The heat map software market is experiencing robust growth, driven by the increasing need for businesses to understand user behavior and optimize website and application design for enhanced user experience (UX). The market, estimated at $2 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $6 billion by 2033. This growth is fueled by several key factors. Firstly, the rising adoption of digital platforms across various industries necessitates effective UX optimization, making heat map software an indispensable tool for businesses aiming to boost conversion rates and customer satisfaction. Secondly, advancements in technology, such as AI-powered analytics and integration with other marketing tools, are enhancing the capabilities and accessibility of heat map solutions. Finally, the growing emphasis on data-driven decision-making within organizations further propels the market's expansion. The competitive landscape is characterized by a blend of established players and emerging startups, fostering innovation and driving down prices. While increased competition could pose a challenge, the overall market outlook remains highly positive, with continued growth anticipated across various regions and segments. Despite its promising trajectory, the market faces some restraints. The relatively high cost of advanced heat map software may limit adoption for smaller businesses with tighter budgets. Furthermore, the complexity of analyzing and interpreting heat map data may require specialized expertise, posing a barrier for some users. However, the ongoing development of user-friendly interfaces and affordable solutions is gradually mitigating these challenges. Segmentation within the market is evolving, with distinct solutions emerging for specific industries and applications, catering to niche needs. The market is segmented by deployment (cloud, on-premise), pricing model (subscription, one-time purchase) and industry (e-commerce, gaming, education, etc). Key players like Hotjar, Smartlook, and others are actively innovating to expand their offerings and remain competitive in this dynamic market.

About the App This app hosts data from Heat Resilience Solutions for Boston (the Heat Plan). It features maps that include daytime and nighttime air temperature, urban heat island index, and extreme heat duration. About the DataA citywide urban canopy model was developed to produce modeled air temperature maps for the City of Boston Heat Resilience Study in 2021. Sasaki Associates served as the lead consultant working with the City of Boston. The technical methodology for the urban canopy model was produced by Klimaat Consulting & Innovation Inc. A weeklong analysis period during July 18th-24th, 2019 was selected to produce heat characteristics maps for the study (one of the hottest weeks in Boston that year). The data array represents the modelled, average hourly urban meteorological condition at 100 meter spatial resolution. This dataset was processed into urban heat indices and delivered as georeferenced image layers. The data layers have been resampled to 10 meter resolution for visualization purposes. For the detailed methodology of the urban canopy model, visit the Heat Resilience Study project website.

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: Sensing package time step valuesUnits: decimal degrees 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.Cities IncludedBaltimore, Boise, Boston, Fort Lauderdale, Honolulu, Los Angeles, Nampa, Oakland-Berkeley, Portland, Richmond, Sacramento, San Bernardino, San Juan, Victorville, Washington, West Palm Beach, Worcester, Charleston and YonkersCities may apply to be a part of the Heat Watch program through the CAPA Strategies website. Attribute Table Informationcity_name: Boston MAAfternoon air temperatures in cities

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 Scotland Heat Map is a tool to help plan for the reduction of carbon emissions from heat in buildings. This service allows users to download spatial data from the map. 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/

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/

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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 1km x 1km 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/

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 250m x 250m 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/

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: air temperatureUnits: 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 Air Temperature and Evening Air Temperature. 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 Air Temperature Observations in Floating-Point (°F)

The Scotland Heat Map provides the locations of existing and planned heat networks. Both communal and district heat networks are included. Data about each network includes, where available, heat capacity size category, network name, status (either 'operational' or 'in development') and the main technology used (for example, 'boiler'). There is only one point location for each network, the data does not show all connected properties or pipe layouts. Networks can serve domestic properties, non-domestic properties or a mixture of the two. Heat networks have the potential to reduce carbon emissions from heating buildings. Alongside other heat map datasets, information on existing and planned networks is used to identify further opportunities to reduce carbon emissions. For example, by connecting more buildings to an existing network or by replacing the energy source with a nearby lower carbon alternative. Data on heat networks comes from two sources. These are: the UK Department for Energy Security and Net Zero's Heat Networks (Metering and Billing) Regulations (HNMBR) dataset and Zero Waste Scotland's Low Carbon Heat Database (LCHD). The most recent data available is up to end July 2022 for the HNMBR dataset (though the majority of the HNMBR data included in the heat map is up to end December 2018) and January 2022 for the LCHD. 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: Sensing package time step valuesUnits: decimal degrees 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.Cities IncludedBaltimore, Boise, Boston, Fort Lauderdale, Honolulu, Los Angeles, Nampa, Oakland-Berkeley, Portland, Richmond, Sacramento, San Bernardino, San Juan, Victorville, Washington, West Palm Beach, Worcester, Charleston and YonkersCities may apply to be a part of the Heat Watch program through the CAPA Strategies website. Attribute Table Informationcity_name: Boston MAMorning air temperatures in cities

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)

This map contains the distribution of hurricane force low pressure centers from 06/2021 through 05/2022 over the North Pacific Ocean. The distribution is plotted as a heat map and indicates the density of hurricane force low centers across the basin during this period. As you zoom in the areas with more hurricane force low pressure centers will appear brighter on the map.The data for the low centers used for the distribution on the map have been taken directly from the Ocean Prediction Center's (OPC's) North Pacific Surface Analyses. The data are also available on the OPC's website in a csv (comma separated value) file along with the associated metadata file. For clarification, an "extratropical" or "post-tropical" low pressure system is classified as "hurricane force" when the winds reach an intensity of 64 knots, or equivalently, 73.6 miles per hour. A system is termed "rapidly intensifying" when the central pressure decreases by at least 24 hectopascals (hPa) or millibars (mb) over a consecutive 24 hour period. In addition, a system is defined as "extratropical" when it is a cold-core non-tropical system. A "post-tropical" system is essentially the same as an extratropical system, but it develops initially as a tropical cyclone before losing its tropical characteristics and transitioning to an extratropical cyclone.

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!

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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/

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: Sensing package time step valuesUnits: decimal degrees 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.Cities IncludedBaltimore, Boise, Boston, Fort Lauderdale, Honolulu, Los Angeles, Nampa, Oakland-Berkeley, Portland, Richmond, Sacramento, San Bernardino, San Juan, Victorville, Washington, West Palm Beach, Worcester, Charleston and YonkersCities may apply to be a part of the Heat Watch program through the CAPA Strategies website. Attribute Table Informationcity_name: Charlottesville VAAfternoon air temperatures in cities