Address
304 North Cardinal
St. Dorchester Center, MA 02124
Work Hours
Monday to Friday: 7AM - 7PM
Weekend: 10AM - 5PM
What Is the Field of View FOV and Ground Coverage of a Hyperspectral Camera?
Hyperspectral Imaging
How Wide Is a Hyperspectral Camera’s Field of View?
A Complete Guide to “Collection Swath”
A Complete Guide to “Collection Swath”
A hyperspectral camera’s collection swath = spatial resolution × pixel count, determined jointly by focal length, altitude, and the detector array. Seeing wide doesn’t mean seeing sharp — the art is finding the “just right” balance.
1 Spatial Resolution vs. Collection Swath — What’s the Difference?
Spatial Resolution (how sharp)
Spatial resolution: the real-world size one pixel represents on the ground
(e.g., 3 cm × 3 cm)
(e.g., 3 cm × 3 cm)
High resolution (fine detail)
Pixel footprint on ground:
3 cm × 3 cm per pixel
Each cell = 3 cm × 3 cm
→ Fine detail, smaller swath
VS
Collection Swath (how wide)
Collection swath: total ground area covered by a single image
(e.g., 60 m wide)
(e.g., 60 m wide)
Large swath (broader coverage)
Pixel footprint on ground:
15 cm × 15 cm per pixel
Each cell = 15 cm × 15 cm
→ Wider coverage, coarser detail
One is like a magnifying glass over a map — the other is like stepping back for a panoramic view
Magnifying glass (see sharp)
- Higher magnification
- Finer detail visible
- Smaller area covered
⟷
Step back, panoramic view (see wide)
- More ground covered
- Detail becomes blurry
Spatial resolution and collection swath are in tension:
To “see sharp” (high resolution), fly lower & use long focal length & fewer pixels — but “swath” shrinks.
To “see wide”, fly higher & use short focal length & more pixels — but “sharpness” degrades.
To “see sharp” (high resolution), fly lower & use long focal length & fewer pixels — but “swath” shrinks.
To “see wide”, fly higher & use short focal length & more pixels — but “sharpness” degrades.
Today we focus on the collection swath (also called “swath width”) of hyperspectral cameras — how to calculate it, what determines it, and why bigger isn’t always better.
2 How Is the Collection Swath Calculated?
For the most common push-broom hyperspectral camera (a single row of detectors scanning line-by-line, like a broom sweeping):
Swath Width Formula
Swath W = GSD (spatial resolution) × N (pixels per row)
Example: GSD = 3 cm per pixel, N = 2,000 pixels per row
→ Swath W = 3 cm × 2,000 = 6,000 cm = 60 m
→ Swath W = 3 cm × 2,000 = 6,000 cm = 60 m
When mounted on a UAV, a single flight pass sweeps a 60-metre-wide strip — that’s the collection swath.
3 What Factors Determine the Collection Swath?
The swath is not fixed by the camera alone — it is a system-level result, governed primarily by four factors:
Four Key Factors: Their Effect on Swath Width (W) and Spatial Resolution (GSD)
| Factor | Effect on Swath W | Effect on GSD | |
|---|---|---|---|
| 1 | Pixel size & pixel count | More pixels N → wider swath W (all else equal) | GSD unchanged (if other factors constant) |
| 2 | Focal length | Shorter focal length → larger FOV → wider swath W | GSD unchanged (if other factors constant) |
| 3 | Flight altitude | Higher altitude H → wider swath W | Higher H → larger GSD (lower resolution) |
| 4 | Scan mode | Push-broom: strip; Frame scan: 2-D area | GSD set by altitude, focal length & pixel size |
1
Pixel Size & Pixel Count
(determines swath width)
The number of detector pixels in a single row (e.g. 2,000 or 4,000) multiplied directly by GSD gives swath width. More pixels → potentially wider swath.
Example 1: 2,000 px
N = 2,000
Swath W₁
Swath W₁
Example 2: 4,000 px
N = 4,000
Swath W₂ = 2 × W₁
Swath W₂ = 2 × W₁
At the same GSD, more pixels → wider swath.
2
Lens Focal Length
(determines FOV and swath)
Shorter focal length → larger field of view (FOV), covering more ground at the same altitude. Long-focus lenses narrow the swath but enable sharper, more detailed views.
Wide-angle (e.g. 12 mm)
Large FOV → wide swath
Telephoto (e.g. 50 mm)
Small FOV → narrow swath
Same altitude H: short focal → large FOV → wide swath; long focal → small FOV → narrow swath.
3
Flight Altitude
(affects both swath and resolution)
Flying higher increases ground coverage, but also increases GSD (each pixel covers a larger area), reducing spatial resolution. Expanding swath often requires a trade-off in resolution.
Low alt. H₁
Swath W₁
GSD small
Swath W₁
GSD small
→
High alt. H₂
Swath W₂ > W₁
GSD large
Swath W₂ > W₁
GSD large
Flying higher: W increases, but GSD also increases (lower resolution).
4
Scan Mode
(determines collection geometry)
Push-broom cameras sweep one line at a time — coverage is a long strip (width = swath W). Frame-scan cameras capture a 2-D array at once — coverage is a rectangular area (length × width).
Push-broom (Line Scan)
Collects one strip at a time
Coverage: strip (width = W)
Coverage: strip (width = W)
Frame Scan
Captures 2-D area at once
Coverage: rectangle (L × W)
Coverage: rectangle (L × W)
In practice, optimize swath vs. resolution trade-off based on mission requirements.
4 Is a Larger Collection Swath Always Better?
Not necessarily — it requires a balance between “seeing wide” and “seeing sharp.”
When large swath is preferred
Scanning large agricultural fields or inspecting long pipelines in a single pass — wide swath means higher efficiency per flight.
When it creates complexity
Achieving both large swath and high spatial resolution simultaneously demands many detector pixels (e.g. tens of thousands per row) or multi-camera mosaicking — making systems more complex and costly.
Typically, hyperspectral camera swath ranges from tens of metres (UAV-mounted) to several kilometres (satellite-borne) — it all depends on mission design.
5 One-sentence Summary
The key formula to remember
Collection Swath = GSD × Pixel Count
Governed by focal length, altitude, and the detector — always in tension with “seeing sharp.”
Next time you look at a hyperspectral image, ask two questions:
1. How wide a strip of ground does it cover?
2. How small a patch does each pixel represent?
Once you know both, you understand exactly what the system can do.
Seeing wide doesn’t mean seeing sharp; seeing sharp doesn’t mean seeing wide. The wisdom of hyperspectral imaging lies in finding that “just right” balance between the two.
