Types of Errors

Today, we'll dive into systematic errors in photogrammetry. Does anyone know what makes an error systematic?

I think it's when errors happen in a consistent way each time.

Exactly! Systematic errors are predictable and often stem from known sources, like lens distortion. Can someone give me an example of a systematic error?

Earth curvature can cause systematic distortion in measurements, right?

Great point, Student_2! Remember, systematic errors can often be corrected if identified. We can think of them as 'predictable problems.'

To help you remember, think of the acronym 'LEAD' for Lens distortion, Earth curvature, Angle of incidence, and Distortion types caused by systematic errors.

So, if we can correct them, they're not as worrisome compared to other types!

That's correct! They are manageable, but we must be aware of them.

In summary, systematic errors are consistent and predictable. We can correct them, unlike random errors, which we will discuss next.

Now, let's talk about random errors. What do you think causes them?

Are they due to things that happen by chance, like weather?

Exactly! Random errors can occur because of unpredictable factors, such as vibrations or atmospheric conditions. Anyone can think of a scenario?

If there was wind while capturing images, that could shake the camera!

Well said! Random errors can be hard to quantify and correct since they vary for each measurement. To remember this, think of 'RNO' - 'Random nature of occurrence.'

That helps! They seem trickier to handle than systematic errors.

Indeed! They are more challenging, which is why we need to consider them during planning.

To summarize, random errors come from unpredictable factors and can cause variability in measurements, making them the most notorious errors in photogrammetry.

Finally, let's explore blunder errors. What sets them apart from the others?

I think they are mistakes made by the operator, like placing GCPs incorrectly.

Absolutely correct! Blunder errors often arise from gross mistakes. Can you think of any serious implications of these errors?

They might lead to completely wrong data and results!

Precisely! That's why careful review and quality control are so important when working with photogrammetric data. Remember the phrase 'BAM' for Blunders Are Major!'

So it’s all about being meticulous?

Exactly! Careful planning and verification can save a lot of trouble.

In summary, blunder errors can happen due to operator mistakes and resolving them requires comprehensive checks of data and processing steps.