The Zip folder contains a range of key GIS boundary files for ESRI and Map Info covering Greater London. The folder includes: - Output Area (OA) 2011, - Lower Super Output Area (LSOA) 2004 and 2011, - Middle Super Output Area (MSOA) 2004 and 2011, - London Wards (two files: City of London merged into single area and split into seperate wards). There are separate download file for 2014 & 2018 boundaries. - London Boroughs - Greater London boundary Note: The OA to MSOA boundaries have been generalised to reduce file size/loading time. On maps created using these boundaries the copyright must be stated. This is: "Contains National Statistics data © Crown copyright and database right [2015]" and "Contains Ordnance Survey data © Crown copyright and database right [2015]" For more information about boundary data sharing read these Terms and Conditions of Supply.

The GLA have produced a dataset that provides a more accurate estimate of the extent of the London’s green infrastructure - the city’s parks, gardens, trees, green spaces, rivers and wetlands, and features such as green roofs. The green cover layer was created by combining classified near-infrared aerial imagery (NDVI) with land use datasets and resulted in a green cover estimate for London of between 48-51 percent. The baseline is presented as a range to account for variations in the analysis of aerial imagery. The methodology is set out in the report below and a web map created to visualise the data. The final green cover layer is available to download in a geospatial format (shape files). **Contains OS data **© Crown copyright and database rights 2019. Contains Verisk **Analytics ** GeoInformation Group UKMap data. NOTE: The data is based on Ordnance Survey mapping and the data is published under Ordnance Survey's 'presumption to publish'.

Transport for London's (TFL) Public Transport Accessibility Levels (PTALs)

PTALS are a detailed and accurate measure of the accessibility of a point to the public transport network, taking into account walk access time and service availability. The method is essentially a way of measuring the density of the public transport network at any location within Greater London.

Each ares is graded between 0 and 6b, where a score of 0 is very poor access to public transport, and 6b is excellent access to public transport.

The current methodology was developed in 1992, by the London Borough of Hammersmith and Fulham. The model has been thoroughly reviewed and tested, and has been agreed by the London Borough-led PTAL development group as the most appropriate for use across London.

The measure therefore reflects:

• • Walking time from the point-of interest to the public transport access points;
• • The reliability of the service modes available;
• • The number of services available within the catchment; and
• • The level of service at the public transport access points - i.e. average waiting time.

It does not consider:

• • The speed or utility of accessible services;
• • Crowding, including the ability to board services; or,
• • Ease of interchange.

The PTAL methodology was developed for London where a dense integrated public transport network means that nearly all destinations can be reached within a reasonable amount of time. Research using the ATOS (Access to Opportunities and Services) methodology shows that there is a strong correlation between PTALs and the time taken to reach key services – i.e. high PTAL areas generally have good access to services and low PTAL areas have poor access to services.

Notes

6-digit references identify 100m grid squares.

The 2012 CSV file previously available on the Datastore is now only available via the TfL feeds page.

The 2014 files are available to download below. This includes the GIS contour files.

Current PTAL values can be viewed at TfL’s web site: www.webptals.org.uk

The GLA has calculated the percentage of population for each ward, LSOA, MSOA and borough within each PTAL. The files for 2014 are available below. The method used mapped the number of addresses (using Ordinance Survey AddressBase Plus, and 2011 Census London Output Areas boundaries).

TFL also publish on their website a tool that shows travel time and PTAL maps from any point within London. Click anywhere on the map or input a postcode to change the selected location.

Archaeological Priority Areas (APAs) are areas where there is significant known archaeological interest or potential for new discoveries. APAs are used to help highlight where development might affect heritage assets. Follow this link to find out more about our APAs: https://historicengland.org.uk/services-skills/our-planning-services/greater-london-archaeology-advisory-service/greater-london-archaeological-priority-areas/. Data updated as required.

This archive contains geospatial data, as well as the code used to generate the geospatial data.
The geospatial data consists of georeferenced polygons identifying areas which are covered by green roofs in London (GBR) generated from 2019 aerial imagery.
The data is described in detail in the manuscript *An Open-Source Automatic Survey of Green Roofs in London using Segmentation of Aerial Imagery*. See abstract below.

Archive contents:
`geospatial_data/green_roofs_220719.geojson` is the main result, which can be opened in any GIS program.
`segmentation_code` contains the Python code used to produce the segmentation from the aerial imagery.
`analysis_code` contains the Python code used to produce the plots and tables for the paper, as well as the OS intersection postprocessing step.

GeoJSON format:
GeoJSON is a format for encoding geospatial data, see https://geojson.org/.
GeoJSON can be read using GIS programs including ArcGIS, QGIS, OGR.

Input data availability:
Unfortunately the aerial imagery and building footprint data cannot be shared directly, as you will require the proper license. Both can be found at [Digimap](https://digimap.edina.ac.uk) provided your institution has the license.

Abstract:
Green roofs are roofs incorporating a deliberate layer of growing substrate and vegetation. They can reduce both indoor and outdoor temperatures, so are often presented as a strategy to reduce urban overheating, which is expected to increase due to climate change. In addition, they could help decrease the cooling energy demand of buildings thereby contributing to energy and emissions reductions and provide benefits to biodiversity and human well-being. To guide the design of more sustainable and climate resilient buildings and neighbourhoods, there is a need to assess the existing status of green roof coverage and explore the potential for future implementation. Therefore, accurate information on the prevalence and characteristics of existing green roofs is required to estimate any effect of green roofs on temperatures (or other phenomena), but this information is currently lacking. Using a machine-learning algorithm based on U-Net to segment aerial imagery, we surveyed the area and coverage of green roofs in London, producing a geospatial dataset. We estimate that there was 0.19 km^2 of green roof in the Central Activities Zone (CAZ) of London, (0.81 km^2) in Inner London, and (1.25 km^2) in Greater London in the year 2019. This corresponds to 1.6% of the total building footprint area in the CAZ, and 1.0% in Inner London. There is a relatively higher concentration of green roofs in the City of London (the historic financial district), covering 3.1% of the total building footprint area. The survey covers 1463 km^2 of Greater London, making this the largest open automatic survey of green roofs in any city. We improve on previous studies by including more negative examples in the training data, by experimenting with different data augmentation methods, and by requiring coincidence between vector building footprints and green roof patches. This dataset will enable future work examining the distribution and potential of green roofs in London and on urban climate modelling.

This dataset is a general representation of parcel mapping used by the City of London. The mapping is derived from assessment and ownership data but is not sanctioned by either MPAC or Teranet. The geospatial accuracy is not to be relied upon and must not be used for building permit applcaitions, engineering designs, detailed planning, development or property use. Use at own risk.

GIS datasets and CAD files representing assessment parcels, streets, contours, and topographic features. Also includes orthorectified aerial image of entire city.

Available on DVD through the Map and Data Library. DVD #453.

London View management Framework protected vistas. Zipped file containing the GIS files (Mapinfo and ESRI shape) for the viewing corridors and background assessment areas from Map 7.3 of the London Plan. See more on the GLA website.

mappen Zip indeholder en række vigtige GIS-grænsefiler for ESRI og kortoplysninger, der dækker Greater London.

Mappen indeholder:

- Outputområde (OA) 2011,

- Lavere Super Output Area (LSOA) 2004 og 2011,

- Middle Super Output Area (MSOA) 2004 og 2011,

- London Wards (to filer: City of London fusionerede i enkelt område og opdelt i separate afdelinger). Der er separat download-fil for 2014 & 2018 grænser.

- London Boroughs

Bemærk: Grænserne mellem OA og MSOA er blevet generaliseret for at reducere filstørrelsen/indlæsningstiden.

På kort, der er oprettet ved hjælp af disse grænser, skal ophavsretten angives. Det drejer sig om: "Indeholder nationale statistiske data © Crown copyright og database ret [2015]" og "Indeholder Ordnance Survey data © Crown copyright og database ret [2015]"

For mere information om grænsedatadeling læs disse Vilkår og betingelser for levering.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

The dataset titled "London ON Zoning By-law No. Z.-1" falls under the domain of Housing and is tagged with keywords such as By-laws, Housing Potential, Land Use, London, and Zoning. It is available in HTML format and covers the geospatial area of London. The dataset is open for access and is owned and published by the City of London. The contact point for any queries regarding access is zoning@london.ca. The dataset was accessed on 3rd March 2025 and has a unique identifier of by-laws/5111. The language of the dataset is English. The dataset does not contain any data about individuals, identifiable individuals, or Indigenous communities. It has a municipal geospatial resolution. The description of the dataset indicates that it contains Zoning By-laws which regulate how land and buildings are used, the location of buildings, lot coverage, building heights, and other provisions necessary for proper development. The resources available in the dataset include 'London ON Zoning By-law No. Z-1' and 'London ON Zoning By-law No. Z-1 - Interactive Map'. The metadata for the dataset was created on 19th March 2025 and was last modified on 26th March 2025.

London Overground stations. Extracted from Solar, newer stations added. Mastermap Alignment: N/A. Last updated : 16/09/16

Part of Release: Official Sub-Ward, Ward and Borough level crime counts. This is the most accurate data available for counting numbers of crimes in London according to official recorded crime types, by the month the offence occurred, and by either borough, ward or sub ward location. The page contains the LSOA level file (Pre-2015 data in the 'archive' file) Click here for corresponding ward level data: Recorded Crime Summary Data for London: Ward Level Click here for corresponding borough level data: Recorded Crime Summary Data for London: Borough Level ‘Sub-Ward data’ counts the number of crimes in each sub ward area of London (Census Lower Super Output Area or LSOA) per month according to crime type. Use this data if you need to analyse crime data at a sub ward level. Because not all crimes can be matched to a specific LSOA area, you should not use this data set to count crimes by ward or borough. For these purposes use one of the other datasets according to the level of geographic precision you need. The categories of crime counts within them may change from time to time. Below is a list of the crime types you can currently extract (*only at borough or ward level): Minor Category: Major Category Murder: ViolenceAgainstThePerson CommonAssault: ViolenceAgainstThePerson OffensiveWeapon: ViolenceAgainstThePerson Harassment: ViolenceAgainstThePerson Otherviolence: ViolenceAgainstThePerson AssaultWithInjury: ViolenceAgainstThePerson WoundingGBH: ViolenceAgainstThePerson PersonalProperty: Robbery BusinessProperty: Robbery BurglaryInADwelling: Burglary BurglaryInOtherBuildings: Burglary TheftOrTakingOfMotor: TheftAndHandling TheftFromMotor: TheftAndHandling MotorInterferenceAndTampering: TheftAndHandling TheftFromShops: TheftAndHandling TheftOrTakingOfPedalCycles: TheftAndHandling OtherTheftPerson: TheftAndHandling OtherTheft: TheftAndHandling HandlingStolenGoods: TheftAndHandling CriminalDamageToADwelling: CriminalDamage CriminalDamageToOtherBldg: CriminalDamage CriminalDamageToMotor: CriminalDamage OtherCriminalDamage: CriminalDamage DrugTrafficking: Drugs PossessionOfDrugs: Drugs OtherDrugOffences: Drugs GoingEquipped: OtherNotifiableOffences OtherNotifiable: OtherNotifiableOffences (NB. no Sexual Offences data is included at LSOA level for disclosure purposes) Each row of data in the data sets contains: *The number of incidents according to the Month Recorded, the specific crime type, and the Location *The Month Recorded *The broad crime type (Major HO category – eg Robbery) *The specific crime type (Minor HO category – eg Robbery: Personal Property) *The Location (Sub –Ward, Ward or borough depending on the data set selected)

Introduction The GIS (Geographic Information System) vectorisation project will deliver the incremental digital conversion of our legacy geospatial network records. This dataset defines the sub-areas which will be incrementally delivered, detailing corresponding current status and planned completion dates. This allows users to understand the current and future coverage of digital geospatial network records as the project progresses.

Methodological Approach Progress against a defined project plan is captured and updated throughout the day. A script is run to convert into a shapefile. This shapefile is then uploaded onto the Open Data Portal.

Quality Control Statement

This dataset is provided "as is".

Assurance Statement The Open Data Team has checked outputs to validate.

Other Download dataset information: Metadata (JSON)Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: https://ukpowernetworks.opendatasoft.com/pages/glossary/

The algorithms and machine learning based techniques used to produce the canopy map were developed using Google Earth Engine which was also leveraged to perform the processing needed to create a pan-London high resolution (25 cm per pixel) tree canopy data. Full details of the methodology are documented here. Final canopy layers have been made available to download below in a geospatial format (KML). The pan-London high resolution canopy layer has also been aggregated to: hexagon grid, Lower Super Output Area (LSOA), Ward (2014) and London Borough geographies.

Red routes, London road network managed and maintained by TfL. Last updated: please refer to the LAST_EDIT_DATE field.

Group of movement trajectories of couriers operating in London, UK.https://rd.eres.rmit.edu.au/experiment/view/2/This dataset is a collection of courier trajectories, captured principally around London over a continuous eight week period. This is a useful example of real movement trajectories, which could potentially be used for benchmarking or for the development of spatio-temporal analytics. In addition to the principle data file,which contains 9,917,703 discrete data points, sixteen different spatial and temporal summaries have been included in the related experiment to aid analysis.

The Green Infrastructure Focus Map is a new tool and evidence base to help London’s decision-makers identify where green infrastructure improvements and investments might be best targeted, and what kind of interventions might be most useful for the needs of a specific area. The Green Infrastructure Focus Map can help: identify where there is more need or less need for green infrastructure interventions describe which specific environmental or social issues have the greatest need for intervention in a particular location highlight other issues that green infrastructure can’t necessarily help with, but that are useful context for decision making (e.g. income deprivation) Please contact environment@london.gov.uk with any queries or feedback. Data and analysis from GLA GIS Team form a basis for the policy and investment decisions facing the Mayor of London and the GLA group. GLA Intelligence uses a wide range of information and data sourced from third party suppliers within its analysis and reports. GLA Intelligence cannot be held responsible for the accuracy or timeliness of this information and data. The GLA will not be liable for any losses suffered or liabilities incurred by a party as a result of that party relying in any way on the information contained in this report.

The 2021 London Output Area Classification (LOAC) has been created by the CDRC and published on 2 October 2023. Data and supporting information are on the datastore here.

This page gives access to the OLD 2011 London Output Area Classification (LOAC), an open source geospatial classification, using a combination of over 60 variables from the 2011 Census to classify every small area in London within a hierarchical structure.

The 2011 London classification used the same variables and methodology as the UK 2011 Area Classifications, but provided a finer level of classification for London.

Users can download the LOAC reports and data from this page.

An interactive map of the 2011 LOAC can be found on the CDRC mapmaker website.

The Digital Surficial Geologic-GIS Map of Weir Farm National Historical Park and Vicinity, Connecticut is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (wefa_surficial_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (wefa_surficial_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (wefa_surficial_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (wefa_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (wefa_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (wefa_surficial_geology_metadata_faq.pdf). Please read the wefa_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://res1wwwd-o-tgoogled-o-tcom.vcapture.xyz/earth/versions/. QGIS software is available for free at: https://res1wwwd-o-tqgisd-o-torg.vcapture.xyz/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://res1wwwd-o-tnpsd-o-tgov.vcapture.xyz/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://res1wwwd-o-tnpsd-o-tgov.vcapture.xyz/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (wefa_surficial_geology_metadata.txt or wefa_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://res1wwwd-o-tnpsd-o-tgov.vcapture.xyz/articles/gri-geodatabase-model.htm).