Use of the GEMS Processing Software

Geo-location and Mosaicing Systems (GEMS) is a hardware and software package initially designed for an Unmanned Aerial Systems (UAS) precision agriculture application. For that reason, the agricultural multispectral sensor optimizes certain parameters: coverage rate, field of view, percent smear, platform altitude and velocity, image overlap for efficient mosaic-ing, frame rate, exposure times and ground sampling distance (GSD). With these parameters the hardware captures RGB, Near -Infrared (NIR), and Normalized Difference Vegetation Index (NDVI) imagery and pixel GPS coordinates in a single flight. Software automatically stores sub-images and is able to generate RGB, NIR, and NDVI mosaics and “geo-locate” images. In this assignment I will review the GEM software and hardware model and assess the quality of GEM software outputs.

Figure I: Here is the GEM workflow taken from the software manual. From 

platform to computer.

Hardware Integration Manual

The Hardware Integration Manual is used for mounting the sensor and assembling connections to the platform. It also discusses important camera parameters that could affect type of platform and flight time.  For instance, Ground Sampling Distance (GSD) (Figure II) is used to determine the scale of a photo by finding the ratio between the camera’s focal length and the plane’s altitude above ground level (AGL). For the GEMS sensor the GSD is 5.1cm at 400ft (altitude), or 2.5cm @200ft (altitude). Camera resolution is 1.3MP RGB and 1.3MP Mono this equates to 1290x1024 pixels for the dimensions of a single image.

Figure II: This image shows how focal length is affected by altitude. 

More information about Ground Sampling Distance.

Image Sensor Resolution: 1280 x 960 pixels
Sensor Dimension: 4.8 x 3.6 mm
Pixel Size: 3.75 x 3.75 μm
Horizontal Field of View: 34.622 degrees
Vertical Field of View: 26.314 degrees
Focal Length: 7.70 mm

It is stated that flying lower and slower will give you a finer resolution on the ground (smaller GSD) while flying higher and faster increases your coverage rate. So there is a natural trade off. This is important when planning a mission based on the area of interest. If there is a larger area to cover flying slower and lower with a multirotor is not recommended because the battery will drain faster. Because flying lower and slower decreases the field of view the distance for line spacing (ensuring overlap) will decrease. In the case of a large study area it is recommended to fly higher and faster with a fixed wing (maybe even a multirotor) to collect data. Your mission will also be affected by the type of sensor you use, the pixel resolution, and the GSD. These will also affect flight time, height, and speed appropriate to your study area and thus affect the type of UAV you use.

Software Integration Manual 

The software Integration Manual  is used to help navigate the software graphical interface (GUI) used to view and manage flight data. When data is downloaded from the jump drive flight data is labeled by Week (X), TOW (H-M-S). These numbers specify the instant data collection began for the specified flight.

X = week
H = hours
M = minutes
S= Seconds

This labeling system can be easily used when using PyScriptor as these numbers can never be repeated and they are easy to enter within a script. Otherwise there are online converters that can help translate the label into common time. Here are some online sources that can help convert or understand GPS time stamps: GPS Time Calculator, GPS Calander. 

Data is uniquely stored in BIN files that will be overlaid on satellite imagery. There are different imagery outputs once a mosaic is built: NDVI-FC1, NDVI FC2, NDVI-Mono, RGB, and RGB-Mono. The NDVI FC imagery is differ by color schema - each using a different color scheme to display the health of vegetation. The RGB imagery is used for high resolution imagery that displays greater detail then ESRI satellite imagery.

A Quick Software Run-through!

Here I will illustrate a simple software use demonstration so that you can better understand how the GEMS software is used. I will then also use the Microsoft Image Composite Editor (ICE) software and preform a quality assessment between the two mosaicked images.

Upon opening the GEMS window you are prompted to select a BIN file (flight data) you wish to use. Again, these are labeled based on the GPS time that was attached when data was first collected. First, click the "Run" tab and select "Run NDVI Initialization". This will yield imagery for NDVI-FC1, NDVI-FC2, and NDVI-Mono. These show the vegetation health using different color schemes to express Near Infrared values. Next, a select the Run" tab again and select "Generate Mosaics." For Fast Mosaic Mode simply check the first two boxes (Shown in Figure III). For a better quality mosaic be sure to select "Preform Fine Alignment" for the Fine Alignment Mosaic Mode. This will generate tiles and mosaics. 

Figure III: Here, the type of mosaic can be specified based on the "Preform Fine Alignment"
check box. Checking it will yield a better quality mosaic, but it takes more time and computing power. 

Data can be viewed within the GEMS software, however it is best to view the geotiffs (georeferenced image) within other software such as ArcMap or Pix4D where upon it can be manipulated, and geographic map elements can be added (title, author, date, data source, legend, scalebar, north arrow: see my first blog for more details). To do this, export the images under the "Tools" tab to Pix4D. These images can be found in the Tiles folder within the flight data folder.

For comparison, I also stitched the images in Microsoft Image Composite Editor (ICE) to examine the differences between the software. This software is easy to use and can be done in 4 simple steps: Import the selected, individual images (Figure IV), Stitch the images, crop the stitched image, and then export it. 

Figure IV: Above the four steps can be seen in the top center of the image. This step is highlighting the importing of images to be stitched together. 

Microsoft ICE (here is a website showing a simple task such as creating panoramas: Stitching Images) 

Results

There are different software that are able to mosaic or stitch imagery and each can produce a different product. Some may be better aesthetically pleasing but less accurate in terms of latitude and longitude location if they even have that data at all. Some products may produce large file sizes as well that can't always be transferred or exported - for instance my Microsoft ICE stitched images were too large. 

Figure IV: Here are maps of images I processed Fall semester, 2015. Flight data was collected over a soccer field and pavilion to detect changes in vegetation health.  

Figure V: Here is the imagery produced from the community garden imagery in Eau Claire. It is similar to the soccer field imagery except that there is more vegetation variation (Trees, garden plants, grass, dirt, pavement). 

Figure VII: Here is a stitched image produced in Microsoft ICE. This imagery is high resolution and the software does a great job stitching is together. Overall it is a very smooth image.  

Conclusion

GEMS Exports

It is apparent in the NDVI and mono imagery that there are some image overlap issues ( the side walk doesn't always line up with the base map imagery and there are blotches across the image. Regardless, the NDVI-FC1 shows ware on some of the soccer field (North of the pavillian) where most of the players run. While it can also be seen in the NDVI FC2 and Mono, it is best expressed in the NDVI FC1 color scheme. However, this scheme can seem counter intuitive as most people associate green with healthy indicators of vegetation, and red as unhealthy. Hence there are two different NDVI color schemes. 

Microsoft Ice Products

This is a freeware that I think offers an amazing high resolution product. It is easy to use and doesn't take too long - depending on the number of images you are using. However, I could not export my image as the software crashed for unknown reasons. The end result is not geo-referenced and should be used purely for image display purposes.

Data Talk

While the GEMS software is user friendly the images produced are not orthorectified as they claim. Instead the images are georeferenced. Unlike orhtorectified images or orthomosaics, georeferenced images are not tied down to the earth via X,Y, and Z (elevation) planes. An Orthorectified image has unified scale across the whole image. A DEM is required to orthorectify an image, and better yet Ground Control Points can also be used to accurately tie an image down. It is also important to note that JPEG files have no geographic information tied to them and should not be used when spatially analyzing imagery. 

Software Analysis

Overall, the GEMS software is easy to use. It was designed with precision agriculture in mind as the sensor generates NDVI imagery. You don't need a geography degree to be able to use the software. With that in mind though there are terms that GEM is using that aren't accurate and that some folks without a geography background might not understand. I am of course referring to georefernce vs. orthorectified imagery. For what the software is disgined for I think it works perfectly. However, there are other software that we will explore this semester that offer more accurate imagery.

Sources:

Georeferences vs. Orthorectified Georeference, Image Registration, and Orthorectification