Introduction
As an introduction to the specifications of this software and hardware, Dr. Hupy provided students with manuals that in detail describe the hardware and software used in GEM products. In essence, GEMs is a custom sensor intended for use in UAV applications . Along with these manuals, students were given questions intended to provide enough guidance to the point we would then be able to process imagery using GEMs products and actually be able to understand what is actually being created and review the products of the operations conducted.
GEMs Hardware
What does GEMs stand for?
GEMS stands for geo-locating and mosaicing system.
Look at figure 3 in the hardware manual and name what the GSD and pixel resolution are for the sensor. Why is that important for engaging in geospatial analysis. How does this compare to other sensors?
GSD: 5.1 cm at 400 feet - 2.5 cm at 200 feet
Pixel Resolution: 1.3 mega pixels
This information is important for geo-spatial analysis because how much ground is covered per pixel provides information of how large something must be on the ground in order for one to definitively identify what is they are seeing. Other sensors, like the Cannon SX260 HS, shoots images with 12.1 MP and has a GSD of 2.2 cm at 200 ft / 5 cm at 400 ft.
How does the GEMs store its data?
The hardware creates a Flight Data Folder per flight mission. That folder is than extracted by the software as a FlightData.Bin File. Within that file is the trajectory of the flight, metadata, and geo-acurate tiffs are stored. Being in the same file location makes it easy for the technology to run quick operations like mosaicing and NDVI initialization. All the files that are created from operations conducted in the software are also stored within the same FlightData.bin file.
What should the user be concerned with when mounting the GEMs on the UAS?
When installing the GEMS payload, it is imperative to do a number of things or there is a risk for damaging the hardware, or producing poor quality data. The payload should be mounted on the bottom of the plane, flat, at least 4 inches away from magnetic material (i.e. engines or batteries), and must be properly secured to limit vibrations. Also, the anetena should be wired so that they are away from any significant sources of EMI. One way to limit this interference on multirotors is wiring the antenna to be above the propeller rotors.
Examine Figures 17-19 in the hardware manual and relate that to mission planning. Why is this of concern in planning out missions?
Some of the concerns with mission planning are anticipating how GSD, image blurring, and amount of overlap are attributed from different mission planner variables. varying levels of speed and height require different degree of image overlap to create accurate mosaics. Going at a faster speed also increases the amount of movement distortion at lower heights. To create a full array of robust imagery, its important to understand your subject area and how much overlap will be needed to create a good product. 70% overlap is desired for quick stitching, but working with percents closer to 50% is possible if working with images containing distinct features that in each image that would assist in aligning the images. Doing missions over agricultural land, where the surface is relatively featureless, it would be more appropriate to employ a higher degree of overlap.
Write down the parameters for flight planning software (page 25 of
hardware manual). Compare those with other sensors such as the Cannon
SX260, Cannon S110, Nex 7, DJI phantom sensor, and Go Pro?
One thing that is apparent when comparing the specs of the other sensors like the Cannon SX260 or a GoPro is the lower level of picture quality. Many of these sensors twice the amount of pixels density on a larger sensor, meaning that there is both more pixels and each pixel is self is smaller. The SX260 for example had pixel size of 1.54 x 154 micro meters to the GEMs 3.75 x 3.75 micro meters.
One thing that is apparent when comparing the specs of the other sensors like the Cannon SX260 or a GoPro is the lower level of picture quality. Many of these sensors twice the amount of pixels density on a larger sensor, meaning that there is both more pixels and each pixel is self is smaller. The SX260 for example had pixel size of 1.54 x 154 micro meters to the GEMs 3.75 x 3.75 micro meters.
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| Table 1: Specs of GEMS and Cannon SX260 sensors. |
GEMs Software
Read the 1.1 Overview section. Then do a bit of online research and answer what the difference between orthomosaic and mosaic for imagery (orthorectified imagery vs. georeferenced imagery). Is Sentek making a false claim? Why or why not?An orthomosiac is a more advanced version of a georeferenced image. For an image to be referenced, each pixel must have an attributed x and y dimension, its only in one dimension. Orthomosiaced images are georeferenced in 3 dimensions, they have an associated z value for each pixel as well. According to the manuals presented by Sentek Systems, there is no sensor that is apart of the GEMs system that is able to collect a point cloud containing elevation data. The GEMs sensor only collects in visible spectrum and near IR. To create a Orthorectified image, one has to use software to combine georefrenced imagery with a digital surface model that was recorded with 3rd, separate sensor. Doing this allows for the data product to accurately extract precise sloping and distance information, which is impossible with a georefrenced image.
What forms of data are generated by the software?
The data generated by this software are images showing RGB, Near IR, NIR of the areas captured during a flight mission. Attributed to each pixel of these images, are 2 dimensional GPS coordinates.
How is data structured and labeled following a GEMs flight? What is the label structure, and what do the different numbers represent?
The files are saved under a labeling system comprised of GPS time syntax. The names generally look like this: (Week=(####) TOW=(######). Using a converter from the this sight, a file that looks like Week = 1862 TOW = 135349 would represents the standard dating/time system as 2015/09/04 6:35 and 32 seconds, Central Time. GPS time is a continuous, non-repainting counting system that counts weeks starting from January 5, 1980. the first four digits represent the number of weeks since that date and the digits after TOW (time of the week) represent the number of seconds that have passed since midnight of the previous Sunday.
What is the file extension of the file the user is looking to run in the folder?
The file saved under the GPS dating system is a .bin file.
Methods
What is the basis of this naming scheme? Why do you suppose it is done this way? Is this a good method? Provide a critique.
For the sake of organization, the first thing that will be done is changing the file names to the standard dating system. Using a converter from the, a file that looks like Week = 1862 TOW = 135349 would represents the standard dating/time system as 2015/09/04 6:35 and 32 seconds, Central Time. GPS time is a continuous, non-repainting counting system that counts weeks starting from January 5, 1980. Although this file syntax system has advantages for scripting, it is unlikely anybody seeing this timing method will be able to make sense of it in quick simple way like they would with a standard timing system. Employing this scheme is tedious outside of scripting operations because Sentek Systems does not provide any sort of conversion apparatus, and the one that is referenced above proved to be hard to find, it would be nice if they offered a conversion calculator of some sort.
Explain how the vegetation relates to the FC1 colors and to the FC2 colors. Which makes more sense to you? Now look at the Mono and compare that to the vegetation.
Figure 2: (Left to right) NDVI FC1 and NDVI FC2.
Given that that NDVI images pertain to vegetation health, the FC1 opption to me would make the most sense given its green to red scale. Green representing healthy vegetation, and red representing unhealthy vegetation or areas lacking vegetation, that color scheme translates well to the common sense that most people attribute to the what each color represents, if they know that the imagery is classifying varying levels of vegetation.
Figure 3: Display scale for Mono-chromatic images
Similar to the scale of the NDVI FC2 referenced in figure 3, the mono scale shows healthy vegetation in lighter shades and areas with unhealthy/no vegetation as darker.
Do these produce orthorectified images? Why or why not?
The two type of mosaics are fast mosaics and fine mosaics. The only difference between the two is that the fine mosaic performs additional computer vision image processing operations, and takes a little bit longer to process. Again, these are not orthorectified because they have not attributed elevation data.
Describe the quality of the mosaic. Where are there problems. Compare the speed with the quality and think of how this could be used.
The quality of the mosaics are good enough, but than could easily be improved if ran with fine mosaicing. It did not take long at all to run a quick Mosaic which poses an advantage for field for conducting field work. Provided you have a strong enough computer system, this running quick mosaics is possible in the field, allowing for the data to be check on site for quality and accuracy. Later on, fine mosaics could be ran to create a better product, which in itself does not take much longer than quick mosaics, especially when using a device where GPU processing can be enabled.
The only area where there is a little bit for distortion in the image are near the overlapping areas near the edge of the newly mosaiced image, where you see edge forming between the images composing the mosiac. There seems to be less of this issue in areas with more contrasting features, near the center of the mosaic.
Navigate to the Export to Pix4D section. What does it mean to export to Pix4D? Run this operation and look at the file. What are the numbers in the file used for?
Exporting the bin files to Pix4D allows the user to actually conduct orthorectification processes, if elevation data is available. Also, exporting a bin for Pix4D creates an excel table for NDVI FC1, NDVI FC2, Mono, and RGB. Each excel table contains the central coordinate taken when each image was taken in lat and long, as well as columns containing the Alt, Omega, Phi, Kappa values of each image. within these tables, it would be nice if each column was labeled so the viewer could know the what type of values they are looking at without having to refer to the software manual.
What is a geotif, and how can it be used?
A geotiff is an image that contains geographical accurate pixels, that is the picture itself, and each of the pixels, has an associated GCS x and y coordinate. This feature allows viewers to locate very accurately, in 2 dimensions, where a given feature is. The geotiff. file structure is completely open source, which it allows it to be opened up, imported, and operated on by a number of different software programs like GEMs, Pix4D, and Arcmap.
Go into the Tiles folder and examine the imagery. How are the geotifs different than the jpegs?
In comparison, viewing the image as a tiff vs. jpeg doesn't produce any noticeable difference. With that being said, the geotiff files are much larger than the jpeg files due to the geospataial data that is stored with the actual imagery.
Results
Using the Mono from the JEMs imagery folder, ice creates a panorama file of all the images you select (in this case, all mono images). The panorama was very smooth and showed no visible level of distortion that i could see. To the right of the viewer there are a number of projection options that allow you to alter the shape and orientation of the panorama in several ways. However, since this does not provide accurate coordinates for each picture/pixel, it is not a geotiff. It does however, allow for the use of combining JPEG images into one, high quality panorama. This could be useful for pure viewing purposes when just aiming to to create a high quality images by just combing jpeg taken during a flight.
Microsoft's ICE software allows users to make panoramas out of JPEG files taken during flight. after running NDVI operations, this can be done for the RGB, NDVI FC1, NDVI FC2, and Mono files that were created using the GEMs software. Although the output is not geolocated, it still created a very nice and seamless mosaic, as you can see in figure 4. One issue when creating these panoramas and exporting them as JPEGs is that the file size becomes too large to import into blogger, so the image you see below is a screenshot taken with snip-tool. because it is a screen shot, the quality of the image is lower than the original file created in ICE.
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| figure 4: Panorama created from Mono - RGB jpegs from UAV flight. |
To utilize the GEMs for its intended agricultural purposes, let us look at the the NDVI FC2 georefferenced mosaic and contrast it with the results obtained from the ICE software. Figure 5 below shows a map of the of the same area, but was created using fast mosaic operations in GEMs.
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| figure 5: Maps created from GEMs hardware and software |
GEMs Hardware and Software Conclusive Review
Although the sensors apart of the GEMs payload do not have the highest resolution, for the purposes of precision agriculture, its enough. The sensors are not designed to take high quality photographs that are able to produce aesthetic maps or diagrams, they are manly intended to detect varying degrees of vegetation species and health. The software and hardware is very simple, light, and easy for first time users to use without having a very deep understanding of remote sensing because the hardware and software are very intimately integrated. All it takes is a load and a few clicks and data product desired is produced with little to know user input.The GEMS sensor hardware is limited though because it does not have a very wide field of view, and thus requires that more paths be ran by a UAV in order to capture the full area of interest. This can be a problem when the device being used has a battery life of 30 minutes, it limits the amount of data one can actually collect. What is also missing from the software is the ability of it integrate point cloud data that would provide Z values which would allow for the creation of true Orthomosaics.
Overall, the software and hardware provided for GEMs is good enough for the application it is intended for, precision agriculture, but it lacks diverse applications that has become common place in modern technology. To vastly improve upon this platform, it would be wise to consider investing in technology that upgrades resolution of the image, and perhaps incorporating a sensor that can collect ground level z values, so that true orthomosaics can be made.
As a teaching tool, this software provided great insight on the basic operations that can be done one remote sensing data collected from a UAV platform, highlight how nice it is to work with technology that has highly integrated software and hardware.
Sources:
Sentek hardware and software manuals
GPS time converter: https://dominoc925-pages.appspot.com/webapp/calc_gpstime/
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