As a producer of moderate resolution land cover data, I am often asked questions about the spatial resolution of our data.  I have gotten used to the fact that 30 meter pixels of our C-CAP data are not always seen as ultra-sexy and the reaction that they “are not good enough.”  And they aren’t in some instances, but then again, sometimes they are (and sometimes it doesn’t matter, as they are the only/best thing available).  What I tell people, though, is that the resolution itself isn’t enough to determine whether these products are good enough or not.  I tell them there are two other key pieces of information to consider: 1) what is the Minimum Mapping Unit (MMU) of the product (or what is the smallest feature that is being reliably mapped)? And, 2) what is it you are trying to map? 

Minimum Mapping Unit:

There are two ways to think about MMU:

1. What is technically possible based upon the image data that the land cover is being derived from?
2. What is reality based upon the methods and techniques used in producing that product? 

The smallest possible feature that could be mapped would be equal to one pixel.  For a 30 meter image source this would be 30 meter by 30 meter area (or approximately 1/4th of an acre).  For a one meter image this would be a 1 square meter area. But, it is generally agreed that the smallest observable feature that can reliably be identified would need to be four contiguous pixels in size (60 by 60 meters or 2 by 2 meters, respectively for the examples above). This is because a quarter-acre-sized feature may not fall entirely within one given pixel but may instead be split among as many as 4 pixels, therefore making up only a minority of any one of those pixels and not being the dominant feature reflected in any. 

Many products (especially those derived from higher resolution imagery) are not based on individual pixels.  These products are often based on polygons derived from the imagery in some way (use of image segments / object or manually derived through photo-interpretation / heads-up digitizing).  When this is the case, this reality trumps what might have been possible based solely on pixel size. 

In reality then, you could end up with a land cover product that while derived from higher resolution imagery, may have a less detailed MMU then that possible.  If this is the case, small linear features and the boundary line between features may be mapped in more detail, but the size of smallest general features mapped would not necessarily be better. 

The tipping point for this comparison between higher resolution and moderate resolution might be approximately 1 acre (i.e. the area approximately equal to four 30 meter pixels, as discussed above).  If the high res data aren’t resolving more detail than that, then you would be highly likely to see these same features in a moderate resolution product as well.

The figure on the right (top) is an example of a land cover data set developed from digital orthophotography with a 0.25 meter pixel resolution and a minimum mapping unit of 0.25 acres.  Note the similarity of most features to those seen in the corresponding 30 meter land cover product (seen below it).  You may also note that there is some added detail in the linear tidal creeks that are mapped as water in blue.

 So, what are you trying to map?

Or more to the point, how big is it?  Smaller than the MMU?  As the mob would say, “fuhgeddaboudit (forget about it),” or at least it isn’t going to be likely. You just can’t map what you can’t see.  Bigger than the MMU?  Don’t worry, be happy…  at least until you turn to consider the accuracy of the product…  but that is detail for another time.

FOOTNOTES:

* For products that are not based solely on pixels, the Minimum Mapping Unit should be clearly defined and included as part of the metadata.  

**For pixel based products, you can determine the appropriate resolution necessary for your applications based upon the smallest feature you want to resolve (i.e. MMU).  The pixel size must be half the smallest dimension of the feature in question. For instance if you want to find a car (which would be ~10 feet  x 6 feet), then the smallest dimension of that car is 6 feet, so your pixel size must be no larger 3 x 3 feet to reliably identify and map cars.