The Ultimate Guide to Thermal Scopes in Australia →
Thermal Academy · Core Curriculum · Capstone
You’re standing at the edge of a paddock on a cold, still night. You lift the thermal, sweep the far tree line, and there it is — a bright, glowing shape out near the fence, maybe two kilometres away. The scope found it instantly. For a second it feels like a superpower. Then the obvious question lands, and the superpower evaporates:
What is it?
You push the zoom. The shape gets bigger but no clearer — a warm smudge, softening as you magnify it. Fox? Calf? Feral pig? A person walking a dog? You genuinely cannot tell. And right there, on the edge of that paddock, you’ve bumped into the single biggest misunderstanding in all of thermal imaging: seeing something is not the same as knowing what it is. “How far can it see?” turns out to be almost the wrong question. The honest question has three parts — how far can it detect, how far can it recognise, and how far can it identify? — and the gap between them is enormous.
Detection is easy.
Identification is hard.
Thermal Academy
This is the article everything else in Thermal Academy has been building toward. Every earlier lesson — heat, lenses, sensors, contrast, weather, NETD, emissivity, the microbolometer, calibration — was quietly assembling the parts you need to understand this one. Because here’s the surprise waiting at the end: none of those specifications, on its own, tells you how far a thermal can identify an animal. Only together do they give an answer. Detection range isn’t a number on a box. It’s what happens when every specification you’ve learned about works together — or fails together.
Key takeaways
- “How far can it see?” has three answers, not one: detect (something’s there), recognise (what kind of thing), and identify (exactly what it is). These are the DRI ranges.
- The three are far apart. A thermal might detect at 2,000 m, recognise at 500 m and identify at 300 m — same animal, same night.
- The model behind them is the Johnson criteria: identifying something needs many more pixels on target than merely detecting it.
- A brochure’s headline “detection range” is the easiest, longest number. The range you actually hunt at — where you can identify your target — is a fraction of it.
- Range is set by everything at once: lens, resolution, pixel pitch, NETD, weather, contrast, crossover, emissivity, the sensor and its calibration. Change any one and the range changes.
- Which is why the true answer to “how far can it see?” is “it depends” — and this guide is about exactly what it depends on.
The Three Questions: Detect, Recognise, Identify
Thermal professionals stopped asking “how far can it see?” a long time ago, because the question hides three completely different tasks. Picture that same warm animal walking slowly toward you across the paddock. As it closes the distance, your thermal passes through three milestones in order — and they can be a kilometre or more apart.
Detection, recognition and identification are three separate ranges for the same target on the same night. Far out it’s a dot you know is there; closer, a shape you know is an animal; closer still, a creature you know is a fox. The distances aren’t close together — and the one that matters for an ethical shot is the shortest.
These three milestones have names, and together they’re called DRI — detection, recognition, identification. They’re not marketing terms; they come straight from decades of imaging science (the Johnson criteria, which we’ll get to). Every serious conversation about thermal range is really a conversation about which of the three you mean.
Detection: Knowing Something Is There
Detection is the easy one, and it’s where the giant marketing numbers come from. To detect a target, your thermal only has to register that a patch of the scene is warmer (or cooler) than its surroundings — a single bright speck against a dark field. It doesn’t need shape, edges or detail; it needs a hot dot standing out from the background. Because a warm animal against cool ground is a strong signal, detection happens a long way out — often well over a kilometre, sometimes two or more for a large, warm target on a cold, clean night.
The catch is that detection tells you almost nothing useful on its own. A bright dot at 1,800 m could be a deer, a dog, a person, a warm rock, a fence-post cap holding the day’s heat, or a distant vehicle. You know something is out there. You have no idea what — and you certainly can’t act on it. Detection is the start of the conversation, not the answer.
Recognition: Knowing What Kind of Thing It Is
Recognition is the next step in, and it demands more from the sensor. Now the target has to be close enough — and rendered with enough pixels — that its shape emerges. You can tell an animal from a vehicle, an upright person from a four-legged creature, a big-bodied pig from a lean dog. You still might not know the exact species, but you’ve sorted it into a category. For a lot of situations that’s genuinely useful: recognising “that’s an animal, not a person” or “that’s a vehicle, not a herd” is often enough to decide what to do next.
Recognition happens much closer than detection — very roughly a fifth to a third of the published detection distance for the same target — because a shape needs several times more pixels across it than a mere blob. This is the range band where the differences between thermals start to show. A sharper sensor with a longer lens holds a recognisable shape together further out; a modest one collapses the same animal into an ambiguous smear much sooner.
Identification: Knowing Exactly What It Is
Identification is the one that matters most, and it’s the hardest by a wide margin. To identify a target you need enough detail to be sure: not just “an animal” but “a fox and not a feral cat,” not just “a large animal” but “a fallow deer and not a calf” — and, crucially, “an animal and definitely not a person.” This is the range at which a responsible shooter is willing to act, because it’s the range at which you actually know what you’re looking at.
Because certainty needs fine detail, identification happens closest of all — often only about an eighth to a fifth of the headline detection distance. That animal your scope detected at 2,000 m might not be identifiable until it’s inside 300 m. Everything between those two numbers is the zone where you can see that something is there but must not assume what it is. Treat every DRI figure as a probabilistic model prediction, never as confirmation of what you are looking at: never use a detection, recognition or identification range to decide whether a target is safe or legal to engage. Positive identification is made with your own eyes, at a distance where you are certain. For hunting, identification range is the number that counts, and it’s the one no brochure puts on the front of the box.
| Level | The question it answers | Roughly what it needs | Relative range |
|---|---|---|---|
| Detection | Is something there? | A warm blob standing out from the background | Longest (the headline number) |
| Recognition | What kind of thing is it? | Enough pixels for a rough shape | ~⅓ to ½ of detection |
| Identification | Exactly what is it? | Enough pixels for clear features | ~¼ to ⅕ of detection |
The relative-range figures are rules of thumb, not guarantees — the exact ratios shift with the target and conditions. But the shape always holds: identification range is a small fraction of detection range.
Johnson Criteria: The Rule Behind the Three
So why are the three ranges so far apart? The answer is beautifully simple and it’s the key that unlocks the whole article: each level needs a different number of pixels on the target. This is the Johnson criteria, worked out in the 1950s and still the backbone of how range is predicted today. It says, roughly, that detecting a target takes only a couple of pixels across its critical dimension; recognising it takes several times more; and identifying it takes more again.
Same animal, three pixel budgets. Two pixels only tell you a warm thing exists. Eight start to sketch a four-legged shape. Thirteen or so let you see the ears, the snout, the tail — enough to be sure. Since a target covers fewer pixels the further away it is, each level is reached at a shorter range.
That’s the whole mechanism. As a target moves away it shrinks in your field of view, so it lands on fewer and fewer detectors — and it drops below the pixel budget for identification long before it drops below the budget for detection. The Johnson criteria guide goes deeper into the exact cycle counts and how they became an industry standard; for range, the one thing to carry forward is this: everything that puts more pixels on your target extends every one of the three ranges. Hold that thought, because it’s about to connect every earlier lesson to this one.
The Marketing Trap: Why “2,600 m Detection” Misleads
Now you can see straight through the single most confusing thing on any thermal spec sheet. When a brochure shouts “2,600 m detection range,” it is quoting the easiest of the three numbers — the distance at which the scope can register a warm blob under favourable conditions. It is technically true and practically misleading, because almost every buyer reads “2,600 m” and hears “I can hunt at 2,600 m.” You cannot. At 2,600 m you’d have a dot you couldn’t even classify, let alone identify.
One number on the box; three very different numbers in the field. The detection bar is real — but the range you can actually act on is the short identification bar at the bottom. This single picture explains why so many first thermals disappoint: the buyer compared headline detection figures and expected to hunt at them.
None of this makes the manufacturers liars — detection range is a legitimate, standardised figure, and it’s genuinely useful for comparing sensors like for like. The trap is purely in the reading. Once you mentally translate “detection range” into “the longest, easiest number, roughly four to five times my real identification range,” the spec sheet stops fooling you and starts informing you. And it sets up the question the rest of this guide answers: if the headline number isn’t the range you hunt at, what actually determines the range you do?
The Detection Range Pyramid
Before we go through the factors one by one, here’s the whole idea in a single picture — the shape worth carrying in your head every time you lift a thermal. The three ranges stack into a pyramid: a wide, easy base where you merely detect, a narrower middle where you recognise, and a small, hard-won apex where you can identify and act. Climbing it means putting more pixels on the target — and everything below decides how high you can climb.
Save this one. The base is the headline “detection range” — easy and far. The apex is where you can ethically act — hard and close. The seven factors underneath are the levers that decide how far up the pyramid your scope can carry you on any given night, and they’re the subject of the rest of this guide.
“It Depends” — and Here’s Exactly What On
Ask an honest expert “how far will this thermal see?” and the answer is always the same two words: it depends. That sounds like a dodge. It isn’t — it’s the entire lesson. Detection range isn’t a fixed property of a scope; it’s the outcome of a dozen things interacting, most of which you’ve already met in Thermal Academy. Everything that puts more pixels on your target, or more signal into those pixels, pushes all three ranges out. Everything that steals pixels or signal pulls them in. Here is the whole cast, each one a lever on the same result — and each with a “remember this?” link back to its own guide.
Lens size — the biggest single lever
A longer lens (more focal length) magnifies the scene onto the sensor, so a distant target lands on more pixels. Swap a 25 mm lens for a 50 mm and you roughly double the pixels across your target — which stretches every DRI range outward. This is the most direct way to reach further, and it’s why long-range setups use big objective lenses. The trade-off, covered in the lens guide, is a narrower field of view: you see further but through a smaller window.
Nothing moved but the lens. Doubling the focal length puts roughly twice as many pixels across the same distant animal — enough to cross from “probably an animal” to “that’s a fox.” This is why lens choice is the most direct lever you have on range.
Sensor resolution — how much scene, how finely
A 640×512 sensor carries far more detectors than a 384×288 one. With the same lens that mostly buys you a wider, finer field of view — more of the paddock, sampled more densely — which in practice means you find targets more easily and keep detail as you push digital zoom. Pair a 640 core with a longer lens and you get both reach and framing. Resolution and lens work together; neither alone is “range.”
Pixel pitch — the fineness of the grid
Pixel pitch is the width of each detector — 12 µm or 17 µm. Smaller pitch means finer angular resolution for a given lens, so more pixels land on a distant target and identification reaches further. It’s the quiet partner of lens size in setting how far you can truly see, and it’s why a 12 µm sensor can out-reach a 17 µm one of the same resolution.
NETD — sensitivity, for the faint targets
Pixels on target get you range only if each pixel can actually tell the target from its background. That’s NETD — the smallest temperature difference a detector can resolve. On a cold night against cold ground a warm animal is easy, but as the contrast fades (dusk, damp, a cool-bodied target), a more sensitive sensor keeps a usable signal where a coarse one loses it into the noise. Low NETD doesn’t add magnification; it protects your range when the scene stops cooperating.
Weather — the range thief
The atmosphere between you and the target is never truly empty, and rain, fog and high humidity actively absorb and scatter infrared. A range you’d get on a clear, dry night can collapse in heavy fog, because the signal is being eaten before it ever reaches your lens. Weather is why the same scope, the same animal and the same lens can give wildly different range on two different nights — and why any single range number is only ever true for one set of conditions.
Contrast — the signal you’re actually reading
A thermal doesn’t see heat; it sees differences in heat. Detection range depends entirely on how far your target’s temperature sits from its background’s — the thermal contrast. A hot pig on cold mud is visible a long way out; the same pig against sun-warmed ground of the same temperature can be nearly invisible up close. Contrast is the raw material range is built from, which is why two identical scopes can post very different ranges on different backgrounds.
Crossover — the worst case
Twice a day, as the land heats and cools, target and background can pass through the same temperature — thermal crossover — and contrast briefly falls toward zero. In those windows even a superb scope’s effective range craters, not because anything is broken, but because there’s momentarily almost no difference to see. It’s the clearest proof that range is a property of the scene as much as the scope.
Emissivity — whether the target tells the truth
How strongly a surface radiates its own heat — its emissivity — decides how much signal even reaches your sensor. Happily, animals are high-emissivity and radiate honestly, so they read at their true warmth and at full range. The relevance to range is mostly the flip side: shiny, low-emissivity surfaces in the scene throw false hot and cold shapes that can be “detected” a long way off yet mean nothing — reflections, not targets.
The sensor & its calibration — clean data to work with
All of the above assumes the sensor itself is delivering honest, even data. That’s the job of the microbolometer and its calibration: hundreds of thousands of tiny detectors, kept in agreement by NUC so the image isn’t smeared with fixed-pattern noise. A drifting, uncalibrated sensor loses fine detail — and fine detail is exactly what identification range is made of. Clean calibration doesn’t add range; it stops you from throwing range away.
Image processing — the last few per cent
Finally, the camera’s image processing — edge sharpening, contrast stretching, detail enhancement — can squeeze a little more usable recognition and identification out of the same raw data by making faint edges easier for your eye to resolve. It can’t invent detail the pixels never captured, but good processing genuinely helps you reach the identification threshold a touch sooner.
| Factor | Push range OUT when… | Range pulls IN when… |
|---|---|---|
| Lens (focal length) | Longer lens (50 mm) | Shorter lens (25 mm) |
| Pixel pitch | Finer (12 µm) | Coarser (17 µm) |
| Resolution | More pixels (640) + a matched lens | Fewer pixels (384) |
| NETD | Lower (more sensitive) | Higher, in low-contrast scenes |
| Weather | Clear, dry, cold | Rain, fog, high humidity |
| Contrast | Target far from background temp | Target near background temp |
| Crossover | Away from crossover windows | During crossover |
| Calibration | Clean, recently corrected | Drifted, overdue for NUC |
Every row is a lever on the same result. Notice that only a few are about the scope — the rest are about the scene and the night. That’s why range can’t be a single number, and why “it depends” is the honest answer.
Try It: An Illustrative Range Calculator
Reading about the levers is one thing; feeling them move is another. The little calculator below is not a spec guarantee — it’s a simplified teaching model built on the Johnson pixel budgets, so you can watch how the pieces interact. Change the lens and see identification range jump. Drop the weather to “poor” and watch all three ranges collapse. Swap a fox for a deer and see how a bigger target is seen further. The exact metres are illustrative; the relationships are the lesson.
Detection range explorer
Illustrative only — a simplified Johnson-criteria model to show how the factors interact, not a performance guarantee.
Detect = something’s there · Recognise = what kind · Identify = the range you’d actually act at.
Watch the identify bar — the range you’d truly hunt at. It’s always a fraction of the headline detect figure, and it’s the first to shrink when the weather turns or the lens gets shorter. That gap, live and moving, is the whole point of this guide.
Putting It Together: Range Is a Result, Not a Spec
Step back and look at what just happened. To answer one deceptively simple question — how far can it see? — we had to call on almost every lesson in Thermal Academy. Not one of them, alone, gives the answer. The lens sets the pixels on target; the pitch and resolution set the fineness; NETD decides whether faint targets survive; weather, contrast and crossover decide what signal even arrives; emissivity decides whether the target radiates honestly; the sensor and its calibration decide whether the detail is preserved; processing squeezes out the last of it. Detection range is where all of those meet.
A capstone should do exactly this: gather every earlier thread into one place. Every road in Thermal Academy leads to detection range, because detection range is what all the roads were about.
Detection range isn’t one specification.
It’s the result of every specification working together.
Thermal Academy
A Worked Example: The Same Fox on Three Nights
Nothing makes “it depends” concrete like watching one variable at a time move the answer. Take a single setup — a good 640×512, 12 µm scope on a 50 mm lens — pointed at the same fox, and change only the night around it. The scope never changes; the answer changes dramatically.
Night one — the dream. Clear sky, cold, dry air, the fox crossing bare cold ground an hour after dark. Contrast is huge, the atmosphere is clean, you’re nowhere near a crossover window. This is where the scope earns its brochure: you detect the fox a long way out and can identify it comfortably at a few hundred metres. If you only ever hunted nights like this, the marketing numbers would almost feel fair.
Night two — the average. Some high cloud, a bit of humidity, ground that soaked up afternoon sun and hasn’t fully let go. Contrast is softer and the damp air nibbles at the signal. The same fox with the same scope is now detected meaningfully closer, and your confident identification range has pulled in by a third or more. Nothing failed — the night simply gave you less to work with.
Night three — the grind. Light drizzle, fog patches, and you’re hunting right through the evening crossover when ground and fox are nearly the same temperature. Now the atmosphere is actively eating the signal and there’s barely any contrast to begin with. The fox you’d have identified at 300 m on night one might be a doubtful smudge at 120 m — if you can pick it out at all. Same scope, same fox, a completely different answer.
| Same 640 / 50 mm scope, same fox | Detect | Recognise | Identify |
|---|---|---|---|
| Night 1 — clear, cold, high contrast | Longest | Comfortable | Furthest — the “dream” number |
| Night 2 — humid, softer contrast | Reduced | Closer | Pulled in by ~a third |
| Night 3 — fog + crossover | Much shorter | Marginal | Very close, sometimes not at all |
Three nights, one scope, one fox — three different sets of ranges. This is “it depends” made concrete, and it’s why a single quoted number can never describe a real hunt. The scope sets the ceiling; the night decides how much of it you actually get.
So How Far Will Your Thermal See?
You now have the tools to answer that for yourself, honestly, on any given night — which is far more valuable than any number a salesperson could give you. Start with what you can control: your lens and sensor set the ceiling on pixels-on-target, so a longer lens on a good 640, 12 µm core reaches furthest. Then subtract for the night: poor contrast, damp air, a target near background temperature or a crossover window will all pull that ceiling down, sometimes dramatically. And always separate the three questions — you’ll detect much further than you can identify, and it’s the identify range that governs what you may ethically do.
Practically, that means judging range as a band, not a point. On a clear, cold night with good contrast, a capable scope might identify a fox out past 300 m and detect one beyond a kilometre; on a warm, humid evening near crossover, those numbers might halve. Neither figure is “wrong” — they’re the same scope answering the same question under different conditions. Learning to feel where you sit in that band, in real time, is the mark of someone who understands their thermal rather than just owns it.
Range lives in the sensor and the glass
Everything here points to the same buying lesson: reach comes from sensor grade and lens, not a headline number. Pixfra’s Pegasus 2 and Cetus pair 640×512, 12µm microbolometers at ≤15 mK NETD with quality objectives — genuine Australian stock, C.R. Kennedy service, and honest specs you can now read for yourself.
Common Detection-Range Myths
Why the Gap Matters: Shoot at Certainty, Not Hope
There’s a moment every experienced hunter knows. A heat signature appears out near the edge of what the thermal can resolve. Your brain — tired, eager, an hour deep into a cold paddock — starts filling in the blanks. You want it to be the fox you came for. But the scope hasn’t actually given you enough to be sure yet. It’s handed you a warm shape and a hope, not an identification.
This is the real reason the three ranges matter, and it’s bigger than any specification. The distance between “I can see something” and “I know exactly what that is” isn’t a technicality — it’s the whole space in which good and terrible decisions get made. Everything in this guide, all the physics and pixels and Johnson criteria, ultimately serves a single judgement made in that moment: has my thermal actually earned my trust for this shot, or is it still just showing me a hopeful smudge?
Good hunters don’t shoot at hope.
They shoot at certainty.
Thermal Academy
Detection range, understood properly, is what lets you tell the two apart in real time. It’s knowing that a signature at 900 m is a detection, not an identification; that the responsible move is to close the distance, wait for a better angle, or let it walk. The discipline to hold when the scope hasn’t earned the shot is the mark of a hunter who understands their thermal — and this entire curriculum, in the end, was teaching you how to know the difference.
Detection Range Is the Final Exam
A dozen lessons ago, the very first idea in Thermal Academy was a simple one: a thermal doesn’t see light at all — only heat. Then came the lenses, the sensors, the weather, NETD, emissivity, the calibration that keeps the picture honest. Each arrived as its own self-contained lesson, and each probably felt like a separate idea. Here’s the quiet truth this capstone reveals: they never were separate. Every one of them was answering the same question — how far can you confidently identify a target? That question is detection range.
Look back at the road you’ve travelled. Across the cornerstones of Thermal Academy you learned about heat and lenses and sensors; about contrast and weather and crossover; about NETD and emissivity; about the microbolometer and the calibration that keeps it honest. Each one felt like a self-contained lesson. And then you arrived here, at the question every buyer starts with — how far can it see? — and discovered something genuinely surprising:
None of those specifications, on its own, can tell you how far a thermal will identify an animal. Together, they do.
That’s why detection range is the perfect capstone. It isn’t a new topic so much as the moment every old topic pays off — the point where lens size stops being trivia and becomes reach, where NETD stops being a millikelvin figure and becomes the difference between seeing your target and losing it, where “it depends” stops being a frustration and becomes a skill. Understand detection range and you don’t just know how far your scope sees; you know why, and you can read any spec sheet, any night, any target, and make an honest call.
Detection is easy.
Identification is hard.
Thermal Academy
So the next time someone hands you a thermal and asks “how far can this thing see?”, you’ll know that the real answer isn’t a number at all. Detection range isn’t a spec on a box. It’s the final exam for everything you’ve learned so far — and by now, you’re ready to pass it.
You’ve mastered how thermal works and what sets its range.
What’s left is getting the most from it in the field.
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Frequently Asked Questions
How far can a thermal scope see?
There’s no single answer — it depends on the target, the conditions and which of three things you mean: detect, recognise or identify. A scope might detect a warm animal beyond 1,500–2,000 m, recognise it as an animal at several hundred metres, and only identify the species inside a few hundred metres. The range you can act on is the identification range, which is a fraction of the headline detection figure.
What is detection range on a thermal?
Detection range is the distance at which the thermal can register that something warm is present — a bright blob against the background — without telling you what it is. It’s the longest and easiest of the three range figures, which is why manufacturers quote it. Useful for comparing sensors, but not the range you hunt at.
What’s the difference between detection, recognition and identification?
They’re the three levels of seeing a target (the “DRI” framework). Detection: something is there. Recognition: what kind of thing it is — animal, vehicle, person. Identification: exactly what it is, such as a fox rather than a cat. Each needs more pixels on the target, so each happens at a shorter range than the last.
What is the Johnson criteria?
It’s the imaging-science model that predicts how much detail a target must span before it can be detected, recognised or identified. It counts cycles — line pairs — across the target, and it takes at least two pixels to render one cycle: about 1 cycle to detect, about 4 to recognise and about 6.4 to identify, each at a 50% probability of success for a trained observer. Because a target covers fewer pixels the further away it is, the Johnson criteria explain why the three ranges are so far apart.
Why is the advertised detection range so much longer than the range I can actually hunt at?
Because “detection” only requires spotting a warm blob, which happens far away, while hunting requires identifying the target, which needs much more detail and so happens much closer. The advertised number isn’t false — it’s just the easiest of the three. Expect your usable identification range to be roughly an eighth to a fifth of the quoted detection range.
How far can a thermal identify a fox or a pig?
As a rough guide, a capable 640, 12 µm scope with a decent lens might identify a fox somewhere around 250–400 m and a larger pig or deer further, in good conditions — but this varies enormously with lens, contrast and weather. Bigger, warmer targets are identified further out than small ones. Use identification range, not detection range, to judge what you can act on.
Does a 640 sensor see further than a 384?
Not directly. With the same lens and pixel pitch, a 640 mainly gives a wider, more detailed field of view rather than more raw range. Its advantage for range shows when paired with a longer lens or when using digital zoom, where the extra pixels preserve detail. Range comes chiefly from lens and pixel pitch; resolution supports it.
Does a bigger lens increase thermal range?
Yes — a longer focal length puts more pixels on a distant target, extending all three ranges. Going from a 25 mm to a 50 mm lens roughly doubles the pixels across your target. The trade-off is a narrower field of view, so you see further but through a smaller window. Lens size is the single most direct lever on range.
Does weather reduce thermal detection range?
Significantly. Rain, fog and high humidity absorb and scatter infrared, so the signal weakens before it reaches your scope. A range you’d achieve on a clear, dry night can fall sharply in heavy fog. This is a major reason the same scope gives very different range on different nights.
Why do two thermals with the same detection range perform differently?
Detection is the easiest figure to match, so two scopes can share it while differing in the things that set recognition and identification — lens, pixel pitch, NETD and image processing. One may hold a clear, identifiable image far further than the other despite an identical detection spec. Compare the whole picture, not one number.
Can I take a shot at a detected heat signature?
No. Detection, and even recognition, are not enough — you must positively identify the target first. The gap between “there’s something there” and “I know exactly what that is” is precisely where dangerous mistakes happen. Always identify before you act, and if you can’t identify it, don’t shoot.
What’s the best thermal for long range?
The one with the sensor grade and lens to match your needs, not the one with the biggest headline number. For reach, look for a fine pixel pitch (12 µm), a low NETD, and a longer objective lens, on a resolution that suits how you hunt. Understanding detection range means you can judge this for yourself rather than being led by a single spec.
Educational guide only. Detection range figures and calculator outputs are illustrative, based on a simplified Johnson-criteria model (detect/recognise/identify ≈ 2/8/13 pixels across the target’s critical dimension; pixels-on-target set by pixel pitch and focal length; range reduced by weather, low contrast and crossover). Real-world performance varies with target, conditions and equipment. Always positively identify a target before acting. Background: Johnson criteria (1958) and standard thermal range science.
The Ultimate Guide to Thermal Scopes in Australia
