GEMs Software Review

This week I will be providing a review of the GEMs software used to develop maps from the data collected in the previous weeks with the corresponding hardware on the multi rotor.

Overview of Software:

The GEo-location and Mosaicing software or GEMs is a used in the compilation of images gathered by the GEMs hardware mounted on a fixed wing or multirotor aerial photography platform. The hardware consists of a multispectral sensor that can collect images in color (RGB), near infrared (NIR) and several forms of normalized difference vegetation index or NDVI. This system was specifically designed to aid in agriculture since the main role of the NDVI imagery is to identify the health of crops and pinpoint any problem areas in a field such as malnourishment or bug infestations. When mounting the hardware to an aerial system it is important to point the antenna away from all magnetic objects or other antennas this will aid in preventing any extraneous signals from disrupting data collection. Adding a copper plate beneath the GEMs will help to act as a faraday cage which will essentially absorb or and eliminate any electronic interference.  It is also important that the hardware mounted facing downwards in a location were vibrations are minimal or dampened to improve image and data quality. As the mission is being flown, data is collected on a SanDisk Extreme 32GB storage device which is able to write data at 100MB/second. The GSD or ground sampling distance is a relationship between the area covered in a pixel at a certain height. For the GEMs the GSD at 200 feet is 2.5 cm and at 400 feet is 5.1, which shows that the relationship between sample height and GSD are near linear. Pixels can also be geo-located to within 1.5 centimeters with field markers at best and without markers between 3 and 5 meters. The sensors are programmed to enhance a variety of parameters such as rate of coverage, field of view, platform altitude, platform velocity, image overlap, percent smear, exposure time and GSDs. These automatic adjustments are invaluable as they save a lot of time in the image collection since you won’t have to worry about doing calculations in the field to measure out these values. At the conclusion of a mission using GEMs, the GPS coordinates are automatically associated with an image for each of the three image types and an orthomosaic is created. The GEMs software allows for two different types of processing when creating a mosaic, which is the compilation of all the images formed into one geo-located image. These processing types are fast and fine mosaicing, where a fast mosaic will be a quickly processed image based on the navigation data corresponding to the individual images and fine will process the image more in depth ensuring proper alignment of the images and creating an overall better quality mosaic. 

GEMs hardware can be used with different software (such as Mission Planner as was used in our class), and if that is the case the following information can be used to ensure successful data collection.

• Image sensor resolution: 1280 x 960 pixels 
• Sensor dimensions (active area): 4.8 x 3.6 mm 
• Pixel size: 3.75 x 3.75 μm 
• Horizontal Field of View: 34.622 deg 
• Vertical Field of View: 26.314 deg 
• Focal length: 7.70 mm 

Using the Software:

To analyse the data previously collected using the GEMs hardware, the imagery data was uploaded onto a computer interface and a file was created to isolate the data for a particular mission. When in the folder, the data is automatically named to represent the time and date that it was collected. This is a useful feature so you can keep track of your images. The data was then able to be uploaded to the GEMs software where the fisrt step is to initialize the NDVI data. This step besides the part where you click the 'Run NDVI initialization' button is automatic and a loading bar will pop up to show you the status of this initialization. Following that, the data was ready to be sent to a program called ArcMap where the data can be visualized and a map can be created. The files that we want to use in ArcMap are called .tiff files which are created when the NDVI data is initialized with the GEMs software. TIFF is a file format that is used to store raster graphics which contain data relating to the color of a pixel. This is important for NDVI images because the color of a pixel determines the health of a that area of vegetation which is the whole purpose of collecting NDVI imagery.

Speaking of pixel colors, here is how pixel color relates to image type:

• RGB Image: Each pixel contains a certain percentage of Red, Blue or Green which related to color of the image as it pertains to the visible light spectrum
• NIR (Mono) Image: This is imagery taken near infrared, this imagery is interpreted in such a way so that you can see it since we biologically cannot see in infrared. 
• NDVI FC1:  Here, the darker orange the pixel, the healthier the vegetation, bad vegetation is dark blue to black in color
• NDVI FC2: This imagery displays healthy vegetation as green and bad vegetation as red.  In this situation, green is good and red is 'dead' an easy scale to visualize. 
• NDVI Mono: Here the more white a pixel, the healthier it is. A black pixel would indicate very unhealthy plant life.

Another form of TIFF file is a geoTIFF which allows georeferenced data to be embedded withing the TIFF file. You can probably understand why this would be important if you want to use your imagery for mapping. In ArcMap these geoTIFFs are used to place your image on an underlaying base map of the world, a feat almost impossible if you don't have any geographical reference points. Other image types such as a .jpeg are not automatically geotagged and therefore whould cause problem if you wanted to create a map with them. One thing the GEMs software will not automatically do is update the metadata associated with your imagery. To combat this it is important to keep a good record with you metadata so that others viewing your data will have an easier time interpreting it and understanding where it came from.

Summary:

With this being my first time analyzing data using the GEM software, it was a bit intimidating at first. Luckily a lot of the data analysis was done automatically making the process a little more streamlined and easier for a first timer like myself. The resulting processed imagery was good, but I am unsure whether it was the software or just the images, but in the NDVI imagery you can clearly see distortions that make the imagery at those points less than ideal. Given, it does a lot better of a job than I could do manually that is for sure. This equipment does not come cheap however and is near $8,000 to obtain the hardware alone, which I would consider a downfall for the technology for those who want to use GEM for individual use and don't have a large budget. Overall I would rate the GEMs as good, but there is still room for improvement.