 'framework' documents mentioned above in the Road Map section.

The City of Springfield Oregon has already shown us the way forward.

Some basic requirements:

  • 3D Virtual Globe interchangeable or simultaneous with 2D Map along with Projection Choices
  • Imagery & Elevation Import
  • Extensible Architecture (Modular Componentry)
  • Data Retrieval via REST, WMS, WCS, WFS, GML, User-Defined
  • OSM Placenames, Boundaries and Roads
  • Picking and Decluttering
  • Shapefile and KML Import
  • Measurement Tools
  • Flooding and Line-of-Sight Calculation
  • Subsurface Visualization
  • Shapes: Placemarks, Path, Polygon, Extruded Polygon, Custom, HTML5-able Balloons
  • Volumes (& Shapes), follow terrain or maintain constant elevation above terrain while moving


This CitySmart app needs to allow for some early successes so we can get buy-in from 'real' municipalities to work with us and thereby keep value-added precisely on target. After the Road Map, then what? Then we challenge Earth's FOSSy development community to provide their solution in response to the Road Map. 'Twoud be fine if we could gather a nice award package for that.

After we (the OSGEO community) evaluate these ‘solutions,’ some will be asked to mashup until in the end we have one OSGEO/FOSS4G/GeoForAll CitySmart app. This app will have an open API for the menu system, for drag-n-drop of functionalities. This will allow each city to tailor the CitySmart app for their specific use. This will also allow the world community to continually optimize old functionalities and design new ones, whether proprietary or FOSSy.


Who Will Do This?

Whoever wants to! We ask academic and other organizations to first help us with the Road Map (the Requirements doc), such as those listed as Potential Partners, http://wiki.osgeo.org/wiki/GeoForAll_UrbanScience_CityAnalytics#Potential_Partners. Or just build it! All are welcome!


Why Do This?

Because we can! And more importantly, because there is a world full of urban management need, much of which is identical no matter what urban location we are in. For a little encouragement, how about a NASA crystal bull for the best Road Map, just like for the Europa Challenge, http://eurochallenge.como.polimi.it/, and of course NASA T-shirts. We need YOU (whoever you are) to design the requirements doc and build the for the CitySmart app.

If you are brave and good, just build it and be a lighthouse guiding our future. If you do this, and no one else does, you get the crystal bull. If others do theirs along with you, then we vote and that winner gets to mash-up the best from what's in the ‘other’ CitySmart apps. We will ask the Region and Theme Chairs to do the voting, http://wiki.osgeo.org/wiki/GeoForAll. Understanding the Changing Planet.'

  1. Historical tracks of hurricanes.
    1. SLOSH http://www.nhc.noaa.gov/surge/slosh.php
  2. Geodesign. I know that ESRI has used this term a lot. It might be something that we examine in the Open Source world
  3. LiDAR - people are using UAV for LiDAR now. Plus several states have LiDAR datasets.
  4. The question I thought about is - can we create citizen scientists to properly gather some of this information.
  5. Biodiversity
    1. They discussed the issues of Land Cover and using coarse remote sensing images (LandSat)
      1. There is a program that will be starting up soon via USGS called Adopt a Pixel - which is to help with that fuzziness
      2. This might also be able to help with the National Land Cover Dataset.
      3. They discussed creating a Gap Analysis to understand issues of biodiversity, etc.
    2. Datasets include:
      1. Landfire http://www.landfire.gov/
      2. Crop Scape http://nassgeodata.gmu.edu/CropScape/
      3. VegScape http://nassgeodata.gmu.edu/VegScape/
  6. Vulnerability Issues
    1. Social Vulnerability Index - we might want to examine it: http://webra.cas.sc.edu/hvri/products/sovi.aspx
    2. Another study O'Brien 2004 discussed vulnerability
    3. Data to grab as reading. I thought of these two sources
      1. http://www.cocorahs.org/Content.aspx?page=store
      2. http://openweathermap.org/
  7. Quite a few people have created indexes on health care coverage and access. These studies might be helpful to examine. These really sounded interesting to me. So if we are going to use this variable I would like to examine these topics. p.72 in study
    1. Lou and Wang 2003
    2. Wang et al 2008
    3. McLafferty and Wang 2009
    4. Rushton et al 2004
  8. Movement
    1. Traffic flow data
  9. Inequality
    1. Issues of Digital Divide
    2. Maps that show hot spot areas of concern
  10. Geodemographics
    1. In USA, a lot of this type of data is in the hands of private companies, so it may be difficult to access this data. ESRI Tapestry, etc.
  11. Possible indexes, include -
    1. Risk Terrain Model http://rutgerscps.weebly.com/rtm.html
    2. Flash Flood Potential Index http://www.crh.noaa.gov/images/dmx/hydro/FFPI/FFPI_WriteUp.pdf
    3. Crisis Mapping and Ushashidid - http://www.ushahidi.com/

Reference Material

  • Resilience: A Bridging Concept or a Dead End? http://www.tandfonline.com/doi/full/10.1080/14649357.2012.677124
    • “Reframing” Resilience: Challenges for Planning Theory and Practice
    • Interacting Traps: Resilience Assessment of a Pasture Management System in Northern Afghanistan
    • Urban Resilience: What Does it Mean in Planning Practice?
    • Resilience as a Useful Concept for Climate Change Adaptation?
    • The Politics of Resilience for Planning: A Cautionary Note
  • Veeckman, C. and van der Graaf, 2015. The City as Living Laboratory: Empowering Citizens with the Citadel Toolkit

Lab nearest city and vulnerability threats, lat/long coordinates

  • Colleagues, please list (1) your name, (2) the city your lab is closest to, (3) the possible threats that city might face in future years related to population growth and/or the effects of climate change (e.g., coastal storm surge, hurricanes, heat islands, inland lack of water, etc.) and (4) your city's lat\long. I'm hoping to map all the cities in our network for a figure for future grant proposals.
    • Charlie Schweik, Springfield, MA, hurricanes, heat islands, 42.393578, -72.524696
    • Thomas Mueller, Pittsburgh, PA, heat island, increased flooding due to climate change, 40.440625, -79.995886
    • Patrick Hogan, Moffett Field, CA, drought, sea-level-rise, 37.42, -122.06
    • Antoni Perez-Navarro, Barcelona, Spain, lack of water, drought, flooding, sea-level-rise, 2.173403, 41.385064
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