The digital filing is created from urban planning announcement data provided by the urban development bureau. The fields include number, administrative district, use zone, zone abbreviation, urban planning name, establishment date, area, building coverage ratio, floor area ratio, maximum volume ratio, urban planning area, detailed planning area, remarks, drawing revision date, publication document number, and project name.

The global Urban Planning Software market is experiencing robust growth, with a market size of $8.87 billion in 2025 and a projected Compound Annual Growth Rate (CAGR) of 7.81% from 2025 to 2033. This expansion is driven by several key factors. Increasing urbanization globally necessitates efficient and sustainable urban planning, fueling demand for sophisticated software solutions. Government initiatives promoting smart city development and infrastructure modernization are further boosting market adoption. The integration of advanced technologies like Artificial Intelligence (AI), Machine Learning (ML), and Geographic Information Systems (GIS) within urban planning software enhances its capabilities, leading to improved decision-making and resource allocation. Furthermore, the growing adoption of cloud-based solutions offers scalability and accessibility, contributing to market growth. While the market faces challenges such as high initial investment costs and the need for skilled professionals to operate these complex systems, the long-term benefits of improved urban planning and resource management outweigh these limitations. The market is segmented by deployment (cloud-based and web-based), end-user (government, real estate, and infrastructure companies), and geography, with North America currently holding a significant market share due to early adoption and technological advancements. However, regions like APAC are witnessing rapid growth, driven by substantial infrastructure development projects and increasing government investments. The competitive landscape is characterized by a mix of established players and innovative startups, fostering innovation and competition. The continued growth of the Urban Planning Software market is expected to be fueled by several factors. The rising adoption of Building Information Modeling (BIM) for improved collaboration and design efficiency within urban projects will be a major driver. Furthermore, the growing need for data-driven insights for better urban planning and sustainable development strategies will further bolster the market. Increased focus on environmental sustainability and climate change mitigation will also drive demand for software capable of integrating environmental impact assessments into urban planning. The market's expansion will also be influenced by the increasing adoption of mobile-based solutions, providing greater accessibility and flexibility for urban planners. Competition among vendors will intensify, pushing innovation and driving the development of more sophisticated and user-friendly software solutions, ensuring continuous growth in the coming years. Specific regional growth patterns are expected to be influenced by factors such as economic conditions, government policies, and technological maturity levels in different areas.

Urban Planning and Design Software Market Outlook

As of 2023, the global urban planning and design software market size is estimated at approximately USD 6.5 billion and is projected to grow at a compound annual growth rate (CAGR) of 9.8% from 2024 to 2032, reaching a forecasted size of USD 14.1 billion by 2032. This impressive growth is driven by the increasing demand for smart city initiatives and sustainable urban development, which are crucial in addressing the rapid urbanization challenges worldwide. The integration of advanced technologies such as artificial intelligence (AI), machine learning (ML), and geographic information systems (GIS) into urban planning processes is significantly enhancing the efficiency and effectiveness of designing urban spaces, further propelling market growth.

The primary growth factor for the urban planning and design software market is the global trend of urbanization, with more than 68% of the world’s population expected to live in urban areas by 2050. This surge in urban populations demands efficient infrastructure planning and development to ensure sustainable living conditions. Urban planners and local governments are increasingly relying on advanced software solutions to analyze and manage data, optimize resource allocation, and design urban spaces that can accommodate this significant influx of residents. Furthermore, these software solutions are instrumental in creating smart cities that leverage technology to enhance urban living, thereby driving their adoption across the globe.

Another critical driver for the market is the rising importance of sustainable development and environmental conservation. With climate change and environmental degradation posing significant threats, urban planning software is essential in designing eco-friendly and sustainable urban environments. These tools help in reducing carbon footprints by optimizing energy use, integrating green spaces, and planning for sustainable transportation systems. Additionally, governments and organizations are increasingly investing in urban development projects that prioritize sustainability, thereby fueling the demand for software solutions that can facilitate such initiatives.

The increasing adoption of digital solutions and cloud technologies in the construction industry also significantly contributes to the market's growth. With the construction and real estate sectors rapidly digitalizing their operations, urban planning software acts as a critical enabler of digital transformation. These solutions provide comprehensive tools for architects, engineers, and planners to collaborate effectively and execute projects with precision. Moreover, the ability to simulate and model various urban scenarios before implementation reduces risks and enhances decision-making capabilities, which is highly valued in the construction industry.

Regionally, North America holds a significant share of the urban planning and design software market due to its advanced technological infrastructure and high investment in urban development projects. Europe follows closely, driven by the EU's stringent regulations on sustainable city planning. Asia Pacific is anticipated to register the highest growth rate, propelled by rapid urbanization and the increasing adoption of smart city projects in countries like China and India. Middle East & Africa and Latin America are also witnessing growing interest in urban planning solutions as these regions strive to modernize their infrastructure and accommodate growing urban populations.

Component Analysis

The urban planning and design software market is broadly segmented into software and services components. The software segment dominates the market, driven by the increasing need for advanced tools that facilitate comprehensive urban planning processes. Software solutions in this market range from computer-aided design (CAD) and building information modeling (BIM) to GIS and simulation tools. These applications enable urban planners to visualize, simulate, and optimize urban spaces effectively. The demand for cloud-based solutions is also rising within this segment, as they offer scalability, real-time collaboration, and cost-effectiveness, which are crucial for large-scale urban planning projects.

Within the software segment, GIS software plays a pivotal role in urban planning by providing spatial data analysis and visualization capabilities. This software allows planners to assess environmental impacts, infrastructure needs, and demographic trends, aiding in informed decision-making. As cities continue to expand and become more c

The National Urban Change Indicator (NUCI) is a change indicator dataset covering the lower 48 United States that uses Maxar’s PCM®, imagery-derived change detection, to map persistent changes to the landscape resulting from urban development. The input data for the PCM process are a multi-temporal stack of precision, co-registered Landsat multispectral scenes. This NUCI 2016 layer provides a history of change areas on an annual basis from 1987 through 2016Co-Registered Geospatial DataIn addition to capturing the PCM-determined date of change, the NUCI 2016 dataset is attributed with data elements extracted from the following co-registered geospatial data sets:2011 National Land Cover Data (NLCD 2011) Land Cover: Each change polygon is attributed with NLCD 2011 land cover name and class number of the area covered by the polygon. If more than one land cover category is present, attributes are also provided for the secondary (by percentage pixel count) and tertiary classes. The percentage of polygon area for each class is also captured and provided.Urban Gravity: Each change polygon is attributed with an “Urban Gravity” value. The Urban Gravity is calculated by treating the Impervious Surface (percent impervious by pixel) data of the NLCD 2011 dataset as units of mass and then calculating a “gravitational pull” as the inverse square distance measure at the center of the change polygon. The higher the Urban Gravity value, the closer the polygon center is to existing concentrations of NLCD 2011 mapped impervious surface areas.Distance to Water: Distance, in meters, to the nearest water body as defined by the NLCD land cover dataset. Values greater than 2,000 meters are shown as “999999”.Shuttle Radar Topography Mission (SRTM)Height Variance: Each change polygon is attributed with a measure of the average elevation variance, in meters, across the polygon. The measure is calculated from the 3 arc-second SRTM digital elevation data using a standard variance filter over a 7x7 kernel.Additional NotesThis tile layer is intended for visualization purposes. The NUCI feature layer can be used as input to spatial analysis tools and applications.A NUCI 2016 change is defined as one which meets the “3-observation change (3oc)” criteria where the detected state of change has persisted for three independent date observations.This version of NUCI 2016 was filtered to focus on changes related to human activity in order to mute spurious changes and false positives.

According to the announcement of the Urban Development Bureau, the content of the urban plan includes fields such as number, administrative district, land use zone, zone abbreviation, urban plan name, establishment date, area, building coverage ratio, floor area ratio, maximum floor area, urban planning area, detailed planning area, remarks, drawing date, publication number, and plan name.

This COVADIS data standard concerns local urban planning documents (PLUs) and land use plans (POS that are equivalent to PLU). This data standard provides a technical framework describing in detail how to dematerialise these urban planning documents into a geographical database that is exploitable by a GIS and interoperable tool. This COVADIS data standard was developed on the basis of the specifications for the dematerialisation of urban planning documents updated in 2012 by the CNIG, itself based on the consolidated version of the urban planning code dated 16 March 2012. The dematerialisation of the graphic documents of a PLU, POS generates a spatial data set composed of several catalogs of objects: The ZONE_URBA class containing the urban areas corresponding to the PLU zoning plan (R.123-5 to 8): urban areas (U), urban areas (AU), agricultural areas (A) and natural and forest areas (N). A settlement is attached to each zone. The regulation may lay down different rules, depending on whether the purpose of the constructions will concern housing, hotel accommodation, offices, commerce, crafts, industry, farming or forestry or the function of warehouse. The PRESCRIPTION class containing all surface, linear and point requirements for PLU or POS (R123-11). They are superimposed on an area of the urban planning document and generally exert an additional constraint on the settlement of the area. A regulation is attached to each prescription.

GeoTiffs that depict attraction values that are derived from our research (not all data are available for public download from its original source). "attr_emp.tif" is employment attraction values; "attr_pop.tif" is population attraction values; "attr_rev.tif" is POI(review) attraction values; "attr_trans.tif" is transportation attraction values. projection_file.prj is the projection for those data.

Geospatial Solutions Market size was valued at USD 282.75 Billion in 2024 and is projected to reach USD 650.14 Billion by 2031, growing at a CAGR of 12.10% during the forecast period 2024-2031.

Geospatial Solutions Market: Definition/ Overview

Geospatial solutions are applications and technologies that use spatial data to address geography, location, and Earth’s surface problems. They use tools like GIS, remote sensing, GPS, satellite imagery analysis, and spatial modelling. These solutions enable informed decision-making, resource allocation optimization, asset management, environmental monitoring, infrastructure planning, and addressing challenges in sectors like urban planning, agriculture, transportation, disaster management, and natural resource management. They empower users to harness spatial information for better understanding and decision-making in various contexts.

Geospatial solutions are technologies and methodologies used to analyze and visualize spatial data, ranging from urban planning to agriculture. They use GIS, remote sensing, and GNSS to gather, process, and interpret data. These solutions help users make informed decisions, solve complex problems, optimize resource allocation, and enhance situational awareness. They are crucial in addressing challenges and unlocking opportunities in today’s interconnected world, such as mapping land use patterns, monitoring ecosystem changes, and real-time asset tracking.

Market Analysis for Geographic Information Systems (GIS) The global Geographic Information Systems (GIS) market is projected to reach a value of USD 2890.3 million by 2033, expanding at a CAGR of 5.3% during the forecast period (2025-2033). This growth is driven by increasing adoption of GIS in various industries, such as utilities, transportation, government, and defense. Additionally, the rising demand for real-time data visualization, spatial analysis, and decision-making is fueling the market expansion. The GIS market is segmented based on type (hardware, software, service) and application (public, private). Public sector applications, such as urban planning, land management, and emergency response, are expected to witness significant growth. Private sector applications, including asset management, supply chain optimization, and environmental conservation, are also gaining traction. Key players in the market include Pasco, Ubisense Group, Beijing SuperMap Software, Hexagon, and Schneider Electric. The market is highly competitive, with established players and emerging startups vying for market share. North America and Europe are the largest markets for GIS, with Asia Pacific expected to exhibit the highest growth potential in the coming years.

The Geographic Information System (GIS) market is experiencing robust growth, projected to reach $5.15 billion in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 20.55% from 2025 to 2033. This expansion is fueled by several key drivers. Increasing urbanization and the need for efficient urban planning are creating significant demand for GIS solutions. Furthermore, advancements in technology, particularly in cloud computing and artificial intelligence (AI), are enhancing GIS capabilities, leading to wider adoption across various sectors. The integration of GIS with other technologies like IoT (Internet of Things) and big data analytics is enabling more sophisticated spatial analysis and decision-making. Industries like transportation, utilities, and agriculture are leveraging GIS for improved asset management, infrastructure planning, and precision farming. The market is segmented by component (software, data, services) and deployment (on-premise, cloud), with the cloud-based deployment model experiencing faster growth due to its scalability and cost-effectiveness. The competitive landscape is characterized by a mix of established players like Esri, Autodesk, and Trimble, and emerging technology providers, creating a dynamic market with significant innovation. However, factors like high initial investment costs and the need for skilled professionals to implement and manage GIS systems pose challenges to market growth. Despite these restraints, the long-term outlook for the GIS market remains positive. The increasing availability of geospatial data, coupled with declining hardware costs and improvements in user interfaces, is making GIS technology more accessible to a wider range of users. The integration of GIS into mobile applications and the rise of location-based services further broaden the market's potential. Government initiatives promoting smart cities and digital infrastructure development are also contributing to market growth. The North American region, particularly the United States, currently holds a significant market share due to early adoption and a robust technology ecosystem. However, other regions, especially in Asia-Pacific and Europe, are experiencing rapid growth, driven by increasing infrastructure investments and the adoption of advanced technologies. Future growth will be influenced by continued technological innovation, the availability of skilled workforce, and government regulations related to geospatial data management.

Weekly snapshot of Cleveland City Planning Commission datasets that are featured on the City Planning Zoning Viewer. For the official, most current record of zoning info, use the CPC Zoning Viewer.This file is an open-source geospatial (GIS) format called GeoPackage, which can contain multiple layers. It is similar to Esri's file geodatabase format. Free and open-source GIS software like QGIS, or software like ArcGIS, can read the information to view the tables and map the information.It includes the following mapping layers officially maintained by Cleveland City Planning Commission:Planner Assignment AreasPlanned Unit Development OverlayResidential FacilitiesResidential Facilities 1000 ft. BufferPolice DistrictsLandmarks / Historic LayersLocal Landmark PointsLocal Landmark ParcelsLocal Landmark DistrictsNational Historic DistrictsCentral Business DistrictDesign Review RegionsDesign Review DistrictsOverlay Frontage LinesForm & PRO Overlay DistrictsLive-Work Overlay DistrictsSpecific SetbacksStreet CenterlinesZoningUpdate FrequencyWeekly on Mondays at 4:30 AMContactCity Planning Commission, Zoning & Technology

This dataset is about books and is filtered where the book is GIS in Italian urban planning, featuring 5 columns: author, BNB id, book, book publisher, and publication date. The preview is ordered by publication date (descending).

The rapid population growth in British Columbia has led to the necessity of innovative housing solutions. Local municipalities in BC, such as Bowen Island, are exploring the implementation of Density Transfer Modelling (DTM) as a planning tool to address these challenges. The study examines Density Transfer Modelling by Geographic Information System (GIS) application on Bowen Island, managed under the Islands Trust Act, to balance development with ecological preservation. This involves identifying "donor" sites (areas of high ecological value with existing development) to transfer development rights from, and "receiver" sites (areas suitable for increased urban density) using the Normalized Difference Built-up Index and residential density classifications. Two main Comprehensive Development Areas (CDAs) on Bowen Island, Arbutus Ridge and Snug Cove are highlighted. The DTM calculates that this area supports the development of up to 30 additional detached homes in Arbutus Ridge Development Area. The Snug Cove Comprehensive Development Area (Snug Cove CDA) has been identified as a key area for increased residential development with a focus on increasing affordability and creating a pedestrian-friendly environment. According to DTM calculations Snug Cove Residential Area supports the development of 2186 dwelling units. The goal of the Snug Cove Development Area is to build a variety of housing types, including duplexes, triplexes, and multi-unit buildings, clustered near essential services and transportation hub(ferry). Both CDAs exemplify how density transfer modellings can be effectively utilized within designated development areas to support sustainable urban planning goals.

The global urban planning software market was valued at USD 1.69 billion in 2025 and is projected to reach USD 3.29 billion by 2033, exhibiting a CAGR of 8.04% during the forecast period. Rising urbanization and increasing population density have led to a growing demand for efficient urban planning to manage land use, infrastructure, and transportation. Additionally, the integration of Geographic Information Systems (GIS) and data analytics into urban planning software is enhancing decision-making capabilities and streamlining planning processes. Key market drivers include increasing government investments in urban infrastructure, rising adoption of cloud-based solutions due to their flexibility and cost-effectiveness, and the growing need for integrated planning systems that can address multiple aspects of urban development. However, factors such as limited awareness of the benefits of urban planning software in emerging markets and data security concerns may restrain market growth. Regional analysis indicates that North America and Europe hold significant market shares due to the presence of established urban planning practices and well-developed infrastructure. Asia Pacific is expected to witness substantial growth potential owing to rapid urbanization and increasing investments in smart city initiatives. The urban planning software market is projected to reach USD 2.29 billion by 2028 from USD 1.69 billion in 2023, at a CAGR of 8.04% during the forecast period. The market is driven by the increasing demand for efficient and sustainable urban planning solutions to address the challenges of urbanization and population growth. Recent developments include: , The Urban Planning Software Market is projected to reach USD 2.29 billion by 2028 from USD 1.69 billion in 2023, at a CAGR of 8.04% during the forecast period. The market is driven by the increasing demand for efficient and sustainable urban planning solutions to address the challenges of urbanization and population growth.Key developments in the market include: In June 2023, Bentley Systems acquired CityEngine, a leading provider of 3D urban modeling software. This acquisition strengthened Bentley's position in the urban planning software market and expanded its portfolio of solutions for city planning and design. In March 2023, Esri, a leading provider of geographic information systems (GIS) software, launched ArcGIS Urban, a comprehensive suite of tools for urban planning and management. This launch enhances Esri's offerings for the urban planning market and provides a comprehensive solution for city planners and urban designers.These developments indicate the growing importance of urban planning software in addressing the challenges of urbanization and creating sustainable and livable cities., Urban Planning Software Market Segmentation Insights. Key drivers for this market are: Smart city initiatives Cloud-based solutions AI and machine learning integration Geospatial data analytics Collaborative planning tools. Potential restraints include: Increasing urbanization Government initiatives Technological advancements Rising demand for sustainable urban planning Growing adoption of cloud-based solutions.

Unlock precise, high-quality GIS data covering 164M+ verified locations across 220+ countries. With 50+ enriched attributes including coordinates, building structures, and spatial geometry our dataset provides the granularity and accuracy needed for in-depth spatial analysis. Powered by AI-driven enrichment and deduplication, and backed by 30+ years of expertise, our GIS solutions support industries ranging from mapping and navigation to urban planning and market analysis, helping businesses and organizations make smarter, data-driven decisions.

Key use cases of GIS Data helping our customers :

1. Optimize Mapping & Spatial Analysis : Use GIS data to analyse landscapes, urban infrastructure, and competitor locations, ensuring data-driven planning and decision-making.
2. Enhance Navigation & Location-Based Services : Improve real-time route planning, asset tracking, and EV charging station discovery for seamless location-based experiences.
3. Identify Strategic Sites for Business Expansion : Leverage GIS intelligence to select optimal retail sites, franchise locations, and warehouses with precision.
4. Improve Logistics & Address Accuracy : Streamline delivery networks, validate addresses, and optimize courier routes to boost efficiency and customer satisfaction.
5. Support Environmental & Urban Development Initiatives : Utilize GIS insights for disaster preparedness, sustainable city planning, and land-use management.

Unlock precise, high-quality GIS data covering 46M+ verified locations across North America. With 50+ enriched attributes including coordinates, building structures, and spatial geometry our dataset provides the granularity and accuracy needed for in-depth spatial analysis. Powered by AI-driven enrichment and deduplication, and backed by 30+ years of expertise, our GIS solutions support industries ranging from mapping and navigation to urban planning and market analysis, helping businesses and organizations make smarter, data-driven decisions.

Key use cases of GIS Data helping our customers :

1. Optimize Mapping & Spatial Analysis : Use GIS data to analyse landscapes, urban infrastructure, and competitor locations, ensuring data-driven planning and decision-making.
2. Enhance Navigation & Location-Based Services : Improve real-time route planning, asset tracking, and EV charging station discovery for seamless location-based experiences.
3. Identify Strategic Sites for Business Expansion : Leverage GIS intelligence to select optimal retail sites, franchise locations, and warehouses with precision.
4. Improve Logistics & Address Accuracy : Streamline delivery networks, validate addresses, and optimize courier routes to boost efficiency and customer satisfaction.
5. Support Environmental & Urban Development Initiatives : Utilize GIS insights for disaster preparedness, sustainable city planning, and land-use management.

Land Management Software Market size was valued at USD 1.69 Billion in 2024 and is projected to reach USD 2.62 Billion by 2031, growing at a CAGR of 5.65% from 2024 to 2031.

The growth of land management software is primarily driven by the increasing demand for efficient land use, advancements in geospatial technology, regulatory compliance, and the need for data-driven decision-making. As global populations grow and urbanization accelerates, there is a growing need for efficient land resource management. Land management software offers tools to optimize land use, enhance productivity in agriculture, forestry, and urban planning, and ensure sustainable development practices.

Advancements in geospatial technology, such as Geographic Information Systems (GIS), remote sensing, and satellite imagery, have significantly enhanced the capabilities of land management software, enabling more accurate mapping, monitoring, and analysis of land resources. Regulatory compliance and environmental concerns also drive the adoption of land management software among government agencies, landowners, and businesses.

Data-driven decision-making is another driving factor, as land management software provides powerful analytical tools for processing large volumes of spatial data, generating insights, and supporting data-driven decision-making processes. The growing awareness of climate change risks and the need for resilient land management practices drives the adoption of software solutions that enable climate-smart land management.

Precision agriculture practices are increasingly emphasized in the agricultural sector, with land management software playing a critical role in supporting these practices. The emergence of integrated land management platforms that combine GIS, asset management, and workflow automation capabilities is also driving the adoption of comprehensive software solutions.

In conclusion, the growth of land management software is driven by the need for efficient land use, advancements in technology, regulatory requirements, and the recognition of the importance of sustainable land management practices in addressing global challenges such as food security, environmental degradation, and climate change.

The geospatial services market is experiencing robust growth, driven by increasing demand for location-based intelligence across diverse sectors. Our analysis projects a market size of $150 billion in 2025, exhibiting a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the proliferation of smart devices and the Internet of Things (IoT) generates massive amounts of location data, requiring sophisticated geospatial analysis. Secondly, governments and businesses increasingly rely on geospatial data for informed decision-making in areas like urban planning, precision agriculture, environmental monitoring, and disaster response. Furthermore, advancements in technologies such as satellite imagery, LiDAR, and artificial intelligence are enhancing the accuracy, speed, and analytical capabilities of geospatial services. This translates into more efficient operations, cost savings, and the ability to address complex challenges with greater precision. The market segmentation reveals strong growth across all application areas. Agriculture benefits significantly from precision farming techniques enabled by geospatial data, optimizing resource utilization and yield. Research institutions and governmental bodies utilize geospatial services for extensive data analysis, contributing substantially to environmental studies and infrastructure development. The geographic distribution highlights significant contributions from North America and Europe, driven by robust technological adoption and substantial investments in the sector. However, rapid growth is also anticipated in the Asia-Pacific region, fueled by significant infrastructure development and increasing adoption of digital technologies in developing economies. While challenges such as data security concerns and the high cost of specialized equipment and software exist, the overall market outlook remains exceptionally positive, indicating strong potential for continued expansion and innovation in the coming years.

This dataset is about book subjects and is filtered where the books is GIS in Italian urban planning, featuring 4 columns: authors, book subject, books, and publication dates. The preview is ordered by number of books (descending).

The GIS-based Time model of Gothenburg aims to map the process of urban development in Gothenburg since 1960 and in particular to document the changes in the spatial form of the city - streets, buildings and plots - through time. Major steps have in recent decades been taken when it comes to understanding how cities work. Essential is the change from understanding cities as locations to understanding them as flows (Batty 2013)1. In principle this means that we need to understand locations (or places) as defined by flows (or different forms of traffic), rather than locations only served by flows. This implies that we need to understand the built form and spatial structure of cities as a system, that by shaping flows creates a series of places with very specific relations to all other places in the city, which also give them very specific performative potentials. It also implies the rather fascinating notion that what happens in one place is dependent on its relation to all other places (Hillier 1996)2. Hence, to understand the individual place, we need a model of the city as a whole.

Extensive research in this direction has taken place in recent years, that has also spilled over to urban design practice, not least in Sweden, where the idea that to understand the part you need to understand the whole is starting to be established. With the GIS-based Time model for Gothenburg that we present here, we address the next challenge. Place is not only something defined by its spatial relation to all other places in its system, but also by its history, or its evolution over time. Since the built form of the city changes over time, often by cities growing but at times also by cities shrinking, the spatial relation between places changes over time. If cities tend to grow, and most often by extending their periphery, it means that most places get a more central location over time. If this is a general tendency, it does not mean that all places increase their centrality to an equal degree. Depending on the structure of the individual city’s spatial form, different places become more centrally located to different degrees as well as their relative distance to other places changes to different degrees. The even more fascinating notion then becomes apparent; places move over time! To capture, study and understand this, we need a "time model".

The GIS-based time model of Gothenburg consists of: • 12 GIS-layers of the street network, from 1960 to 2015, in 5-year intervals • 12 GIS-layers of the buildings from 1960 to 2015, in 5-year intervals - Please note that this dataset has been moved to a separate catalog post (https://doi.org/10.5878/t8s9-6y15) and unpublished due to licensing restrictions on its source dataset. • 12 GIS- layers of the plots from1960 to 2015, in 5-year intervals

In the GIS-based Time model, for every time-frame, the combination of the three fundamental components of spatial form, that is streets, plots and buildings, provides a consistent description of the built environment at that particular time. The evolution of three components can be studied individually, where one could for example analyze the changing patterns of street centrality over time by focusing on the street network; or, the densification processes by focusing on the buildings; or, the expansion of the city by way of occupying more buildable land, by focusing on plots. The combined snapshots of street centrality, density and land division can provide insightful observations about the spatial form of the city at each time-frame; for example, the patterns of spatial segregation, the distribution of urban density or the patterns of sprawl. The observation of how the interrelated layers of spatial form together evolved and transformed through time can provide a more complete image of the patterns of urban growth in the city.

The Time model was created following the principles of the model of spatial form of the city, as developed by the Spatial Morphology Group (SMoG) at Chalmers University of Technology, within the three-year research project ‘International Spatial Morphology Lab (SMoL)’.

The project is funded by Älvstranden Utveckling AB in the framework of a larger cooperation project called Fusion Point Gothenburg. The data is shared via SND to create a research infrastructure that is open to new study initiatives.

1. Batty, M. (2013), The New Science of Cities, Cambridge: MIT Press.
2. Hillier, B., (1996), Space Is the Machine. Cambridge: University of Cambridge

12 GIS-layers of plots in Gothenburg, from 1960 to 2015, in 5-year intervals. Only built upon plots (plots with buildings) are included. File format: shapefile (.shp), MapinfoTAB (.TAB). The coordinate system used is SWEREF 99TM, EPSG:3006.

See the attached Technical Documentation for the description and further details on the production of the datasets. See the attached Report for the description of the related research project.