Thermal Drone Inspection Calculator

Calculate thermal camera resolution, defect detection capability, and flight parameters for building, solar panel, and infrastructure inspections.

Inputs

Thermal resolution (H pixels)

Thermal resolution (V pixels)

Horizontal FOV (°)

Flight altitude (m)

NETD (mK)

Min defect size (cm)

Inspection area (m²)

Flight speed (m/s)

Image overlap (%)

Ambient temp (°C)

Expected surface temp (°C)

Tab to move between fields

Results

Spatial resolution (cm/px)

1.64

Pixels on min defect

6.1

Detection level (0-3)2

IFOV (mrad)1.09

Min detectable ΔT (°C)0.25

Frame width on ground (m)10.9

Frame height on ground (m)8.6

Flight passes6

Total thermal frames48

Flight time (min)1.1

Max altitude for recognition (m)15.3

Required frame rate (Hz)0.7

Detection CapabilityRecognition (6-12 px)

Temp Delta DetectableYes

How to Use This Calculator

Enter thermal camera resolution (H × V pixels), horizontal field of view (°), and flight altitude (m).
Set NETD (mK) — the camera's thermal sensitivity, typically 25–50 mK for inspection cameras.
Enter the minimum defect size (cm) you need to detect (e.g., delamination, hot spots).
Review spatial resolution (cm/px), pixels on the minimum defect, and detection confidence level.
If pixels-on-defect is below 9, reduce altitude or use a camera with a longer focal length.

How the result changes with Thermal resolution (H pixels)

Thermal resolution (H pixels)	Spatial resolution (cm/px)	Pixels on min defect
200	5.24	1.9
500	2.09	4.8
860	1.22	8.2
1,160	0.9	11.1

What each input means

Thermal resolution (H pixels): Horizontal pixel count of thermal sensor (e.g., 640×512 is common).
Thermal resolution (V pixels): Vertical pixel count of thermal sensor.
Horizontal FOV (°): Thermal camera horizontal field of view in degrees.
Flight altitude (m): Distance from camera to target surface. For rooftops, this is AGL.
NETD (mK): Noise Equivalent Temperature Difference. Lower = more sensitive. Good cameras: 30-50 mK.
Min defect size (cm): Smallest anomaly you need to detect (e.g., 10 cm hot spot, delamination).
Inspection area (m²): Total area to inspect (rooftop, solar array, facade).
Flight speed (m/s): Slower speed improves thermal image quality. 2-4 m/s typical.
Image overlap (%): Overlap between consecutive thermal frames. 50% typical for inspections.
Ambient temp (°C): Current air temperature. Affects thermal contrast.
Expected surface temp (°C): Expected temperature of the surface being inspected.

What each result means

Spatial resolution (cm/px): Size of one thermal pixel on the target surface.
Pixels on min defect: How many thermal pixels cover the minimum defect size. Need 6+ for recognition.
Detection level (0-3): 0 = below threshold, 1 = detection, 2 = recognition, 3 = identification.
IFOV (mrad): Instantaneous field of view per pixel in milliradians.
Min detectable ΔT (°C): Minimum temperature difference reliably detectable (5× NETD).
Frame width on ground (m): Width of each thermal frame on the target surface.
Frame height on ground (m): Height of each thermal frame on the target surface.
Flight passes: Number of parallel passes needed.
Total thermal frames: Total images captured during inspection.
Flight time (min): Estimated inspection flight duration.
Max altitude for recognition (m): Maximum altitude to achieve recognition-level detail on the minimum defect.
Required frame rate (Hz): Minimum capture rate to maintain overlap at current speed.

How this is calculated

Worked example, using the default values

Identify Input Parameters
4 parameters
Thermal resolution (H pixels) = 640, Thermal resolution (V pixels) = 512, Horizontal FOV (°) = 40, Flight altitude (m) = 15 = 11 input(s) provided
Calculate Spatial resolution
Spatial resolution = ifovRad * flightAltitudeM * 100
1.64 = 1.64
Calculate Pixels on min defect
Pixels on min defect = defectSizeM / (spatialResCm / 100)
6.1 = 6.1
Calculate Detection level
2 = 2
Calculate IFOV
IFOV = ifovRad * 1000
1.09 = 1.09

Engine last updated August 5, 2026.

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