Comparison - MrSID, JPG, JPG2000, GeoTIFF 24-bit and GeoTIFF 8-bit

There are times I wish to work with Landsat ETM+ imagery with attention to file size. Instead of 80 MBs of raster imagery, I would like to work with 4 MBs. Using Global Mapper Raster Image Export feature, I am able to get the imagery I need easily. The raster format I typically use is JPG2000. Let me share why.

Raster Comparison (1:300,000)

I did a comparison of different raster formats July 2007. My previous comparison was poorly constructed and explained. I always meant to redo it. So here it goes. The first composite shows a portion of a MrSID, JPG, JPG200, GeoTIFF 24-bit and GeoTIFF 8-bit. At 1:300,000 scale the images are visibly indistinguishable. One appears to be just as good as the other.

Raster Comparison (1:25,000)

At 1:25,000 scale, which is pushing the limits of the original image (MrSID format), the first 4 images are very similar in clarity. The GeoTIFF 8-bit image begins to lose color depth, as one would expect from 8-bit imagery as it uses fewer colors in its color palette.

Raster Comparison (1:8,000)

Raster Comparison (1:2,000)

Finally, lets push the images far beyond their intended usefulness. The three middle images, JPG, JPG2000 and GeoTIFF 24-bit are noticeably superior to MrSID and GeoTIFF 8-bit at this scale. It is at the 1:2,000 scale that pixel size difference shows up. The three middle images all carry the same sized pixels and range of colors. The GeoTIFF 8-bit image has the same pixel size as the middle images, but without the rich variety of colors. The MrSID image, our base image, has a larger pixel size. Its color palette is used to form the colors found in all of the other images.

Now for the kicker - size and number of files: MrSID - 80.4 MBs and 2 files; JPG - 21.5 MBs and 3 files; JPG2000 - 4.5 MBs and 3 files; GeoTIFF 24-bits - 121.8 MBs and 1 file; GeoTIFF 8-bit - 10.4 MBs and 1 file. Clearly, the JPG2000 packs the greatest image bang for your MBs. However, I understand that JPG2000 is not widely used. If you are able to use it, do so as it gives you quality imagery in a compressed package. If you are not able to use JPG2000 format and you do not require working at 1:50,000 or lower, the GeoTIFF 8-bit works quite well. I happen to prefer JPG as my second choice after JPG2000. At twice the size of GeoTIFF 8-bit imagery, it is still a reasonably sized file to work with in lieu of MrSID. GeoTIFF 24-bits is far too large compared to the other three raster formats. Last, but not least is the MrSID format. It is my base imagery. The four other raster images were derived from my Landsat ETM+ image in MrSID format.

Hopefully, this raster comparison is both informative and helpful. If nothing else, the raster comparison images are pretty slick composites giving you side-by-side visible examples of these 5 popular raster formats.

Enjoy!

How To Turn a Black Sea Transparent

Nisos Skiathos - LIIM with a Black Sea (1:90,000)

Let's begin with the LIIM of Nisos Skiathos. There are times I would like to switch off a range of colors or, for that matter, switch off any colors I wish to. I asked Mike at Global Mapper if a modification like this would be possible. He said that it seemed to be a fairly simple process and he would modify Global Mapper v9.0 to allow this color by color control.

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How To Create Transparent Seas

The process to switch a color or multiple colors off is simple. The image I used is a GeoTIFF 8-bit. Within the Overlay Control Center select the image and open it with Options. Select the Transparent feature and you will be given a palette of colors. This image contains 255 colors using the GeoTIFF 8-bit image option. Either use the shift-key to select a range of colors or the control-key and pick and choose any colors you want. I selected all of the colors that defined the black sea. Switching them off gave me the image below.

Nisos Skiathos GeoTIFF 8-Bit Transparent Sea (1:90,000)

Pretty slick, huh? The process to switch off the black sea and make it transparent took about 30-minutes to complete. I really like this feature. It allows for some pretty creative imagery analysis. For example, the burned area on Nisos Skiathos could be easy to isolate and study in greater detail.

Global Mapper's way of doing business - 1) Ask for a feature. 2) If it can be done, Mike will add the feature. If not, Mike will tell you straight up. 3) And the cost for the feature update - $0.

Enjoy!

How To Realign Misaligned Contours Using the "Eye-Ball" Method

Rapa Iti - NE Coast GeoTIFF Image False Color (1:10,000)

I have been working on a redo of Rapa Iti Island, using an exquisite, cloud-free GeoTIFF image, for the past month, an "on-again, off-again" project. I have completed the island's revised shorelines taking them from EVS precision to EEVS precision. That is from Enhanced Vector Shorelines using Landsat ETM+ base imagery to Extremely Enhanced Vector Shorelines using 1-meter resolution base imagery. The "zooming" capabilities of EEVS are pretty amazing. If you map it, one could zoom in to view your backyard which is in need of mowing.

Anyway, the revised Rapa Iti shoreline is finished. I still have a variety of vegetation layers to digitize, along with human ground signatures (dwellings, roads, paths, harbor features, etc). Before I tackled these challenging layers I thought I would quickly generate topographic contours. Using Global Mapper's "Generate Contours" routine, one merely needs to import the appropriate SRTM image for your area of interest, select a few options and one has contours generated in seconds. These contours, when SRTM is accurate and complete (no voids), accurately reflect the elevations of your target area. But, SRTM tiles often have little voids, which can be quickly filled using software tools (my personal favorite is SRTMFill) and in certain areas, big voids, which are difficult to reliably fill. After much thought, research and counting my money (I hate to spend money on pricey software), I decided to use a tried-and-true method "eye-ball-it". Any cartographer worth their salt cringes at this method. Too often, unscrupulous map-makers foist their finished product off as a rigorously crafted map following standard cartograph protocols, when, in fact, the map is more fiction than fact - none of which speaks kindly of the "eye-balling" method. However, since I do not have the means to obtain surveyed contour lines or modified SRTM data of my target island, I'll just "eye-ball" this portion of the project. This involves looking at the underlying land features and comparing them to accurate, reliable contours, guess-timating possible alignment of the various misaligned contour tracks (i.e., 20-meters, 40-meters, etc) and finally realigning them.

Rapa Iti - NE Coast Misaligned Contours Realigned (1:10,000)

Let's begin with Maputu Pt or the NE Coast of Rapa. Because the SRTM data was incomplete, containing a large void (no data or incomplete data), this point had contours that were spilling into the ocean.

Rapa Iti - NE Coast SRTM Base Image Misaligned Contours Realigned (1:10,000)

The above image shows the SRTM limits as a darker shade of green, when, in fact, the actual shoreline is west of the SRTM shoreline. Using the GeoTIFF image, I was able to realign the misaligned contours (see the blue contours). The method I used is "eye-balling". I looked at the shape of the easterm side of the point and beginning with the highest elevation, I realigned each contour level. The eastern side of Maputu Point appears to be quite steep, based on the GeoTIFF image and my contour realignments.

Rapa Iti - NE Coast EEVS Map with Realigned Contours Draped over SRTM Image using GM's 3D Effect (1:10,000)

Using Global Mapper's 3D Effect, I was able to see my work in a different, more revealing way. I think my "eye-balling" of the misaligned contours works quite well.

Rapa Iti - NE Coast GeoTIFF Image False Color (1:10,000)

From my GeoTIFF image to . . .

Rapa Iti - NE Coast EEVS Map Misaligned Contours Realigned (1:10,000)

Rapa Island, Maputu Point using EEVS precision (hi-res imagery). The green contours are generated from SRTM data. The blue contours are my realigned contours. They track the elevations more accurately then the SRTM based contours.

Rapa Iti - S Coast GeoTIFF Image False Color (1:10,000)

Rapa Iti - S Coast Misaligned Contours (1:10,000)

Along with the misaligned contours in the NE, another area of misaligned contours is along the southern shore. Looking at the GeoTIFF image without contours, one sees a coastline fronted by some pretty steep south facing slopes. Looking at the contours generated from the SRTM data, it is very easy to locate the problem contours. The steep slope is either poorly defined or nondefined by contours. Based on SRTM data, it appears the immediate shoreline is a very steep cliff fronting the shore. The contours do nothing toward resolving the remainder of the slope. Also the point that extends out is not defined.

Rapa Iti - S Coast EEVS Map Misaligned Contours Draped over SRTM Image with 3D Effect (1:10,000)

Looking at the contours draped over the SRTM image the reason for the misalignment is obvious. Where there should be elevation data there is none.

So I will carefully "eye-ball" the slope and assigned contours where I guess-timate they belong. You know and I know these realigned contours are nothing more than educated guesses. In the case of this map of Rapa and in consideration of the quality of the base GeoTIFF imagery, the educated guesses will ultimately lead to a good map that is useful to gather an understanding of the topography of this island. If I were to have actual contours that could be applied to this map, I could produce a high quality product useful for a wide variety of purposes. As it is, my map containing "eye-balled" contours will be a quality product useful for a variety of purposes.

Stay tuned. This project should be finished within the next few weeks. Then, you be the judge.

Enjoy!