Data is not inherently geospatial. Some sort of coordinate system or projection makes the data geospatial. Without some sort of coordinate system, the data is merely that: data. Whether that is an image or an attribute table it is not geospatial if it cannot be located in space.
GIS data is different than a digital map for one main reason: attribute data. GIS is a smart map. It has information and data that accompanies the map or projection. A regular map is simply a map. It does not have any attached data or information or attribute table to do any sort of data processing or analysis from.
Having an understanding of geospatial concepts and fundamentals is important in working with UAS data because a lot of the data we collect with UAS is one sort of spatial data type or another. For example, taking images and creating a mosaic with an unmanned system is a form of raster data. Each pixel holds RGB information in the form of integers, which gives you color information. Also, digital surface models can be created from UAS data, which is floating point raster data that gives you elevation information. These are both spatial data types and are very common in UAS data.
This lab addresses key geospatial concepts such as projections and coordinate systems, as well as types of spatial data.
Part 2 (Methods/Lab Assignment):
Open the Tornadoes folder and find the Tornado_tracks files. List out each file with its extension.
TORNADO_tracks.dbf
TORNADO_tracks.prj
TORNADO_tracks.sbn
TORNADO_tracks.sbx
TORNADO_tracks.shp
TORNADO_tracks.xml
TORNADO_tracks.shx
Why is file management so key in working with UAS data?
File management is so key in working with UAS data because of this reason. As you can see in Figure 1, the file TORNADO_tracks has many various attribute files. Together, they make up the entire data set. File management is important because all of these files are necessary, and with so many files, it can be simple to misplace, mis-copy, or leave behind an important file.
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| Figure 1: Tornado_tracks files |
In ArcCatalog, a folder connection is made to make it easier to access the files you are working with. After a folder connection is made, you can easily locate and navigate to the files and data you are working with.
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| Figure 2: File layout in ArcCatalog |
Before when viewing the TORNADO_tracks file from windows explorer, we had an entire grouping of files that made up the data. Figure 2 shows that ArcCatalog groups together our data for us. Since ArcMap and ArcCatalog use all the files simultaneously, it makes sense that it would hide the attribute data and just show the shape file title.
Why is it so important, beyond maintaining proper file management/naming, to use Arc Catalog for managing your GIS data?
It is important to use ArcCatalog for managing GIS data to reduce the risk of losing a file. From the layout in Figure 1, it would not be that difficult to misplace one of those files, whereas with ArcCatalog, it organizes it and makes it less likely to lose anything.
What do those icons mean? Hint: Use the preview tab to view the file.
Those icons to the left of each file in Figure 2 give an indication of the type of data of which the file is comprised. For example, to the left of the states shape file, the symbol shows several shapes side by side, which indicates it is a vector polygon data file. To the left of the TORNADO_tracks files, it shows a line with some nodes on it, which indicates it is a vector line file.
List out each of the geospatial data types, and then provide an example file for that data type.
Vector data
Point: dams00x020.shp
Line: TORNADO_tracks.shp
Polygon: States.shp
Raster data
Integer: 20170613_wolfpaving_dsm.tif
Floating point: 20170613_wolfpaving_transparent_mosaic.tif
What topic/term relates to this description tab? Why is having this information so important in the UAS realm?
Another term that relates to the description tab is metadata. This information is important so other users of the data can have context to the data. They will be able to know the altitude it was flown, the resolution, the sensor and platform used, the weather conditions, and other such factors that could affect the data.
Right click on the 20170613_wolfpaving_dsm.tif raster, and then select ‘properties’. Scroll down to the statistics section. What does it say?
The statistics section gives minimum and maximum values, as well as average and standard deviation. For this specific file, the minimum was 281.047, the maximum 323.089, the average 296.967, and the standard deviation 4.178.
What types of tasks rely on statistics? Why would this information be important for data processing, analysis, and communication with the client? (Think of what was discussed in lecture/demo)
Tasks that rely on statistics are 3D projection in ArcGis, and further analysis of the data could rely on statistics as far as the deliverable to the customer. For example, with the dsm and mosaic of the wolfpaving, this information could be useful in calculating elevation differences, and areas of higher or lower elevation as far as drainage goes.
Cell Size: 0.02077
o Format: TIFF
o XY Coordinate System: WGS 1984 UTM Zone 16N
o Linear Unit: Meter (1.000000)
o Datum: D_WGS_1984
o Use the Linear unit and write the pixel size in square cm: 4.314 square cm
Referring to your notes from the demo/lecture, list out some different ways to add data.
Some ways to add data include dragging the file from the ArcCatalog menu directly into your layers, using the File>Add Data menu, or using the Add Data icon on the toolbar.
What basemap did you use? Why?
I used the topographic base map. There was not a specific reason for choosing this basemap, it did not matter a whole lot as I overlayed the states shape file above it anyways. I chose the topographic map above the others because it showed elevation changes. Depending on how I was viewing the data, I might have wanted to choose a streets map if I were viewing which cities the tornadoes potentially passed over.
Add the states.shp shapefile. What type of GIS data is this? Justify your answer.
The states shapefile is a vector polygon file. As visible in Figure 3, each state has a boundary line, and using the inspect tool, the state is the one selected and not the line, meaning that it is a vector polygon file rather than a vector line file.
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| Figure 3: Dams and tornadoes on states |
The TORNADO_tracks file is a vector line file. Each of the tracks is a line, and upon inspection, highlights and gives information about a particular line.
Go into the hydrofeatures folder, and add the dams00x020.shp file. What type of GIS data is this? Justify your answer.
The last data that is overlayed in figure 3 is the dams shape file. These data are represented by the diamonds on the image. This type of file is a vector point data file, as each dam is at one particular location, and using the inspect tool, it displays the attribute data behind each individual point.
Right click on the Tornado_tracks file, and go to properties, then click on the source tab. Write down the Coordinate System:
NAD_1983_UTM_Zone_16N
Now write the coordinate system for the other two data layers.
Dams: GCS_North_American_1983
States: USA_Contiguous_Equidistant_Conic
Are all of these coordinate systems the same? Why might that be an issue?
These coordinate systems are not all the same. This could be an issue because of differences in the projections. Both the tornado file and the states file are projected coordinate systems, and the dams file is a global coordinate system. The slight differences in coordinate systems could easily skew the data being analyzed, and not only that, if the datum is not the same between coordinate systems, you would have even further skewed data.
How might the need for metadata relate to coordinate systems.
The original coordinate system is needed just as much as metadata is needed to analyze data. If you are analyzing data that is projected on a different coordinate system, your interpretations will be wrong. If you are lacking metadata that shows altitude the images were captured at, it could be more difficult to put a scale to the image to properly use the data.
Think of some different types of attribute data that could be used in conjunction with UAS data and list it here with a use example.
Figure 4 displays attribute data associated with the TORNADO_tracks file. This data includes the date, time, state, F scale of the tornado, length, deaths, and other information that is associated with each individual line in the data. Other attribute data that could be used in conjunction with UAS could be wind information, temperature, humidity, and similar data that could influence or be used in the analysis of the data.
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| Figure 4: TORNADO_tracks attribute data |
What type of data is this?
The orthomosaic is raster data.
What is the format?
The format is TIFF.
What is the projection?
The projection is a UTM projection on the WGS_1984_UTM_Zone_16N coordinate system.
Add the XYWOLF_PAVING_UTM16_massaged.shp file.
What is the projection?
The projection is a UTM projection.
Does this projection match the Ortho? Why is this so important?
Yes this projection matches the orthomosaic. This is really important because this current file is the ground control points for the mosaic. These two files are very closely related, and if these projections did not match, the data would be worthless.
Zoom in over a few of the GCP points. Do the points line up with the markers on the ground?
These ground control points do line up with the markers on the ground.
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| Figure 5: Ground Control Point |
Measure several features on the map. How might this type of tool be useful in working with UAS data?
The measure tool could be useful for measuring distances between points of interest, or in measuring areas of the image that would be useful in data analysis.
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| Figure 6: Measuring tool |
The identify tool could come in handy in viewing the attribute data of a certain point or part of the file. Figure 7 shows the floating point value of a pixel in the wolfpaving_dsm file, which shows the particular elevation at that pixel.
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| Figure 7: Identify tool |
Figure 8 shows the swipe tool being used between the wolfpaving_dsm and the mosaic. This tool could be useful not only with these data types, but in others as well such as various spectrum images. This tool allows you to quickly swipe back and forth between two sets of data, allowing you to quickly compare and contrast areas of the data being analyzed.
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| Figure 8: Swipe tool |
Depending on the GIS user, UAS data could be very beneficial in the data analysis process and the production of a smart map. The data that can be collection through the use of a UAS is unique to other forms of data collection.
Some limitations that UAS data has includes limitations with resolution, whether that is from the sensor aboard the UAS, or the altitude that was flown. Other limitations include weather limitations. For instance, the wind conditions could affect the collection of data. The user should know about how the data was collected, especially through the use of a metadata file. The metadata will give useful information regarding the data and sensor package.
UAS data could be combined with ground station data such as other forms of surveying, or other ground sensor depending on the mission. For example, if a person is trying to analyze irrigation levels in a particular field, the sensor data could be combined with rain gauges on the ground as well as ground elevation surveying to form a more accurate 3D model of the field, potentially to better analyze drainage conditions.
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