Urban heat islands are small areas where temperatures are unnaturally high - usually due to dense buildings, expansive hard surfaces, or a lack of tree cover or greenspace. People living in these communities are exposed to more dangerous conditions, especially as daytime high and nighttime low temperatures increase over time. NOAA Climate Program Office and CAPA Strategies have partnered with cities around the United States to map urban heat islands. The NOAA Visualization Lab, part of the NOAA Satellite and Information Service, has made the original heat mapping data available as feature services.

Market Size and Key Trends: The Heat Maps Software market is anticipated to grow at a CAGR of 9.3% from 2025 to 2033, reaching a valuation of 886 million value units by 2033. The increasing demand for user experience optimization, personalized experiences on websites and mobile apps, and the need for data-driven decision-making are driving the market growth. Cloud-based and web-based heat maps software are gaining traction due to their cost-effectiveness, flexibility, and accessibility advantages. Competitive Landscape and Regional Dynamics: The Heat Maps Software market is highly competitive, with a diverse range of players from global technology giants to niche software providers. Key market players include Hotjar, Smartlook, VWO, Zoho PageSense, Freshmarketer, Crazy Egg, Lucky Orange, Hitsteps Web Analytics, EyeQuant, UserZoom, Instapage, Clicktale, Acoustic Experience Analytics, Mouseflow, ContentSquare, and SessionCam. North America is expected to remain the dominant market due to the presence of major technology and digital marketing hubs, while Asia Pacific is projected to experience the fastest growth due to the expanding e-commerce and mobile internet usage in the region.

Urban heat islands are small areas where temperatures are unnaturally high - usually due to dense buildings, expansive hard surfaces, or a lack of tree cover or greenspace. People living in these communities are exposed to more dangerous conditions, especially as daytime high and nighttime low temperatures increase over time. NOAA Climate Program Office and CAPA Strategies have partnered with cities around the United States to map urban heat islands. The NOAA Visualization Lab, part of the NOAA Satellite and Information Service, has made the original heat mapping data available as feature services.

The global heat maps software market is growing rapidly, driven by the increasing demand for customer experience optimization. According to a recent study, the market size was valued at USD 825.2 million in 2025 and is expected to grow at a CAGR of 8.9% from 2025 to 2033. The growth is attributed to the rising adoption of cloud-based heat maps software, which offers scalability, flexibility, and cost-effectiveness. Enterprises and SMEs are leveraging heat maps software to gain valuable insights into user behavior patterns and optimize their websites and applications. Key trends in the market include the integration of artificial intelligence (AI) and machine learning (ML) for advanced data analysis, the emergence of mobile heat maps software, and the growing demand for real-time heatmaps. North America and Europe dominate the market, followed by Asia Pacific. Prominent players in the market include Hotjar, Smartlook, VWO, Zoho PageSense, Freshmarketer, Crazy Egg, Lucky Orange, Hitsteps Web Analytics, EyeQuant, UserZoom, Instapage, Clicktale, Acoustic Experience Analytics (formerly Tealeaf), Mouseflow, ContentSquare, SessionCam, and more.

Urban heat islands are small areas where temperatures are unnaturally high - usually due to dense buildings, expansive hard surfaces, or a lack of tree cover or greenspace. People living in these communities are exposed to more dangerous conditions, especially as daytime high and nighttime low temperatures increase over time. NOAA Climate Program Office and CAPA Strategies have partnered with cities around the United States to map urban heat islands. Using Sentinel-2 satellite thermal data along with on-the-ground sensors, air temperature and heat indexes are calculated for morning, afternoon, and evening time periods. The NOAA Visualization Lab, part of the NOAA Satellite and Information Service, has made the original heat mapping data available as dynamic image services.Dataset SummaryPhenomenon Mapped: heat indexUnits: degrees Fahrenheit Cell Size: 30 metersPixel Type: 32 bit floating pointData Coordinate Systems: WGS84 Mosaic Projection: WGS84 Extent: cities within the United StatesSource: NOAA and CAPA StrategiesPublication Date: September 20, 2021What can you do with this layer?This imagery layer supports communities' UHI spatial analysis and mapping capabilities. The symbology can be manually changed, or a processing template applied to the layer will provide a custom rendering. Each city can be queried.Related layers include Morning Heat Index and Evening Heat Index. Cities IncludedBoulder, CO Brooklyn, NY Greenwich Village, NY Columbia, SC Columbia, MO Columbus, OH Knoxville, TN Jacksonville, FL Las Vegas, NV Milwaukee, WI Nashville, TN Omaha, NE Philadelphia, PA Rockville, MD Gaithersburg, MD Takoma Park, MD San Francisco, CA Spokane, WA Abingdon, VA Albuquerque, NM Arlington, MA Woburn, MA Arlington, VA Atlanta, GA Charleston, SC Charlottesville, VA Clarksville, IN Farmville, VA Gresham, OR Harrisonburg, VA Kansas City, MO Lynchburg, VA Manhattan, NY Bronx, NY Newark, NJ Jersey City, NJ Elizabeth, NJ Petersburg, VA Raleigh, NC Durham, NC Richmond, VA Richmond, IN Salem, VA San Diego, CA Virginia Beach, VA Winchester, VA Austin, TX Burlington, VT Cincinnati, OH Detroit, MI El Paso, TX Houston, TX Jackson, MS Las Cruces, NM Miami, FL New Orleans, LA Providence, RI Roanoke, VA San Jose, CA Seattle, WA Vancouver, BC Canada Boston, MA Fort Lauderdale, FL Honolulu, HI Boise, ID Nampa, ID Los Angeles, CA Yonkers, NY Oakland, CA Berkeley, CA San Juan, PR Sacramento, CA San Bernardino, CA Victorville, CA West Palm Beach, FL Worcester, MA Washington, D.C. Baltimore, MD Portland, ORCities may apply to be a part of the Heat Watch program through the CAPA Strategies website. Attribute Table Informationcity_name: Afternoon Heat Index Observations in Floating-Point (°F)

The London Heat Map is a tool designed to help you identify areas of high heat demand, explore opportunities for new and expanding district heat networks and to draw potential heat networks and assess their financial feasibility. The new version of the London Heat Map was created for the Greater London Authority by the Centre for Sustainable Energy (CSE) in July 2019. The London Heat Map is regularly updated with new network data and other datasets. Background datasets such as building heat demand was last updated on 26/06/2023. The London Heatmap is a map-based web application you can use to find and appraise opportunities for decentralised energy (DE) projects in London. The map covers the whole of Greater London, and provides very local information to help you identify and develop DE opportunities, including data such as: Heat demand values for each building Locations of potential heat supply sites Locations of existing and proposed district heating networks A spatial heat demand density map layer The map also includes a user-friendly visual tool for heat network design. This is intended to support preliminary techno-economic appraisal of potential district heat networks. The London Heat Map is used by a wide variety of people in numerous ways: London Boroughs can use the new map to help develop their energy master plans. Property developers can use the map to help them meet the decentralised energy policies in the London Plan. Energy consultants can use the map to gather initial data to inform feasibility studies. More information is available here, and an interactive map is available here. Building-level estimated annual and peak heat demand data from the London Heat Map has been made available through the data extracts below. The data was last updated on 26/06/2023. The data contains Ordnance Survey mapping and the data is published under Ordnance Survey's 'presumption to publish'. © Crown copyright and database rights 2023. The Decentralised Energy Master planning programme (DEMaP) The Decentralised Energy Master planning programme (DEMaP), was completed in October 2010. It included a heat mapping support package for the London boroughs to enable them to carry out high resolution heat mapping for their area. To date, heat maps have been produced for 29 London boroughs with the remaining four boroughs carrying out their own data collection. All of the data collected through this process is provided below. Carbon Calculator Tool Arup have produced a Carbon Calculator Tool to assist projects in their early estimation of the carbon dioxide (CO2) savings which could be realised by a district heating scheme with different sources of heating. The calculator's estimates include the impact of a decarbonising the electrical grid over time, based on projections by the Department for Energy and Climate Change, as well as the Government's Standard Assessment Procedure (SAP). The Excel-based tool can be downloaded below. Borough Heat Maps Data and Reports (2012) In March 2012, all London boroughs did a heat mapping exercise. The data from this includes the following and can be downloaded below: Heat Load for all boroughs Heat Supplies for all boroughs Heat Network LDD 2010 database Complete GIS London Heat Map Data The heat maps contain real heat consumption data for priority buildings such as hospitals, leisure centres and local authority buildings. As part of this work, each of the boroughs developed implementation plans to help them take the DE opportunities identified to the next stages. The implementation plans include barriers and opportunities, actions to be taken by the council, key dates, personnel responsible. These can be downloaded below. Other Useful Documents Other useful documents can be downloaded from the links below: Energy Masterplanning Manual Opportunities for Decentralised Energy in London - Vision Map London Heat Network Manual London Heat Network Manual II

The Scotland Heat Map is a tool to help plan for the reduction of carbon emissions from heat in buildings. This service allows users to view layers from the map using their GIS software. The Scotland Heat Map is produced by the Scottish Government. The most recent version is the Scotland Heat Map 2022, which was released to local authorities in November 2023. More information can be found in the documentation available on the Scottish Government website: https://www.gov.scot/publications/scotland-heat-map-documents/

Urban heat islands are small areas where temperatures are unnaturally high - usually due to dense buildings, expansive hard surfaces, or a lack of tree cover or greenspace. People living in these communities are exposed to more dangerous conditions, especially as daytime high and nighttime low temperatures increase over time. NOAA Climate Program Office and CAPA Strategies have partnered with cities around the United States to map urban heat islands. Using Sentinel-2 satellite thermal data along with on-the-ground sensors, air temperature and heat indexes are calculated for morning, afternoon, and evening time periods. The NOAA Visualization Lab, part of the NOAA Satellite and Information Service, has made the original heat mapping data available as dynamic image services.Dataset SummaryPhenomenon Mapped: heat indexUnits: degrees Fahrenheit Cell Size: 30 metersPixel Type: 32 bit floating pointData Coordinate Systems: WGS84 Mosaic Projection: WGS84 Extent: cities within the United StatesSource: NOAA and CAPA StrategiesPublication Date: September 20, 2021What can you do with this layer?This imagery layer supports communities' UHI spatial analysis and mapping capabilities. The symbology can be manually changed, or a processing template applied to the layer will provide a custom rendering. Each city can be queried.Related layers include Morning Heat Index and Afternoon Heat Index. Cities IncludedBoulder, CO Brooklyn, NY Greenwich Village, NY Columbia, SC Columbia, MO Columbus, OH Knoxville, TN Jacksonville, FL Las Vegas, NV Milwaukee, WI Nashville, TN Omaha, NE Philadelphia, PA Rockville, MD Gaithersburg, MD Takoma Park, MD San Francisco, CA Spokane, WA Abingdon, VA Albuquerque, NM Arlington, MA Woburn, MA Arlington, VA Atlanta, GA Charleston, SC Charlottesville, VA Clarksville, IN Farmville, VA Gresham, OR Harrisonburg, VA Kansas City, MO Lynchburg, VA Manhattan, NY Bronx, NY Newark, NJ Jersey City, NJ Elizabeth, NJ Petersburg, VA Raleigh, NC Durham, NC Richmond, VA Richmond, IN Salem, VA San Diego, CA Virginia Beach, VA Winchester, VA Austin, TX Burlington, VT Cincinnati, OH Detroit, MI El Paso, TX Houston, TX Jackson, MS Las Cruces, NM Miami, FL New Orleans, LA Providence, RI Roanoke, VA San Jose, CA Seattle, WA Vancouver, BC Canada Boston, MA Fort Lauderdale, FL Honolulu, HI Boise, ID Nampa, ID Los Angeles, CA Yonkers, NY Oakland, CA Berkeley, CA San Juan, PR Sacramento, CA San Bernardino, CA Victorville, CA West Palm Beach, FL Worcester, MA Washington, D.C. Baltimore, MD Portland, ORCities may apply to be a part of the Heat Watch program through the CAPA Strategies website. Attribute Table Informationcity_name: Evening Heat Index Observations in Floating-Point (°F)

The Scotland Heat Map provides estimates of heat demand for all properties in Scotland. To indicate reliability, each estimate is assigned a confidence level from 1 to 5. Level 1 is least reliable and level 5 most. This is mainly determined by the presence of information that would directly impact on heat demand in the estimate's source data. For example, estimates based on data that includes building type, age and floor area would be more reliable than estimates based solely on floor area derived from mapping data. This raster dataset gives the average (mean) confidence level of properties within 1km x 1km grid squares covering all of Scotland. The Scotland Heat Map is a tool to help plan for the reduction of carbon emissions from heat in buildings. Average confidence level is an indicator of reliability of the heat demand estimates within an area and allows planners to decide whether they meet their needs. The map is produced by the Scottish Government. The most recent version is the Scotland Heat Map 2022, which was released to local authorities in November 2023. More information can be found in the documentation available on the Scottish Government website: https://www.gov.scot/publications/scotland-heat-map-documents/

Find out the most popular cycling routes and running routes across North Yorkshire and the world.

This is a useful website to show where the most popular cycling and running routes are in your area.

Why not try going for a run or a ride? Why not try cycling to work? Have a healthier hobby? or visit an attractive part of the County and take in a ride?

Urban heat islands are small areas where temperatures are unnaturally high - usually due to dense buildings, expansive hard surfaces, or a lack of tree cover or greenspace. People living in these communities are exposed to more dangerous conditions, especially as daytime high and nighttime low temperatures increase over time. NOAA Climate Program Office and CAPA Strategies have partnered with cities around the United States to map urban heat islands. Using Sentinel-2 satellite thermal data along with on-the-ground sensors, air temperature and heat indexes are calculated for morning, afternoon, and evening time periods. The NOAA Visualization Lab, part of the NOAA Satellite and Information Service, has made the original heat mapping data available as dynamic image services.Dataset SummaryPhenomenon Mapped: heat indexUnits: degrees Fahrenheit Cell Size: 30 metersPixel Type: 32 bit floating pointData Coordinate Systems: WGS84 Mosaic Projection: WGS84 Extent: cities within the United StatesSource: NOAA and CAPA StrategiesPublication Date: September 20, 2021What can you do with this layer?This imagery layer supports communities' UHI spatial analysis and mapping capabilities. The symbology can be manually changed, or a processing template applied to the layer will provide a custom rendering. Each city can be queried.Related layers include Afternoon Heat Index and Evening Heat Index. Cities IncludedBoulder, CO Brooklyn, NY Greenwich Village, NY Columbia, SC Columbia, MO Columbus, OH Knoxville, TN Jacksonville, FL Las Vegas, NV Milwaukee, WI Nashville, TN Omaha, NE Philadelphia, PA Rockville, MD Gaithersburg, MD Takoma Park, MD San Francisco, CA Spokane, WA Abingdon, VA Albuquerque, NM Arlington, MA Woburn, MA Arlington, VA Atlanta, GA Charleston, SC Charlottesville, VA Clarksville, IN Farmville, VA Gresham, OR Harrisonburg, VA Kansas City, MO Lynchburg, VA Manhattan, NY Bronx, NY Newark, NJ Jersey City, NJ Elizabeth, NJ Petersburg, VA Raleigh, NC Durham, NC Richmond, VA Richmond, IN Salem, VA San Diego, CA Virginia Beach, VA Winchester, VA Austin, TX Burlington, VT Cincinnati, OH Detroit, MI El Paso, TX Houston, TX Jackson, MS Las Cruces, NM Miami, FL New Orleans, LA Providence, RI Roanoke, VA San Jose, CA Seattle, WA Vancouver, BC Canada Boston, MA Fort Lauderdale, FL Honolulu, HI Boise, ID Nampa, ID Los Angeles, CA Yonkers, NY Oakland, CA Berkeley, CA San Juan, PR Sacramento, CA San Bernardino, CA Victorville, CA West Palm Beach, FL Worcester, MA Washington, D.C. Baltimore, MD Portland, ORCities may apply to be a part of the Heat Watch program through the CAPA Strategies website. Attribute Table Informationcity_name: Morning Heat Index Observations in Floating-Point (°F)

The Scotland Heat Map is a tool to help plan for the reduction of carbon emissions from heat in buildings. Average confidence level is an indicator of reliability of the heat demand estimates within an area and allows planners to decide whether they meet their needs. The map is produced by the Scottish Government. The most recent version is the Scotland Heat Map 2022, which was released to local authorities in November 2023. More information can be found in the documentation available on the Scottish Government website: https://www.gov.scot/publications/scotland-heat-map-documents/

Notice: this is not the latest Heat Island Severity image service. For 2023 data, visit https://tpl.maps.arcgis.com/home/item.html?id=db5bdb0f0c8c4b85b8270ec67448a0b6. This layer contains the relative heat severity for every pixel for every city in the contiguous United States. This 30-meter raster was derived from Landsat 8 imagery band 10 (ground-level thermal sensor) from the summer of 2021, patched with data from 2020 where necessary.Federal statistics over a 30-year period show extreme heat is the leading cause of weather-related deaths in the United States. Extreme heat exacerbated by urban heat islands can lead to increased respiratory difficulties, heat exhaustion, and heat stroke. These heat impacts significantly affect the most vulnerable—children, the elderly, and those with preexisting conditions.The purpose of this layer is to show where certain areas of cities are hotter than the average temperature for that same city as a whole. Severity is measured on a scale of 1 to 5, with 1 being a relatively mild heat area (slightly above the mean for the city), and 5 being a severe heat area (significantly above the mean for the city). The absolute heat above mean values are classified into these 5 classes using the Jenks Natural Breaks classification method, which seeks to reduce the variance within classes and maximize the variance between classes. Knowing where areas of high heat are located can help a city government plan for mitigation strategies.This dataset represents a snapshot in time. It will be updated yearly, but is static between updates. It does not take into account changes in heat during a single day, for example, from building shadows moving. The thermal readings detected by the Landsat 8 sensor are surface-level, whether that surface is the ground or the top of a building. Although there is strong correlation between surface temperature and air temperature, they are not the same. We believe that this is useful at the national level, and for cities that don’t have the ability to conduct their own hyper local temperature survey. Where local data is available, it may be more accurate than this dataset. Dataset SummaryThis dataset was developed using proprietary Python code developed at The Trust for Public Land, running on the Descartes Labs platform through the Descartes Labs API for Python. The Descartes Labs platform allows for extremely fast retrieval and processing of imagery, which makes it possible to produce heat island data for all cities in the United States in a relatively short amount of time.What can you do with this layer?This layer has query, identify, and export image services available. Since it is served as an image service, it is not necessary to download the data; the service itself is data that can be used directly in any Esri geoprocessing tool that accepts raster data as input.In order to click on the image service and see the raw pixel values in a map viewer, you must be signed in to ArcGIS Online, then Enable Pop-Ups and Configure Pop-Ups.Using the Urban Heat Island (UHI) Image ServicesThe data is made available as an image service. There is a processing template applied that supplies the yellow-to-red or blue-to-red color ramp, but once this processing template is removed (you can do this in ArcGIS Pro or ArcGIS Desktop, or in QGIS), the actual data values come through the service and can be used directly in a geoprocessing tool (for example, to extract an area of interest). Following are instructions for doing this in Pro.In ArcGIS Pro, in a Map view, in the Catalog window, click on Portal. In the Portal window, click on the far-right icon representing Living Atlas. Search on the acronyms “tpl” and “uhi”. The results returned will be the UHI image services. Right click on a result and select “Add to current map” from the context menu. When the image service is added to the map, right-click on it in the map view, and select Properties. In the Properties window, select Processing Templates. On the drop-down menu at the top of the window, the default Processing Template is either a yellow-to-red ramp or a blue-to-red ramp. Click the drop-down, and select “None”, then “OK”. Now you will have the actual pixel values displayed in the map, and available to any geoprocessing tool that takes a raster as input. Below is a screenshot of ArcGIS Pro with a UHI image service loaded, color ramp removed, and symbology changed back to a yellow-to-red ramp (a classified renderer can also be used): Other Sources of Heat Island InformationPlease see these websites for valuable information on heat islands and to learn about exciting new heat island research being led by scientists across the country:EPA’s Heat Island Resource CenterDr. Ladd Keith, University of ArizonaDr. Ben McMahan, University of Arizona Dr. Jeremy Hoffman, Science Museum of Virginia Dr. Hunter Jones, NOAA Daphne Lundi, Senior Policy Advisor, NYC Mayor's Office of Recovery and ResiliencyDisclaimer/FeedbackWith nearly 14,000 cities represented, checking each city's heat island raster for quality assurance would be prohibitively time-consuming, so The Trust for Public Land checked a statistically significant sample size for data quality. The sample passed all quality checks, with about 98.5% of the output cities error-free, but there could be instances where the user finds errors in the data. These errors will most likely take the form of a line of discontinuity where there is no city boundary; this type of error is caused by large temperature differences in two adjacent Landsat scenes, so the discontinuity occurs along scene boundaries (see figure below). The Trust for Public Land would appreciate feedback on these errors so that version 2 of the national UHI dataset can be improved. Contact Dale.Watt@tpl.org with feedback.

Dates of Images:Pre-Event: April 2024Post-Event: 5/18/2024, 5/19/2024, 5/20/2024Date of Next Image:UnknownSummary:The Black Marble High-Definition (BMHD) images were created by the NASA Black Marble Science team, with directed funding the NASA-Google Partnership program. The images map the impact of extreme heat in Houston, Texas on electric grids. The baseline image is from April 2024, a cloud-free, moon-free composite, and the “after" image is from May 18, 2024 - May 20, 2024. There is a layer to display where clouds are present in the "after" images. This comparison between the images is meant as a visual assessment of outage impacts from the extreme heat to aid various partners who are working to deliver emergency aids to local communities. Power outage maps like these help disaster response efforts in the short-term as well as long-term monitoring during the crucial stages of disaster recovery.From the BMHD data, zonal statistics were collated with FEMA's National Risk Index (NRI) Social Vulnerability score to identify areas where vulnerable populations were affected by power outages. Higher (red) census tract areas indicate a higher amount of power lost relative to the second date listed. For example, a red polygon in the Baseline (April) - May 18th layer indicates that specific area lost disproportionately more power and is in an area with high social vulnerability risk when comparing the normal power available (baseline) to when the disaster occurred.Suggested Use:NOTE: Black Marble HD images are downscaled from NASA’s Black Marble nighttime lights product (VNP46), and as such are a “modelled” or “best guess” estimate of how lights are distributed at a 30m resolution. These images should be used for visualization purposes, not for quantitative analysis.The image is in a yellow-red color scale. Red indicates more severe impacts. Grey polygons are acquired from cloud cover and represent areas where no data was available on a given day.Satellite/Sensor:The primary data source, NASA’s Black Marble nighttime lights product suite (VNP46), utilized to generate this product is derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP) along with high resolution base layers - Landsat derived normalized index products (NDVI and NDWI) and OpenStreetMap (OSM) derived road layerResolution:Scaled resolution of 30 metersCredits:NASA Black Marble Science teamFEMA National Risk Index (NRI) TeamPlease cite the following two references when using this data:Román MO, Stokes EC, Shrestha R, Wang Z, Schultz L, Carlo EA, Sun Q, Bell J, Molthan A, Kalb V, Ji C. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PloS one. 2019 Jun 28;14(6):e0218883.Román MO, Wang Z, Sun Q, Kalb V, Miller SD, Molthan A, Schultz L, Bell J, Stokes EC, Pandey B, Seto KC. NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment. 2018 Jun 1;210:113-43.Point of Contact:Ranjay ShresthaNASA Goddard Space Flight CenterE-mail: ranjay.m.shrestha@nasa.govAdditional Links:NASA’s Black Marble Product SuiteRomán, M.O. et al. (2019) Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14 (6).Román, M.O. et al. (2018) NASA’s Black Marble nighttime lights product suite. Remote Sensing of Environment. 210, 113–143.FEMA's National Risk Index Map: https://hazards.fema.gov/nri/data-resources#shpDownloadEsri REST Endpoint:See URL section on right side of page.WMS Endpoint:https://maps.disasters.nasa.gov/ags03/services/texas_extremeheat_202405/Relative_Power_Loss_Web_Map/MapServer/WMSServer?request=GetCapabilities&service=WMSData Download:https://maps.disasters.nasa.gov/download/gis_products/event_specific/2024/texas_extremeheat_202405/blackmarble_hd/

The Scotland Heat Map provides estimates of annual heat demand for almost 3 million properties in Scotland. Demand is given in kilowatt-hours per year (kWh/yr). Property level estimates can be combined to give values for various geographies. Both domestic and non-domestic properties are included. This raster dataset gives the total estimated heat demand of properties within 500m x 500m grid squares covering all of Scotland. Heat demand is calculated by combining data from a number of sources, ensuring that the most appropriate data available is used for each property. The data can be used by local authorities and others to identify or inform opportunities for low carbon heat projects such as district heat networks. The Scotland Heat Map is produced by the Scottish Government. The most recent version is the Scotland Heat Map 2022, which was released to local authorities in November 2023. More information can be found in the documentation available on the Scottish Government website: https://www.gov.scot/publications/scotland-heat-map-documents/

This layer presents detectable thermal activity from MODIS satellites for the last 7 days. MODIS Global Fires is a product of NASA’s Earth Observing System Data and Information System (EOSDIS), part of NASA's Earth Science Data. EOSDIS integrates remote sensing and GIS technologies to deliver global MODIS hotspot/fire locations to natural resource managers and other stakeholders around the World.Consumption Best Practices:

As a service that is subject to very high usage, ensure peak performance and accessibility of your maps and apps by avoiding the use of non-cacheable relative Date/Time field filters. To accommodate filtering events by Date/Time, we suggest using the included "Age" fields that maintain the number of days or hours since a record was created or last modified, compared to the last service update. These queries fully support the ability to cache a response, allowing common query results to be efficiently provided to users in a high demand service environment.When ingesting this service in your applications, avoid using POST requests whenever possible. These requests can compromise performance and scalability during periods of high usage because they too are not cacheable.Source: NASA FIRMS - Active Fire Data - for WorldScale/Resolution: 1kmUpdate Frequency: 1/2 Hour (every 30 minutes) using the Aggregated Live Feed MethodologyArea Covered: WorldWhat can I do with this layer?The MODIS thermal activity layer can be used to visualize and assess wildfires worldwide. However, it should be noted that this dataset contains many “false positives” (e.g., oil/natural gas wells or volcanoes) since the satellite will detect any large thermal signal.Additional InformationMODIS stands for MODerate resolution Imaging Spectroradiometer. The MODIS instrument is on board NASA’s Earth Observing System (EOS) Terra (EOS AM) and Aqua (EOS PM) satellites. The orbit of the Terra satellite goes from north to south across the equator in the morning and Aqua passes south to north over the equator in the afternoon resulting in global coverage every 1 to 2 days. The EOS satellites have a ±55 degree scanning pattern and orbit at 705 km with a 2,330 km swath width.It takes approximately 2 – 4 hours after satellite overpass for MODIS Rapid Response to process the data, and for the Fire Information for Resource Management System (FIRMS) to update the website. Occasionally, hardware errors can result in processing delays beyond the 2-4 hour range. Additional information on the MODIS system status can be found at MODIS Rapid Response.Attribute InformationLatitude and Longitude: The center point location of the 1km (approx.) pixel flagged as containing one or more fires/hotspots (fire size is not 1km, but variable). Stored by Point Geometry. See What does a hotspot/fire detection mean on the ground?Brightness: The brightness temperature measured (in Kelvin) using the MODIS channels 21/22 and channel 31.Scan and Track: The actual spatial resolution of the scanned pixel. Although the algorithm works at 1km resolution, the MODIS pixels get bigger toward the edge of the scan. See What does scan and track mean?Date and Time: Acquisition date of the hotspot/active fire pixel and time of satellite overpass in UTC (client presentation in local time). Stored by Acquisition Date.Acquisition Date: Derived Date/Time field combining Date and Time attributes.Satellite: Whether the detection was picked up by the Terra or Aqua satellite.Confidence: The detection confidence is a quality flag of the individual hotspot/active fire pixel.Version: Version refers to the processing collection and source of data. The number before the decimal refers to the collection (e.g. MODIS Collection 6). The number after the decimal indicates the source of Level 1B data; data processed in near-real time by MODIS Rapid Response will have the source code “CollectionNumber.0”. Data sourced from MODAPS (with a 2-month lag) and processed by FIRMS using the standard MOD14/MYD14 Thermal Anomalies algorithm will have a source code “CollectionNumber.x”. For example, data with the version listed as 5.0 is collection 5, processed by MRR, data with the version listed as 5.1 is collection 5 data processed by FIRMS using Level 1B data from MODAPS.Bright.T31: Channel 31 brightness temperature (in Kelvins) of the hotspot/active fire pixel.FRP: Fire Radiative Power. Depicts the pixel-integrated fire radiative power in MW (MegaWatts). FRP provides information on the measured radiant heat output of detected fires. The amount of radiant heat energy liberated per unit time (the Fire Radiative Power) is thought to be related to the rate at which fuel is being consumed (Wooster et. al. (2005)).DayNight: The standard processing algorithm uses the solar zenith angle (SZA) to threshold the day/night value; if the SZA exceeds 85 degrees it is assigned a night value. SZA values less than 85 degrees are assigned a day time value. For the NRT algorithm the day/night flag is assigned by ascending (day) vs descending (night) observation. It is expected that the NRT assignment of the day/night flag will be amended to be consistent with the standard processing.Hours Old: Derived field that provides age of record in hours between Acquisition date/time and latest update date/time. 0 = less than 1 hour ago, 1 = less than 2 hours ago, 2 = less than 3 hours ago, and so on.RevisionsJune 22, 2022: Added 'HOURS_OLD' field to enhance Filtering data. Added 'Last 7 days' Layer to extend data to match time range of VIIRS offering. Added Field level descriptions.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

The location of existing and planned sources of energy, both electricity and heat, is provided as part of the Scotland Heat Map. Alongside data on heat demand, this is used to identify opportunities to reduce carbon emissions from heat in buildings, either by connecting supply and demand in a more efficient manner or by using lower carbon alternatives to existing supply. Data on each energy supply point includes, where available, capacity size category, main technology used (e.g., ‘wind’, ‘biomass’) and planning status (e.g., ‘operational’, ‘in development’). This dataset is new for the Scotland Heat Map 2022 (which was released to local authorities in November 2023). It replaces the data on existing and planned energy supply in earlier versions of the heat map. The Scotland Heat Map is produced by the Scottish Government. Data on existing and planned energy supply comes three sources. Two are UK Government sources: the Renewable Energy Planning Database (REPD) and the Major Power Producers (MPP) dataset. The third is the Energy Saving Trust’s (EST’s) Renewable Heat Database (RHD). Records from the MPP dataset have only been included where they have a fuel type of fossil fuel or nuclear, or where they have a renewable fuel type but their installed capacity is less than 1 MW. This is to avoid overlap with the REPD as much as possible. Records from the RHD have only been included where they output heat only, their installed capacity is 1 MW or higher and they can be shared. The 2020 quarter 4 extract of REPD has been used. MPP data was provided by the UK Government in late 2020. The RHD provides installation information as at end December 2021. More information can be found in the documentation available on the Scottish Government website: https://www.gov.scot/publications/scotland-heat-map-documents/

A heatwave refers to a prolonged period of unusually hot weather. While there is no standard definition of a heatwave in England, the Met Office generally uses the World Meteorological Organization definition of a heatwave, which is "when the daily maximum temperature of more than five consecutive days exceeds the average maximum temperature by 5°C, the normal period being 1961-1990". They are common in the northern and southern hemisphere during summer, and have historically been associated with health problems and an increase in mortality. The urban heat island (UHI) is the phenomenon where temperatures are relatively higher in cities compared to surrounding rural areas due to, for example, the urban surfaces and anthropogenic heat sources. For an example of an urban heat island map during an average summer, see this dataset. For an example of an urban heat island map during a warm summer, see this dataset. As well as outdoor temperature, an individual’s heat exposure may also depend on the type of building they are inside, if indoors. Indoor temperature exposure may depend on a number of characteristics, such as the building geometry, construction materials, window sizes, and the ability to add extra ventilation. It is also known that people have different vulnerabilities to heat, with some more prone to negative health issues when exposed to high temperatures. This Triple Jeopardy dataset combines: Urban Heat Island information for London, based on the 55 days between May 26th -July 19th 2006, where the last four days were considered a heatwave An estimate of the indoor temperatures for individual dwellings in London across this time period Population age, as a proxy for heat vulnerability, and distribution From this, local levels of heat-related mortality were estimated using a mortality model derived from epidemiological data. The dataset comprises four layers: Ind_Temp_A – indoor Temperature Anomaly is the difference in degrees Celsius between the estimated indoor temperatures for dwellings and the average indoor temperature estimate for the whole of London, averaged by ward. Positive numbers show dwellings with a greater tendency to overheat in comparison with the London average HeatMortpM – total estimated mortality due to heat (outdoor and indoor) per million population over the entire 55 day period, inclusive of age effects HeatMorUHI – estimated mortality per million population due to increased outdoor temperature exposure caused by the UHI over the 55 day period (excluding the effect of overheating housing), inclusive of age effects HeatMorInd - estimated mortality per million population due to increased temperature exposure caused by heat-vulnerable dwellings (excluding the effect of the UHI) over the 55 day period, inclusive of age effects More information is on this website and in the Triple Jeopardy leaflet. The maps are also available as one combined PDF. More information is on this website and in the Triple Jeopardy leaflet.

The Scotland Heat Map includes information on the percentage of households in each 2011 Data Zone that are renting their home from a council or a housing association (socially renting). Alongside other heat map datasets, this data is used to identify areas suitable for measures to reduce carbon emissions from heating homes and other buildings. For example, through the creation of heat networks. The 2011 Census provides the total number of households and the number of socially rented households in each 2011 Data Zone. Scotland’s census is carried out by National Records of Scotland. Boundaries for Data Zones are created by the Scottish Government. Census data and Data Zone boundaries are updated approximately every 10 years. The Scotland Heat Map is a tool to help plan for the reduction of carbon emissions from heat in buildings. More information can be found in the documentation available on the Scottish Government website: https://www.gov.scot/publications/scotland-heat-map-documents/ The Scotland’s Census website provides details on how the census is carried out and information on accessing publicly available census data, including geographical areas: https://www.scotlandscensus.gov.uk/