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The Power of Heatmaps

Data Processing & Custom Development
April 29, 2024

Heatmaps, or georeferenced single-band rasters, are a type of data visualization that represents various measurements—such as elevation, temperature, depth, methane concentration, or magnetic anomalies—across geographical locations. In most cases it gives invaluable additional information for data analysts.

Examples of Heatmap Applications

1. Elevation Maps: These maps measure the height of terrain at different points. Such data is usable in construction or mining, enabling the calculation of material volumes, cross-sections, and site differences. 

Sources of data: photogrammetry or LIDAR

2. Thermal Maps: By showing temperature variations, thermal maps are crucial for identifying solar panel faults or building insulation issues. 

Sources of data: infrared (IR) cameras and photogrammetry software.

3. Depth Maps: Similar to elevation maps but for underwater, showing depths based on echosounder data. They are essential for marine navigation, underwater inspections and construction planning, mapping of sediments in ponds, lakes and rivers.

Sources of data: echo sounders or bathymetry LIDARs

4. Methane Leak Maps: These indicate methane concentrations at sites like landfills or gas pipelines, aiding in the detection of leaks. 

Sources of data: TDLAS methane detectors or methane sniffers

5. Magnetic Anomaly Maps: Used in mining exploration and utility location, these maps reveal variations in the magnetic field, indicating potential resource deposits or infrastructure.

Sources of data: magnetometers

Enhancing Heatmap Readability

While heat maps provide detailed data, the presentation is key to their utility. Here are some tips and tricks to enhance their readability:

- Overlaying on Maps: Displaying heatmaps over traditional maps (like Google Maps or custom orthomosaics) with color coding and transparency helps contextualize the data spatially.

Displaying heatmaps over traditional maps (like Google Maps or custom orthomosaics) with color coding and transparency helps contextualize the data spatially.

- Color Palettes: Colors are chosen to represent data values effectively—typically, blue for low values and red or white for high values, with a spectrum in between. This choice can depend on the specific application, industry standards and customer preferences.

Colors are chosen to represent data values effectively—typically, blue for low values and red or white for high values, with a spectrum in between. This choice can depend on the specific application, industry standards and customer preferences.

- Value Range Clipping: Limiting the range of displayed values can eliminate outliers and emphasize areas of interest, thereby making the data clearer and more focused.

Limiting the range of displayed values can eliminate outliers and emphasize areas of interest, thereby making the data clearer and more focused.

- Hillshading: Adding a 3D effect through hillshading can highlight minor variations in the data, providing a more detailed and visually appealing representation.

Adding a 3D effect through hillshading can highlight minor variations in the data, providing a more detailed and visually appealing representation.

Project delivery

Creating visually appealing and informative heatmaps is crucial for client presentations. Open question is how to deliver to customers without the need to install specialized software.

DroneGIS serves as a cloud-based platform that enables users to upload, store, and manage georeferenced heatmap data, facilitating access, collaboration and reporting. It offers tools for adjusting the visual appearance of heatmaps, including customizable color palettes and overlay settings, to enhance readability and client presentation.

DroneGIS accepts the following types of heatmaps: 

  • GeoTiffs from Agisoft Metashape, Pix4DMapper, Pix4DFields, SimActive, DroneDeploy, PropellerAero and other photogrammetry tools
  • GeoTiff DTM, DSM from LIDAR360, LP360, TerraSolid and other point cloud processing software
  • Grids (.grd) from Oasis Montaj or similar software
  • CSV files from sensors with Latitude, Longitude, Value structure which are automatically converted to a heatmap
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