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This guidebook provides a comprehensive overview of 🔥 thermal 🧊 data products generated by the 🪴 Plant Science team. The document outlines the organization of thermal data products, details the processing steps involved, and offers beginner-friendly instructions on data exploration techniques.

Data Product Level Identification

The data product level plays a crucial role in understanding the processing state of the thermal data. Here's how to identify the product level from the filename convention:

  • Example Filename: 2024_4_25_F58_thermal.L3T.tif
  • Breakdown:
    • 2024_4_25_F58_thermal: This prefix encodes the data collection details - year, month, day, field identifier (F##, here F58), and sensor type (thermal).
    • L3T: This extension indicates the data product level (L3T in this example).
    • tif: This extension signifies the file format (Tagged Image File Format).

Compressed Files (ZIP):

  • If you receive the data in a compressed ZIP archive, unzip the file to access the individual data products.

Data Product Level Definitions

Product level Remarks
Level 0 Raw data
Raw sensor data in TMC format. Find more details in this link.
Level 0 RJPEG
Thermal data converted from ThermoViewer software and saved in RJPEG format (radiometrically corrected JPEG). Used internally as input to Level 1 Processing (L1P).
Level 1 Pix4D project
Pix4D project files including images, processing settings, and intermediate results. For internal reference only.
Level 2 Temperature (L2T) Temperature orthomosaic (georeferenced image) where each pixel represents a relative temperature value. Not yet calibrated to absolute temperatures using ground-truth measurements
Level 3 Temperature
Temperature orthomosaic where each pixel represents an absolute temperature value. Calibrated to absolute temperatures using ground-truth measurements.
Level 3 Temperature heatmap
Temperature orthomosaic with colormap visualization (yellow = high, indigo = low).
Level 4 Temperature
Manually georeferenced L3T data product. Generated on a per-request basis.
Level 4 Temperature heatmap
Manually georeferenced L3TH data product. Generated on a per-request basis.

Georeferencing and Data Accuracy

Since field surveys or reference objects for georeferencing weren't performed and used, readily available features were used for alignment when creating Level 4 data products. Examples of such features include weeds, thermal pads, tire track intersections, or bare soil patches. While this approach allows us to tie thermal images to RGB images, it limits the overall geospatial accuracy. We expect the accuracy to be up to 5 meter for Level 4 products (L4T, L4TH) and 5-10 meters for Level 3 products (L3T, L3TH). As this type of georeferencing is time-intensive, Level 4 data is provided on a per-request basis.

Temperature Data Exploration with QGIS

  • Open-source ⛰️ Geographic Information System (GIS) software, such as QGIS, can be used to explore the temperature data extracted from the processing pipeline.

    • 🔥 Temperature Value Retrieval: The Identify Features tool within QGIS allows users to query individual pixels and retrieve their corresponding temperature values from the L2T and L3T data layers.

    • 👀 Visualizing Temperature Trends: The L3TH data layer provides a visual representation of the overall temperature trends within the image. ❗It's important to note that the pixel values in L3TH do not represent absolute temperatures.

If you have any questions, please email 🌞Sun (


Plant Science UAV Thermal Data Handbook






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