Difference between revisions of "Opencitysmart"

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## Participant categories: U, D, R
 
## Participant categories: U, D, R
 
## Free and open-source spatial analytics and GIS Development, SDIs suitable for rural local authorities etc.
 
## Free and open-source spatial analytics and GIS Development, SDIs suitable for rural local authorities etc.
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# [https://www.linkedin.com/in/sudhira Sudhira HS], [http://gubbilabs.in Gubbi Labs], Gubbi, Karnataka, India.
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## Participant categories: U, D, R
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## Spatial Planning Support Systems, Modelling and Analytics for Urban Planning and Decision-making, Urban Land-use/Land Cover change using Satellite Remote Sensing
  
 
== Global Drivers for 'OpenCitySmart' ==
 
== Global Drivers for 'OpenCitySmart' ==

Revision as of 19:48, 2 February 2016

Welcome to OpenCitySmart for Urban Infrastructure Management

OpenCitySmart will be a suite of tools to benefit city operations, such as management of urban infrastructure (utilities, traffic, services, etc.). The purpose will be to continually add and advance functionalities serving urban management, for more efficient operations and with ultimate consideration for increasing sustainability and quality of urban life.

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

Our intent here is that we have one powerful open platform that's easy to add functionalities to and that are easy to share.


What's an OpenCitySmart 'platform' look like?

A rough draft! Thank you City of Springfield Oregon, a brilliant guidepost for navigating the OpenCitySmart terrain.


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. Peter Baumann, Jacobs University Large-Scale Scientific Information Systems Research Group
    1. Participant categories: D, R, E
    2. Providing the [http:/www.rasdasman.org rasdaman] Array Database which enables flexible, scalable analysis on massive spatio-temporal sensor, image, simulation, and statistics data based on the open OGC "Big Geo Data" standards suite, WCS (of which rasdaman is Reference Implementation), plus WMS and WPS, and interfacing with a series of clients, such as OpenLayers, QGIS, NASA WorldWind.
  2. Chris Pettit, UNSW,
    1. Participant categories:
    2. Build and use planning support systems for empowering planners, policy-makers and communities in exploring city scale what if scenarios of sustainable, productive and resilient land use futures.
  3. 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."
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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?).
  21. 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?
  22. 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.
  23. Tuong-Thuy Vu, School of Geography, University of Nottingham, Malaysia campus.
    1. Participant categories:
    2. Big geospatial data analytics with applications to urban environment
  24. 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/
  25. Jeffrey Johnson, Independent Consultant, World Bank GFDRR,
    1. Participant categories:
    2. Geospatial Modeling for Disaster Risk Management
  26. 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
  27. 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
  28. 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.
  29. Patricia Carbajales-Dale, Clemson Center for Geospatial Technologies, Clemson University
    1. Participant categories:
    2. High Performance Computing for geospatial analytics.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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?
  35. 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
  36. Ruslan Rainis, Geoinformatic Unit, School of Humanities, Universiti Sains Malaysia, Penang, Malaysia
    1. Participant categories: R
    2. Urban big data, spatial/land use modelling.
  37. Stephan Winter, Geomatics, The University of Melbourne
    1. Participant categories: R, E
    2. Coordinating the Melbourne Urban Connectedness research cluster.
  38. Ingo Simonis, OGC
    1. Participant categories: U, R, E
    2. Standardization needs and solutions for Urban Science.
  39. Junyoung Choi, Spatial Information Office of Korea Land and Housing Corp(Public company) and Spatial Big Data Center at MOLIT, Republic of Korea.
    1. Participant categories: U, R
    2. Spatial Big Data for the Smart Cities in Developing Countries, Urban Spatial Measures for UN Sustainable Development Goals(SDGs); UN SDG 11. Making Cities and Human Settlement.
  40. Rizwan Bulbul, Director of Geospatial Research and Education Lab, Institute of space technology, Islamabad, Pakistan
    1. Participant categories: R, E
    2. 3D city modeling, 3D reconstruction, Spatio-temporal databases for cities, NSDI
  41. Emma Strong, Southern Mississippi Planning and Development District (SMPDD)
    1. Participant categories: U
    2. I work with the southern 15 counties of Mississippi and all cities and towns contained within. A few cities and counties have advanced GIS, mostly proprietary, but much of the area is rural with little to no GIS budget, so I plan to train myself so I can train others and spread GIS to more areas in the public sector. I think this project can help me to do that.
  42. Jaisen Nedumpala, Koorachundu Village Panchayat, Kozhikode, Kerala, India.
    1. Participant categories: U, D, R
    2. Free and open-source spatial analytics and GIS Development, SDIs suitable for rural local authorities etc.
  43. Sudhira HS, Gubbi Labs, Gubbi, Karnataka, India.
    1. Participant categories: U, D, R
    2. Spatial Planning Support Systems, Modelling and Analytics for Urban Planning and Decision-making, Urban Land-use/Land Cover change using Satellite Remote Sensing

Global Drivers for 'OpenCitySmart'

Key Research Questions

  • How can we transform cities to be more sustainable, productive and resilient?
    • Facilitate the ability for cities to work together in addressing issues all cities must face.
  • How can we empower cities, their citizens, community groups, planners, policy and decision-makers to work cohesively in addressing the issues our cities face such that they successfully engage in a sustainable urban future?
    • We build an app whose functionalities all cities can share and every city will also own.
    • If cities have a way to share solutions they generate for themselves, we address our own needs yet end up serving the interest of all. That's compound interest!

The Road Map

  • We can thank Brandt Melick, Information Technology Department Director, Springfield Oregon USA for putting this OpenCitySmart app idea into action! Will your city step forward to help lead our shared effort to make cities more productive and more livable?
  • 'OpenCitySmart' 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. INSPIRE Data Models
  2. Imagery Resolution, 3-inch pixel is preferred, 1-foot pixel less so, 1-meter much less so
  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, invaluable data, needing the tools to put it to good use. The City of Springfield has high resolution LiDAR, 8 points per meter. Though they put it to good use, they want even better tools to work with it (i.e., our OpenCitySmart app).
  • Challenges
  1. Technical e.g. raw data made usable, data dating, accurate geo-reference conversion, unit conversion (i.e., metric/standard), data storage, data security, firewalls, standardized metadata, etc.
  2. Legal e.g. investigating and suggesting the required framework to preserve privacy, ensure equity (equality in access to data and computing capacities), protecting IP and copyrights.
  3. Economic e.g. creating sustainable Research Infrastructures for the public and private sector, investigate possibilities for Public Private Partnerships.
  4. Social e.g. fostering public engagement in 'Big Data,' community participation in evaluation of current practices, data gathering, analysis and privacy issues.
  • Social dimension sub-roadmap - Any serious roadmap on urban management must consider the social dimension. In this respect, we need to:
  1. Identify necessary incentives and natural barriers for participation. How can we organize to meet the needs of the citizens affected? For instance, for academics, it might be how to utilize or create peer-review publication venues for contributed work that can reach the community. For practitioners, can we define the city's key or most pressing needs? For commercial 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, such as the users, customers, consumers, instead of focusing on producers of data, infrastructure, software and services. Beneficiaries might be: urban planners, city councils, citizens, teachers and students, scientists, and academia, 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 representatives of an intended target group, e.g. with champions in digital social innovation, or via associations that are directly connected to these communities, such as citizen associations.
  4. Engage with these people in order to identify their real needs for city analytics. This will help to accurately identify requirements, and acquire direct feedback. this should also include them in continuously active review panels.
  5. Evaluate the impact of proposed development activity, on existing development and on the natural environment. For city development 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.

Technologies Available In Our Network

  • NASA Web World Wind (JavaScript)
  • NASA World Wind (Java, iOS and Android)
  • Online What If? Planning Support System (Web version is now available)
  • QGIS
  • i-Locate
  • GeoMoose
  • Policrowd2.0
  • Europa Challenge Open Source Projects 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
    • Multi-temporal, 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)

Natural Partners

OpenCitySmart 'The App'

The Task

Develop an OpenCitySmart App based on 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
  • Open Street Map (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 OpenCitySmart 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. This app will have an open API for the menu system, for easy-to-add functionalities. This will allow each city to tailor the OpenCitySmart app for their specific use. This will also allow the world community to continually optimize functionalities and design new ones, whether proprietary or FOSSy.


Who Will Do This?

We ask academic and other community oriented organizations, such as those listed as Natural Partners, to help us with the Road Map.


Why Do This?

Because there is a world full of urban management need, much of which is identical no matter the city. If you are brave and good, just build it and be a lightning rod for our brighter future. The Region and Theme Chairs will evaluate self-identifying contributions, http://wiki.osgeo.org/wiki/GeoForAll.


Understanding our Changing Planet.

  1. Historical tracks of hurricanes.
    1. SLOSH http://www.nhc.noaa.gov/surge/slosh.php
  2. LiDAR - local communities are using UAVs to generate their own LiDAR maps. Plus several states have LiDAR datasets.
  3. Biodiversity
    1. Datasets include:
      1. Landfire http://www.landfire.gov/
      2. Crop Scape http://nassgeodata.gmu.edu/CropScape/
      3. VegScape http://nassgeodata.gmu.edu/VegScape/
  4. Vulnerability Issues
    1. Social Vulnerability Index: http://webra.cas.sc.edu/hvri/products/sovi.aspx
    2. Data sources:
      1. http://www.cocorahs.org/Content.aspx?page=store
      2. http://openweathermap.org/
  5. 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/

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
    • Ela Wołoszyńska-Wiśniewska, Warsaw, Poland, heat island, flooding and flash floods, 21.020, 52.259
    • Hande Demirel, Istanbul, Turkey, drought, flash flood, heat island, sea storm surge, 41.0136, 28.9550
    • Helena Mitasova, Raleigh, NC, population growth, tornadoes, hurricanes, flash floods, 35.7818,-78.6764

OpenCitySmart - important journals

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