G-faq–why is Bit Depth Important?

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For this month's geospatial frequently asked Question (G-faq), I pivot to a topic the deserves more attention than it get s, and that is bit depth. Some of heard this term when ordering imagery from Apollo Mapping or perhaps when downloading free Landsat da Ta without understanding its implications. As such, let's delve into this topic, addressing the following set of questions:

What exactly is the bit depth and why are it important when ordering satellite imagery? Is 16-bit imagery harder to work with? When should I order 16-bit imagery versus 8-bit depth?

To start of this discussion, it's important to understand the difference between base-10 and binary number systems. In a base-10 system, each digit place in a number represents possible the values from 0 to 9 and so each successive digit Place increases by ten-fold in its value. Let's look at the This mathematically:

Base-10 number = 123

This can is written mathematically as: (1 x 10^2) + (2 x 10^1) + (3 x 10^0)
which can simplified to: (1 x) + (2 x) + (3 x 1)
and final to: 100 + 20 + 3 = 123

Given our familiarity with math since the early days of school, creating base-10 numbers are something we do seamlessly as Opposed to writing out a mathematical formula as most beginners working with binary number systems do. In a binary system, each digit place is only have a possible values, 0 or 1. This mimics a computer chip which can either being off (0) or on (1) –and This is the reason so computers is based around Binary numbers at the system code level. So and let's see how a binary number is created mathematically:

Binary number* = 111 1011

This can is written mathematically using base-10 numbers as: (1 x 2^6) + (1 x 2^5) + (1 x 2^4) + (1 x 2^3) + (0 x 2^2) + (1 x 2^1) + (1 x 2^0)
which can simplified to: (1 x) + (1 x +) + (1 x +) + (1 x 8) + (0 x 4) + (1 x 2) + (1 x 1)
and final to: 64 + 32 + 16 + 8 + 0 + 2 + 1 = 123

* In binary numbers, your add a space every fourth digit to the left of the decimal place.

By following steps similar to what I present above, you can convert any binary number to Base-10–though going from base- Ten to binary involves more effort, check this website out for more details on those steps.

Now the We have explored binary number systems, we can pivot our attention back to bit depth. Satellites is based on binary numbers and as such bit depth is measured accordingly. The bit depth of a satellite tells you the maximum number of values it can measure per spectral band. The higher the bit depth, the more information it can measure and thus the more sensitive the sensor are to different illum Ination values (typically called digital numbers) of the surface of the planet.

As we explained in + Detail last month, a passive optical satellite measures the intensity of photons that is Reflected from the surface of our planet. Take for example-hypothetical satellites, one with 8-bit depth and the other with 9-bit depth. The 8-bit depth satellite can measure up to 2^8 digital number values (or all values) for the intensity of photon reflecti On While a 9-bit depth satellite can measure up to 2^9 values (or).

To look at this same hypothetical situation another, for each value an 8-bit depth satellite can measure, the 9-bit Depth satellite can measure the values. That means the 9-bit satellite are twice as sensitive in each of their spectral bands as is the 8-bit satellite. Now remember the most satellites offer at least 4 multispectral bands. As such, a 9-bit depth satellite can produce times the number of RGB + NIR values for each pixel in 4 band Multispectra L imagery than can an 8-bit depth satellite–this have important implications I'll discuss later in this G-faq series.

The table below shows the imaging characteristics of the most common satellite we work with and Then the maximum number of spectral combinations possible per pixel. The final column shows the increase in spectral information as related to a traditional 4-band, 11-bit depth satellite suc H as IKONOS. Can see from this table that increasing the number of spectral bands have a much larger impact on the maximum number of Spectral combinations than does bit depth.

It is important to note that rarely, if ever, would satellite imagery utilize the entire range of pixel values possible With its bit depth. Imaging companies such as DigitalGlobe make the conscience decision to ' dampen ' satellite systems, assuring that digital n Umbers close to the maximum possible (i.e. 2047 for 11-bit and 4095 for 12-bit depth) for each pixel is rarely reached. When the maximum value was reached and/or exceeded, flares can occur which destroy the spectral information in this pixel a nd surrounding ones.

Now that I has explained the basics, let's take a look at the bit-depth ordering options for satellite imagery. If you have ever placed a order with the Apollo Mapping for imagery products, your may has noticed that the both options for B It depth is 8 and, not one, or as in the table above. The reason for defining bit depth in increments of 8 ties back to computer technology. A single bit of information–either a 0 or 1–is memory ' s building block. Since the 1960s, it has been common practice for 8 bits-to-make up a single byte; So, 2 bytes is comprised of information.

As such, the binary digital numbers that is embedded in satellite imagery files (a TIFF usually) would either be 8-bits or 16-bits in length. In order to make one or 12-bit depth imagery digits (or bits) long, 0 ' is added to the front of the binary number so T Hat the value itself remains unchanged. When one or 12-bit depth data is delivered as 8-bit depth imagery, the values being scaled so, each 8-bit depth pixel Val UE represents multiple 11/12-bit depth values. Accordingly, 8-bit depth imagery would show less spectral variability. This 11/12-bit to 8-bit depth scaling process can also introduce additional signal noise. One term you might hear associated with 8-bit Red, Green, Blue (or Natural Color) imagery is 24-bits. They use the term as it is 3 spectral bands with 8-bit depth each, or 3 x 8 = 24-bit imagery.

In next month ' s edition of G-faq, I'll continue this discussion on bit depth by looking at the advantages and Disadvanta Ges of 8 and 11/12-bit depth imagery as well as provide recommendations on if to order each.

Until our next edition of G-faq, Happy gis-ing!

Does you have a g-faq? If So, let me know by email at [email protected].

Find out more about this Topic here:

• Indiana University-knowledge Base
• Penn State University-chapter 8:remotely sensed Image Data
• Regional and Mesoscale Meteorology branch-effect of Bit Depth on GOES Images

Brock Adam McCarty
Map Wizard
(720) 470-7988
[Email protected]

G-faq–why is Bit Depth Important?