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UrbanFootprint: Next-Gen Scenario Planning Tool

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In my view the world in my mind and the number you short have the uh the the head and the fish and the and go through the use of a and a lot of you have have the uh the head and the fish that no 1 can go through and you know it the and the 2 of you you you know if the and and the head and the er ror around runaround around around here and I had it in the in the in the fall the what we want the all the of the all good yes the the the thank you for the kind of the 1 and 2 and 4 of of is and the is and the you the in the head and the the uh the head and the fish but no progress through the environment and go through a the use of a and a lot of the time and you you and you there's also this is indeed a new feature it after of what you have on the very properties that yet so if you want a settlement recognize and it also has a power of the book book and that it's the and and the and and that of and
the and thank you thank and the special is while you just on the problem the whole thing with that of the good of the and the often with the couple couple times alterations and this much of this a B and and again it started it's 1 o'clock so it will let me know if this might doesn't pick me up it sounds like it's OK from here that think about it look at the so this is a a presentation about and urban planning platform how many of you are in the urban planning business thrust OK 1 of the great of so some of you have and how many people are familiar with urban footprint or just for the word can you this is so our urban footprint is an open-source planning propped up platform and what is a Scenario Planning Platform well it's a suite of tools that let cities and regions compare alternative land use features from so for instance alternative land use features might be deciding whether land use development was to be business as usual service sprawl auto oriented versus green more green Compaq growth around transit so the the goal of urban footprint is to help cities in municipal regions the the creator or take the existing future land use plans they have on show them on show them on a map look at the future data and run analysis to see both what the differences are between the base year of the study might be 2012 for instance when they gathered the data in a future scenario years such as 2050 Our or 2030 and then all get more into this but the goal is to see how this difference future scenarios compare so 1 and then you choose I'm not Garland Woodsong who listed in the program I am the primary software all perfervid footprint not Calthorpe Associates is an urban diet design and planning firm located in Berkeley California and were very where a small team with the big product so hopefully there's something here of interest to you it is so this kind of program is often called the a sketch tool because it literally that's you sketch futures on the map which will will get into on the interface on on you're going to have you have a base passes on the map that show you what's on the ground and then the order to sketch a future scenario and run Alex of the of the project is also exciting because it is fully open source the stack is in open source stack and all get into details on that since I'm the software guy and and lesser presenter planted I feel free ask me questions on anything but I'm in no more amenable to give you a lot of information on the software and I might I might have did differ little bit on some of the planning elements of of so the cult of associates has been around for a long
time they have decades of of experience with scenario planning and you can see some of the regions that we've worked in our focus is on transit-oriented development and Compaq growth trying to meet some of these global and regional climb environmental health goal said a lot of your surely interested in some we've been leveraging geospatial software technology for a long time with the goal of improving the efficiency and the visibility of the planning process we specialize in regional planning and we also work with individual cities and towns what that urban
footprint started was a practical vision California which took place from 2008 to 2012 approximately and this is a project that was funded by the California High Speed Rail Authority along with the California Strategic Growth Council and to basically shows some of the differences how these different future scenarios could have impacts on environmental fiscal and health I and really to tie to really tiny and the interplay with transportation and land-use investments so rather than looking at them in a siloed is set to show how where you build our the can impact your either positive or negative results so we modeled data in the 5 major population regions of California and when you're doing this kind of geographic analysis attended some and also when you're dealing with this many features and doing analysis you tend to some limits of traditional modeling software and we actually broke the proprietary software that we're working with we're having 12 hour long runs of analysis that would would go overnight and then end up with a you know very mysterious error message and so the team was actually forced into open source and open source stack and we're very happy that we moved in that direction also so we started with we moved into the post GIS Django and we're using OpenLayers that was the original division California product so here is
just 1 of the many outputs of the vision California projects this shows we we analyze the number of different future scenarios but this shows the 2 extremes business as usual sprawl audio oriented the business park in the suburbs kind growth verses growing smart which is really a kind of a package of of more aggressive green scenarios are designed to concentrate growth of around the existing and future trends in networks so you can see on the left a lot of that pink area he is near population centers but really sprawled out and on the right you can see much more compact growth around the planned high-speed rail corridor from 7 Cisco Sacramento and San Diego and very happily that high speed rail project is now finally being constructed it the um we also show some slides at the end of the presentation that demonstrates the the impact of these different scenarios on on important analysis like greenhouse gas emissions Public Health fiscal impacts water energy yeah and please on a few questions I know some of this stuff especially for non planners can go right every had so stop me if any of this doesn't make sense us so here's a look at the 2 software products that came out of the vision California process the 1 on the bottom is actually and called rapid-fire and that's actually a spreadsheet spreadsheet-based model it's for non geospatial comparison of scenarios for this was developed for regions that you don't have access to geospatial data or don't need to do geospatial comparison they might just have a few different future scenarios that they're looking at compact sprawler something in the middle and they have some policy packages they wanna compare with the results are so rapid fire was designed to work without a geospatial analysis urban footprint the 1 on the top is the 1 that this talk is going to focus on and that is the Web VIP web-enabled open source and geospatially obviously where platform I so urban footprint like a lot of GIS applications starts with you gotta start with your data the and you have to get your data together organize it and then the other 2 parts of or urban for print are taking up based data developing scenarios and running analysis so the in in terms of data development organization our clients which are typically the regional entities or typically provide us with feature data it's often possible but it could be something bigger like transportation areas and that data at a minimum needs to contain information about employment categories on the parcels or other features and as well as dwelling unit categories and probably some kind of land use code so that we can categorize it and show it on the map they might also need to supply us with additional data such as information about water and energy usage so that we can run certain types of analysis other data we can sometimes I infer from census data so it's what we get depends on what the client has available and what we can get from elsewhere so once you have that base data load it gets normalized into our system and at that point the client is able to visualize 1 or more layers on the map usually there the Bay State apostles we would say but perhaps also transportation networks that they've given us I'm so that's sort of a starting point where you can leave you your the features that you have on the ground representing and such as 2014 the next step is to actually create or import the future scenarios which are gonna be your yeah 2 or more alternative scenarios that you want analyze oftentimes the client will already have future scenarios on the books but a lot of assessing California the regional entities are required by law to come up with our future plans for every 6 every few years for a certain target years so they might have a few different alternative plans for 2040 say oriented books and then it's our job to take those plans and translate them in urban footprint and that gives us scenario development now might also be the case that you have no future plans or you wanna modify 1 in which case you might start with the base scenario and create a future scenario and literally paint futures on a map you select certain certain parcels and say well this used to be this and I wanted in 20 to be this so 1 might do core and say I want all the low density single family homes that are within this distance of a transit stop and we want to upgrade them to mixed-use development for the target year and that way you get a certain increase of of certain employment categories and dwelling unit categories increase whereas other ones might decrease the so so the way you do it you're going to get future scenarios whether imported or made from scratch or a combination of the 2 while you making his future scenarios you have the opportunity to run analysis on them and something else is very simple is just saying well what's a delta from the base year to the future year how many how much more employment of certain types we have how much how many more dwelling units do we have other analysis all the module shown here are in you are somewhat more complex a very complex we have things like what are the local fiscal impacts for the public health impacts on transportation you can do the anti analysis vehicle miles traveled and that's a much more complicated 1 that requires analysis of travel networks um so I know the rest the presentation is going focus on that these 3 different all parts of the new development analysis the
so it's start with the stack for those that are interested in this starting from the top going down the bottom on the website if things were producing calling out for the maps that's transitioning to leaflets and spalling apps is no longer supported we we use the but a JavaScript framework called sprout for which enables us to do a single page web app it's very powerful Model-View-Controller from our framework for those of you who know what that is let us do a single page up with a lot of complex functionality in embedded into the system on the server side we've got Django running Python PostgreSQL's jails but other than than to usual suspects in this world are we also work with the 3 4 our charting and we do some socket I O of code to send messages back and forth to the client and we'll so we'll see style stash are under a tiles on the server side the let me know if you more questions on this i can talk forever about this are so here's a 1st look at urban footprint on this is a map of the city of Irvine in a Los Angeles region it shows their parcels and it's colored by the land use codes that they gave us so we focus of course on of the map is the center of attention we wanna make sure that most the interaction is it involves looking at the map from we support a limited set of features on a map such as navigation of course and but also selecting features and very targeted editing of those features so we don't allow users to just added any feature they want we usually create specific editors that's tailored to their workflow In the case of Irvine and they need they need to be a review their land use codes edit them and then and then comment on the edits they made so that interface this low inter at interface on the right is doing just that the rest of the app here you've got your your various layers on the left which is on the number of layers they can bring in the system and we typically preconfigure layers for them at this point because of that the complexity of it but we also have the ability to import of certain types of layers and x 4 layers on to various formats we don't yet have we don't yet have a starling tool or a map legend tool but that's on short term roadmap so we're really hoping to have you pretty full-featured input and output and editing process for the layers in the near term you can also there is also way are later organize you can drag and drop layers to to get the water on the map that you want on the top is a query editing interfaces 1 of the newest parts of the out this is you very powerful sequel based of querying of the map features and you can do all the typical sequels operator you can do filters you can join any 2 later tables together geographically or by at tribute and so you can also do aggregation Saigon some your dwelling units employment a average them and then you can you can group by other Rach pizza you you might for instance have several jurisdictional codes that represent different cities in your region you might want to group by those jurisdictional codes and say well I want I wanna know what my average employment is er or break it down by certain employment categories and get the selections on the map so this these are quarry results were seeing here for individual features but you can also get aggregate results and and show them there and export than the CSP in other formats the on and finally on the right I show that before that's the the pop out interior but that also 0 we can run analysis so we do a lot of different projects for different clients based on their needs some in the case of we just did a project for the southern out Southern California Association of governors also notice gagging staggers the largest metropolitan planning organization in the United States they have 100 and 190 cities in 6 counties so when every do work with skag you're dealing with immense amounts of data so for this project it was a data review pilot and what they wanted to do was take the data that they had at the regional level and expose it to the various cities in the region so we picked several cities are from Orange County in LA County to take a look at the data that skag had and and check over the land use codes make sure things were correct in if not make changes to those codes and add comments and on so this this is a new project because it forced us to on the fly implements a new features like a complete user permission system are so now we have user permissions that limit what region a certain clients see so if you log in as a city of Irvine your omega see that the Irvine City parcels even know it's just 1 server serving up everything and we also have the ability to limit what is editable and and who has administrative
access on the other the other anything about this project is because it was designed to have low level people at a certain jurisdiction making edits and managers in that jurisdiction or the regional entity of review the parcels we implemented a data review system so that when somebody editor land use code and comments on and then the manager can go in and take a look at everything that's been edited and decide whether they want to prove that emerged into the master copy which we call the master scenario versus the draft scenario and so our focus is really been to implement features based on what our current clients need in those features of course because it's open source everything is fully available to the other clients we also implemented any data version really primitive data versioning system for this release which allows it whenever any features edited out a revision is created and you can go back and take a look at here revision history so in some ways we're trying to did a little bit toward a guy get style repository system for the future data and where we can support we can show versions the data and allow emerging from addressing area to a master scenario and this kind of thing is really important for government agencies and need a lot of they have a lot of auditing in wanna keep track of what's happening with a large number of jurisdictions I'm very similar slides I'm sorry this is the sum next slide here is is actually sketching future is this is sort of the 2nd part of those the 3 tiers I showed you the 1st so 1st we had that analysis of what was on the ground and this is actually a project for the San Diego region the San Diego Regional Planning Agency they already had a number of 20 50 year 2050 future scenarios on the books outside of urban footprint so you can see in the top left are about 6 different scenarios that we brought in the system and showing on the map is the 1 of those future scenarios along so you can see the parcels a colored along with the transit networks there in here's a 1st you at some of the deceased 3 charts we create in these d 3 charts great because as the users update their parcels as a paint them with new land use is we constantly run analysis on the back end and up to date the charge so each time the you paint 1 or more parcels you'll see these charts updated and you can see well now I now I have a different delta between my base year in my future year in terms of employment and we also have charts allow you to compare 1 or more scenarios side by side so you can see which scenario is performing better or worse in a certain category and and then finally so you know managing each 1 of these scenarios can typically contains a unique set of of layer features a lot of data to manage some of the data shares some of the data that doesn't change can be shared with the goal of this is to allow clients to rapidly experiment with new scenario so take 1 scenario clone it a couple times make some changes and see how it performs so were constantly trying to make the system faster and more distributed on the back and um clients have the ability to choose land use codes when they're painting their future parcels and we really this is something that the cult of associates really specialize in a hierarchy of of land use and building types what we do is we actually take sample buildings that exist in the real world we model them in the system you can see the editor in back there for certain building and then we combine similar type buildings and what's called a building type and that is what a CLI will typically use to paint the future scenarios but we also have when clients a painting bigger isn't parcels we have something all place type which allows them to combine building information with other urban forms such as streets and parks into what's called a place type a combination of different assets on the ground and we can on the front on the front of the image here you can see a visualization of 1 of those placed types so we have some the aggregate attribute information is as well as 73 charts based on the information so that's that was kind of face to this area of Goldman and finally we have to test the impacts using this but we using the various analysis so again you see public health this convex excetera these are analysis modules that are developed in-house account outside and they're all peer reviewed by the academic and scientific community and continually upgraded as new information becomes available since is an open-source project a goal is to make these as transparent possible to provide feedback when these analysis modules run so that users of the system and the public can understand how the numbers are being generated and have a reasonable amount of confidence in the results here's an example of 1 of
the analysis modules this is the vehicle miles traveled module running on this is that this a big 1 it takes a long time we do run distribute processes on the back in the speed up so when you developing scenarios you can run this analysis at any time and get the aggregate results here so this is on showing some total the energy for the region but in aggregate form and then we also have the ability to of course show the results on the map as In this case some green to red going from green is least Fanty near the city centers in red is the most the empty away from the city centers and we can of course also represented with specific custom the anti charts up on top there so With these analysis modules are pretty exciting because they can be updated extended and we're always looking to add new ones to make the system more powerful and useful to our clients were also working on API is to better expose the modules to the front end and to allow contribution in collaboration in finance can quickly show some the results of the vision
California project this is actually from the spreadsheet based model the rapid-fire model just to give you an idea of how persuasive some of these results can be to decision makers so here's this is for California in 2050 showing the amount of land that could be saved by adopting a smart growth senior policy instead of a business as usual policy enough enough land saved 2 match Delaware and Rhode Island combined and similarly on here's
1 from VMT showing just a tremendous number of miles traveled reduced by adopting the smart growth policy here's 1 here's a this is a
vision or this is an urban footprint result from vision California again showing another VMT map showing how in the LA region how much of the MT how much we induce increase in the outlying areas versus In near the city centers here's a couple more 1
showing how much water can be saved by 2050 50 times headachy people on similarly
building energy enough power for all homes in California for years and the
energy savings household energy the household savings for energy and water and auto fuel on ownership savings by concentrating land use and the
greenhouse gas emissions significant savings by building more compact that building buildings cluster transit and reducing passenger vehicle miles and then there's a lot more information on these results if anybody's interested
then real quick couple next as for urban footprint where really working on
scaling this up for multiple users as we did for the LA region providing customer support is a big old hours when you have a lot of different municipal area admissible workers like planners and other people using the software you need to have basically 24 hour support and also constantly user interface enhancements so if some people give us suggestions all the time and we're always trying to make the product better and then some other you always working improve the analytic modules some were working on social equity indicators for instance climate adaption and resilience and conservation ecosystem services and we have a few other ones that are in the workers as well the and in the last last thing is were really working on bringing this more the local planning process so when community reviews of plans we can get the community engaged by showing the software to them and allowing them to see how their decisions decision-makers decisions can impact the quality of life and were also hoping to help out with the general planning process for for cities and regions as well as assessing health impacts and helping with climate action planning so there's a lot going on here that's a super quick overview let me know if you have specific questions you care about
what we do in terms of planning or in terms of software and few from the uh them the the we can assess all this working yeah it says that at this stage of the land use is associated to go on and possible whose our what is the land part of this is this is you are dealing with feature in areas that could be a huge foster which is now a cultural and view the light to a thing that you upon i would like just to split the updating different was that I you IUD do we'll with we don't support editing the partials right now in the software that will probably SPE support the future there is there are but I think some ways to do it on the back and so even if if they can split up we can bring it into the system so that it's different than the base year them currently with older adults is just the not when we knew we were talking about painting means did theories as well the land which trees associ really given land use from all the possible in within the bounding box so without the selected right it's a good old you know the importance of whole parcels although the way the analysis works if you were to take it in agricultural partial and turn in the mixed use development on the system smart enough to know that that's not gonna be a single parcel it's can analyze it on the assumption that would be broken up into many partials so a draw 1 more technical this question to the course of the disorder is what the user of do you deal with the people are applying different design difference in areas of the same data set we typically clone of the we the feature sets that that are going to be edited on that's where really the data review and merging process through the get like versioning becomes really important but on each scenario we we cloned the minimum that we don't want clone anything more than we have to but obviously if the editing we have to make a new copy that we talk about finally viewing find the the including geometry old just laying we yeah we call on the geometry to and I the that it is yeah so you all these things can be optimised to be nice in the future the the goal would be to have the geometry normalized in just reference set separately we do a little bit of that and it's it's going to keep getting better as time goes on the this this yes the so it is is ah as an open-source project is something that we did some really need the 3 was a client or is it something we just that were sorry could downloaded and implement the city at this at this point you have to go through us our goal is to make it more more friendly I mean it's a complicated process in and it's probably Kanade usually need some amount of help but the goal is as an open-source process the MIT prob program to make it more and more accessible so that there is more plug and play to it that we we start publishing the data standards so you know how to set it up and get the data in your system but it it does run on it runs on Amazon cloud that's that's way we typically run and and it's becoming it's going apply words multi but it's very distributed and so typically requires some amount of assistance to get set up and running in the in OK well I think my time is up so thank you very much for the bearer
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Metadaten

Formale Metadaten

Titel UrbanFootprint: Next-Gen Scenario Planning Tool
Serientitel FOSS4G 2014 Portland
Autor Likuski, Andy
Lizenz CC-Namensnennung 3.0 Deutschland:
Sie dürfen das Werk bzw. den Inhalt zu jedem legalen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen.
DOI 10.5446/32092
Herausgeber FOSS4G, Open Source Geospatial Foundation (OSGeo)
Erscheinungsjahr 2014
Sprache Englisch
Produktionsjahr 2014
Produktionsort Portland, Oregon, United States of America

Inhaltliche Metadaten

Fachgebiet Informatik
Abstract UrbanFootprint is a new open source scenario planning tool that seeks to revolutionize the practice of planning, with the potential to allow for a closer integration with research, public involvement, and education. Within version 1.1 alpha now complete and the next version currently under development, UrbanFootprint is a new state-of-the-art model that uses open source geographic information system (GIS) technology to create and evaluate physical land use/transportation investment scenarios. It is designed to be deployed by government agencies, private entities and NGOs. The model translates disparate data describing the existing environment and future urban development plans into a common data language, and defines future scenarios through the application of a new common set of ÔPlace Types'. The model's suite of Place Types represents a complete range of development types and patterns, from higher density mixed-use centers, to separated-use residential and commercial areas, to institutional and industrial areas. The physical and demographic characteristics associated with the Place Types are used to calculate the impacts of each scenario. UrbanFootprint represents the new standard for scenario modeling tools intended for use by urban and regional planners at the local, county, regional, state or national level. Running on a backbone of PostGIS, PostgreSQL and Ubuntu Linux 64-bit, it takes full advantage of today's hardware processing capabilities to model the impacts of future urban growth scenarios on the base (existing) environment in future years to generate outcomes for a full list of metrics, including: Travel behavior (vehicle miles traveled, transit trips, walking trips, fuel consumed, fuel cost, criteria pollutant emissions, transportation electricity consumed and impacts); Energy & Water consumption (for transportation & buildings); Land Consumption by type; Infrastructure Cost (capital and operations & maintenance); City revenue from residential development; Public Health Impacts (Obesity, Asthma, Rhinitis, Pedestrian-Vehicle Collisions, Respiratory & Cardiovascular Health Incidences); and Greenhouse Gas (GHG) Emissions.
Schlagwörter UrbanFootprint
planning
urban
regional
GIS
transportation
land use
place types
mixed use
mixed-use
demographics
scenario
city
state
PostGIS
PostgreSQL
Ubuntu
Linux
travel
VMT
transit
walk
pedestrian
bicycle
fuel
cost
criteria pollutant
electricity
consumption
criteria
impacts
energy
water
buildings
land
infrastructure
capital
operations
maintenance
O&M
revenue
fiscal
residential
commercial
development
public
health
obesity
asthma
rhinitis
vehicle
collisions
respiratory
cardiovascular
incidences
GHG
greenhouse
gas

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