Global Navigation Satellite Systemswebspace.ship.edu/sadrzy/geo420/labs/GIS3_Lab_GNSS_QA_QC.pdf ·...

Read everything before doing anything! Visualize your final product. 1

LAB: Global Navigation Satellite Systems

Introduction Bolstad (2016: p203-209) We know that GIS is a class of technology that’s used to store, analyze, visualize and share the locations and properties of landscape entities and fields. Well, a Global Navigation Satellite System (GNSS) is a related class of technology that’s used to measure time and position, to record other observations, and to assist navigation and tracking. Many geoenvironmental projects involve both field work with GNSS and office work with GIS, so it is useful to learn how to leverage both technologies.

GNSS devices (satellite signal receiving hardware and data logging software) come in three grades: recreational, differential, and survey. Recreational grade devices (e.g., mobile phones and pocket receivers) are typically hand-held devices that were designed for waypoint marking, place finding, and geotagging; they can, under the very best conditions, make repeated horizontal coordinate measures with ±3 meters of precision. Differential grade devices have larger antennas, better hardware, and better software. Coupled with post-processing software, differential grade devices can make repeated horizontal coordinate measures with sub-meter precision. Survey grade devices are the state-of-the-art. They can make repeated horizontal coordinate measures with ±1 centimeter of precision in real time. We’re going to learn how to use differential grade Trimble GeoExplorer3000 devices and GPS Pathfinder Office (v5.8) software.

Geospatial data can be exchanged between Trimble GNSS and Esri GIS software because both vendors recognize the WGS84 geographic coordinate system and both adopted the same data format standards (e.g., ASCII text, Esri Shapefile, etc.). In other words, we can exchange data easily between them because both adopted the same geospatial standards (interoperability). The practical problem The Department of Art & Design at Shippensburg University has installed several durable pieces of art around campus.1 Unfortunately, there’s no resource online (or in print) that lets the SHIP community or campus visitors know how many pieces of art are installed, where they’re installed, who made them, or what they’re about. As geographers with mapping skills, we can remedy this problem by using Global Navigation Satellite Systems (GNSS) to help us build a Geographic Information System (GIS). Purpose The purpose of this exercise is to build answers to four research questions:

Where are the campus art pieces located? And, what properties does each have?

Where are survey marks located on campus? And, on average, how closely do the coordinates that we measure at these marks match the actual coordinates of these marks?

Just because we can Since we’re going to be in the field anyway, we can gather a little more data that helps us to learn more about how GNSS technology work.

How long is the track that surrounds the Student Recreation Complex?

Where are the Pokémon GO sites (e.g., gyms) on campus and what properties do they have?

1 I’ve been told that many campus art pieces on campus serve as Pokéstops.


Objectives To accomplish our purpose, we need to develop a workflow that assures the data we collect are accurate, consistent, and complete. Bolstad (2016: p617-624) Before collecting any data, we need a plan:

1. Perform mission planning to identify the blocks of time when GPS satellite-receiver geometries are optimal;

2. Identify the vector feature class (point, line, or polygon) that is most appropriate for representing each entity class (artwork, survey mark, track, etc.);

3. Identify the attribute data type that is most appropriate for storing each measured property.

While in the field: 4. Conduct your coordinate and attribute surveys with good equipment and during the

good blocks of time you found during mission planning. Back in the lab:

5. Post-process the raw data to differentially correct the positions that support each feature; 6. Export and map your acceptable results; 7. Assess the accuracy of your data by comparing actual mark coordinates and measured

mark coordinates (projected, of course) and calculating an RMSE statistic.

Quality Assurance (QA) methods, Part 1 Quality Assurance is an industry term that refers to a workflow that is designed to ensure outputted data, calculated quantities, or their derivatives (e.g., maps or graphs) meet predefined “quality” thresholds. A quality assurance workflow differentiates acceptable work from unacceptable work. Client demands or industry standards typically dictate what is acceptable. The QA process for this lab involves: understanding the difference between GNSS features and their supporting positions (lecture and textbook material); mission planning; preparing to collect data by building a data dictionary; collecting data with good equipment; fixing raw coordinates; and exporting GNSS data for use in GIS software.

Step 1. Perform mission planning. Bolstad (2016: p203-213) Anyone who’s used a car navigation system or a cell phone with GPS knows that your ‘blue dot’ sometimes gets plotted at the wrong spot. That’s because those devices are designed to measure positions quickly, but some field conditions are better than others. Mission planning is the process of predicting when the satellite constellation above your work site will be suitable for collecting reliable GNSS data. Visit the Trimble GPS Data Resources page (link below) and open the GNSS Planning Tool, which will help you to identify blocks of time when GPS satellites-receiver geometries will be optimal.

http://www.trimble.com/GNSSPlanningOnline/

Use the Settings tool to set the latitude and longitude of our AOI. Pick… a spot on the SU campus - any spot will do. Next, assume an average land elevation of 200m and a 10˚ cutoff above your local horizon. Next, choose: the date you will to do your field work, your expected start time, and a 24 hour time span (Eastern Time zone, of course). Apply these choices.




Use the Satellite Library tool to uncheck the Glonass, Galileo, BeiDou, and QZSS fleets, and any unhealthy (x) GPS satellites. We’re going to use healthy GPS satellites only.

Use the Sky Plot tool and the slider bar (lower right corner) to visualize how the GPS satellites are expected to pass over your work site and local horizon.

Use the Number of Satellites tool to identify the blocks of time when the most and fewest satellites will be above your work site and local horizon.

Next, examine the DOPs (see Figure 5-12 in Bolstad ,2016: p213). Take notes regarding the time frames when the PDOPs will exceed 3.0. You want to avoid doing GPS work during these blocks of time.

Last, use the Iono Map tool and slider bar (lower right corner) to visualize the field of electrons that is expected to disturb the ionosphere and, hence, GPS satellite signals.

Question 1: Report the settings you choose as well as each ‘bad’ block of time (start time and end time) when PDOPs are expected to be greater than 3.0. Remember, you want to avoid doing any GPS work during those bad periods.

Steps 2 and 3. Think carefully about what needs to be mapped and what needs to be measured. Begin a session of GPS Pathfinder Office and setup a New… project named Shippensburg. Direct the Project Folder: to either your T: drive; the C:\Geotemp folder; or a workspace on your external memory device. Next, use Trimble’s Data Dictionary Editor utility to help you think about each entity class we want to map and to think about the attribute data types that are most appropriate for storing measured properties. Create a data dictionary called ShipArt_<your initials>.ddf and save it in your folder.

1. Name: ShipArt_<your initials>

2. Comment: Fall 2016

3. Version: TerraSync v5.00 and later

4. Create a New point Feature… called Art with the following settings and symbol: a. Select a 1-second position logging interval; b. Set a minimum of 120 positions needed to support each piece of art; c. Choose a green, 20-pt, and artsy-looking symbol; d. Next, create New Attributes…

i. Text attribute 1. Name: Title 2. Comment/Alias: What is this piece called? 3. Length: 48 4. On Creation: Required 5. On Update: Normal

ii. Text attribute 1. Name: Artists 2. Comment/Alias: Who created it? 3. Length: 48 4. On Creation: Required 5. On Update: Normal

iii. Text attribute 1. Name: CYear


2. Comment/Alias: In what year was it created? 3. Length: 4 4. On Creation: Normal 5. On Update: Normal

iv. Menu attribute 1. Name: Photo 2. Alias: Did you take a picture? 3. Menu Attribute Values:

a. New i. Attribute value: Yes

ii. Default: checked iii. Code Value 1: 1

b. Add i. Attribute value: No

ii. Default: unchecked iii. Code Value 1: 0

4. Display in Field As: Radio Buttons 5. On creation: Required 6. On update: Normal

v. Text attribute 1. Name: Caption 2. Comment/Alias: Photo caption? 3. Length: 36 4. On Creation: Normal 5. On Update: Normal 6. Condition: [Change]

a. Enable condition: checked b. If this condition is true: “Photo is No” c. On creation: Not Visible d. On Update: Not Visible

vi. Text field 1. Name: Comments 2. Comment/Alias: Open ended comment. 3. Length: 36 4. On Creation: Normal

5. Create a New point Feature… called Mark with the following settings and symbol:

a. Select a 1-second position logging interval; b. Set a minimum of 120 raw positions to support each survey mark; c. Choose a black 20pt triangle symbol. d. Create New Attributes… for your Mark feature class.

i. Menu attribute 1. Name: SMID 2. Alias: Survey mark ID? 3. Menu Attribute Values:

a. New i. Attribute value: SM001



b. Add i. Attribute value: SM002


c. Add i. Attribute value: SM003


d. Add i. Attribute value: SM004


e. Add i. Attribute value: SM005


f. Add i. Attribute value: SM006


4. On Creation: Required 5. On Update: Normal

ii. Text field 1. Name: Comment 2. Alias: Open ended comment. 3. Length: 36 4. On Creation: Normal 5. On Update: Normal

6. Create a New point Feature… called Pokémon with the following settings and symbol:

a. Select a 1-second position logging interval; b. Set a minimum of 120 raw positions to support each game place. c. Choose a 20pt yellow-colored symbol. d. Create New Attributes… for your Pokémon point feature class.

i. Menu attribute 1. Name: Place 2. Alias: Type? 3. Menu Attribute Values:

a. New i. Attribute value: PokéStop


b. Add i. Attribute value: Gym

ii. Default: unchecked


iii. Code Value 1: 2 c. Add

i. Attribute value: Other ii. Default: unchecked

iii. Code Value 1: 99 4. On Creation: Required 5. On Update: Normal

ii. Menu attribute 1. Name: Items 2. Alias: Found items? 3. Menu Attribute Values:

a. New i. Attribute value: Egg


b. Add i. Attribute value: Poké Ball


c. Add i. Attribute value: Other


4. On Creation: Normal 5. On Update: Normal 6. Condition: [Change]

a. Enable condition: checked b. If this condition is true: “Place IS NOT Pokestop” c. On creation: Not Visible d. On Update: Not Visible e. Value to assign: NA

iii. Text field 1. Name: Owner 2. Alias: Gym owner. 3. Length: 36 4. On Creation: Normal 5. On Update: Normal 6. Condition: [Change]

a. Enable condition: checked b. If this condition is true: “Place IS NOT Gym” c. On creation: Not Visible d. On Update: Not Visible

iv. Text field 1. Name: Comment 2. Alias: Open ended comment. 3. Length: 36 4. On Creation: Normal


7. Create a New line Feature… called Track with the following settings and symbol: a. Select a 1-second position logging interval; b. Choose a line symbol to represent a track; c. Next, create New Attributes… for your Track point feature.

i. Numeric field 1. Name: Loop 2. Alias: 3. Decimal places: 0 4. Minimum: 1 5. Maximum: 100 6. Default: 1 7. Field Entry > On Creation: Not Visible 8. Field Entry > On Update: Not Visible 9. Auto-Incrementing: Increment 10. Auto-Incrementing > Step Value: 1

ii. Text field 1. Name: Comments 2. Comment/Alias: Open ended comment. 3. Length: 36 4. On Creation: Normal

Save your data dictionary file (see Figure 1) and close the editor.

Next, obtain a Trimble device and insert it into the cradle. Turn on the device (green button). On the workstation, Microsoft’s Mobile Device software should recognize the device and open a port for communication. When prompted, choose “Connect without setting up your device” (we’re not trying to sync music libraries or anything like that).

Next, open Trimble GPS Pathfinder Office’s Data

Transfer utility and connect with the GIS Datalogger on Windows Mobile device (if it hasn’t already done so). Next, add your data dictionary file to your send list, then transfer everything on the send list to the Trimble device. Close and Exit.

Figure 1. Snapshot of a completed data dictionary.


Step 4a. Start your survey of art pieces, survey marks, tracks, and game places. Before beginning any field work, make sure you are prepared with suitable clothing, water, and sun protection (e.g., a hat, sunscreen, etc.). Expect to be outside for a few hours, so plan accordingly.

Next, go to the GIS Lab, grab the Trimble you prepared, and go outside. Start GPS /

TerraSync (Professional). TerraSync is data collection software that works with the receiver antenna (the domed part of your device) and can read satellite signals. It can take several minutes to ‘lock’ onto all the GPS signals that are above your local horizon. Be patient.

On open, TerraSync will display its Status window, which looks similar to the Sky Plot graph you reviewed during mission planning: you are at the center, the circle represents your local horizon; and the box symbols represent the GPS satellites, by PRN, that are in the volume of space above your horizontal circle.

Next, choose the Map option from the pull-down menu, which will attempt to draw a map centered at your location. Follow the Layers > Background Files… path and check ‘on’ the MobileCampusMap.TIF file. It might take a moment for the map to load.

Next, choose the Data option from the pull-down menu, which will let you select your data dictionary: ShipArt_XYZ. Data file names are generated automatically: the prefix is usually the letter “R” (R for rover); the next two digits indicate the month (“09” for September); the next two digits indicate the day of the month; the next two digits indicate the hour of the day (on a 24-hour clock); and the suffix is usually a letter that auto-increments (from A, to B, to …, Z). Be sure to choose your data dictionary before you Create a data file.

Next, enter the height of the GPS antenna above the ground (1.5 m is about right for a person of average height). If you followed all the directions above, then you should see 7 buttons: [Art], [Mark], [Track], and [Pokemon] (the feature classes that you created) as well as the default feature classes: [Point_generic], [Line_Generic], and [Area_generic].

Step 4b. Collect data. Bolstad (2016: 227-239; p96-97) Survey marks

Start your field work by finding the first survey mark, which is in the grassy yard behind Shearer Hall (see the Appendix for pictures). Occupy the position and create a digital Mark

feature to represent the actual mark entity. TerraSync will report the number of satellites involved and the number of raw positions that have been recorded (recall, you need at least 120 positions, so don’t wander as the device does its work). Complete your attribute form as the device logs raw position data. After you’ve collected at least 120 raw positions (more is okay, fewer is not) and finished recording attributes, then close the feature by hitting Done.

Last, with a digital camera, take a digital picture of each mark. Art pieces and Pokémon sites Follow the same procedure you used to measure a survey mark, but create Art features at art installations and create Pokémon features at Pokémon gyms and stops. Don’t forget to take a digital picture at each place. Track

We’re going to collect track data a little differently than we collected the other data. When creating and measuring the Track, we want to do so repeatedly with multiple loops. We want to collect at least 4 loops (but more is better) of track data.


Start by finding a nice starting spot on the track, use the Trimble GeoExplorer3000 to create a Track feature, walk around the track once, and then stop at your point of beginning. Finish the loop by hitting Done.

At the same spot, create another Track feature, walk around the track again, and stop again at your starting point. Close the feature by hitting done.

Keep repeating the preceding workflow until you have 4 or more loops worth of data. Try to follow the same path around the track each time you walk a loop.

IF you have enough time to complete your entire inventory during a single trip to the

field, THEN keep your data file open: navigate to each entity, use your GPS unit to create a new feature to represent it, then hit Done. When you’re all done with all your field work, then close the data file, exit TerraSync, and power down the device.

IF you do not have enough time to complete the entire survey during a single trip to the

field OR you have to wait for good (bad) blocks of time to start (end), THEN you can close the data file; close the TerraSync application; and let the machine go to sleep (saves battery). When the next good window opens, you can re-open TerraSync, re-open your existing data file, and add the next new feature to it.

IF you do not have enough time to complete the entire survey during one session AND

you have to spread your work over multiple days, THEN create a new data file for each day. You can combine multiple data files after you get back to the lab. Again, make sure you are prepared with enough water, appropriate clothing and sun protection.

If you need a break, then this point in the lab is a natural break. Step 4c. Download the data file(s) (*.SSF) you created. Close the TerraSync software on the Trimble device before inserting it back into its cradle. Microsoft’s Mobile Device software should recognize the device and open a port for communication. When prompted, “Connect without setting up your device.” Minimize the Mobile Device Center. Next, add your data file to your receive list, then transfer all the items on the receive list to your computer. Close Data Transfer.


Quality Assurance (QA) methods, Part 2 All that mission planning you did was to ensure that you collected data when optimal conditions were predicted. Working according to plan does not guarantee, however, that actual conditions were optimal, that you collected good data, or that you collected all the data you needed.

First, your raw data are likely infected with some clock- and atmosphere-related errors. Second, tall campus buildings and trees likely interfered with some of your incoming satellite signals or, worse, caused them to bounce around before arriving at your device. See Figure 5-31

in Bolstad (2016, p231). Third, you might have committed some mistakes while learning how to use the Trimble device. Or fourth, you might have started taking short cuts or making blunders the longer you worked. These are just some of the reasons why you never want to give raw GNSS data to a client.

Before post-processing, make a copy of your data file (e.g., copyR09*.ssf). Working with a copy of your data will let you practice and play without fear of decimating your field data, for you’ll always have the original SSF file as a back-up.

Start a session of GPS Pathfinder Office and go back to your Shippensburg project. Make

sure you can see the Map, Time Line, Feature Properties, and Position Properties windows.

Next, set the Options > Coordinate System… to US State Plane 1983, Pennsylvania South 3702 (NAD83). Set your vertical datum to be Mean Sea Level (via the latest GEOIDxx model). All coordinate values should be displayed in meters. 2 Next, File > Open… your data file (copyR09*.ssf). If you setup your data dictionary correctly, then you should see where your features were measured (Map window) and when they were measured (Time Line window). You can use your cursor to select a feature in either window and the corresponding symbol will become selected in the other window. Notice, also, that Feature and Position attributes are reported with any change in your selection. Question 2: How many feature classes are in your data file and how many features are in each

feature class? Use your cursor to select a survey mark. The Feature Properties window lets you review the attribute data. The Position Properties window reports the average but uncorrected Easting, Northing, and Altitude values for the selected feature (remember the position averaging technique we discussed in class?). Change the View > Layers > Features… > Not in Feature > Symbol… properties to have a dark color and a thick width. Now, Delete your selected feature. Relax, deleting a feature allows you to see the sample of raw (single-fix) position coordinates that support the average feature coordinates. Change map scale and pan to focus on your supporting sample. Question 3: How many raw single-fix positions (repeated measures) support the average

coordinates that were calculated for your feature?

2 Remember, all GNSS receivers spatially reference positions to the WGS84 ellipsoid model only. These settings do not

change the actual geographic coordinates { λ, Φ, h } that you measured; rather, they simply tell the software which spatial reference system/projection method you want to use for on-screen display purposes.


Next, use your cursor to select raw positions, one-by-one, and examine their coordinates and DOP values. Observe how your measuring method changed as GPS satellites entered or left the constellation above your local horizon. Question 4: Describe any changes that occurred to your satellites-receiver geometry as you

collected these raw data. Question 5: Do you notice any sequence of raw single-fix positions that seems to fall along an

apparent straight line? If so, what might this pattern indicate was happening? Question 6: Look at the entire pool of supporting positions.

a) Does your pool of supporting positions have a central cluster? If so, how wide is it? (Use the Measure tool. You might have to change your display units to show meters; not kilometers.) Also, how far apart are the most distant pair of raw positions?

b) Interpret your answers above to characterize how consistently your measuring

equipment/method produced the same result during repeated measures? Step 5. Apply differential corrections. Bolstad (2016: p215-221) As described in your textbook, differential correction techniques require at least two proximate GNSS receivers to read satellite data simultaneously. One receiver is installed at a fixed and known point; this receiver is called the “base” (e.g., a local National Geodetic Survey CORS site). The other receiver is mobile and used for field work; this receiver is called the “rover.” Because the “base” is installed at a known spot and it measures itself over-and-over again, any difference between the actual base coordinates (thanks NGS) and the measured base coordinates (obtained via GPS) can be blamed on the GPS.

𝐷𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑐𝑒𝑏𝑎𝑠𝑒 @ 𝑡𝑖𝑚𝑒𝑥= 𝐴𝑐𝑡𝑢𝑎𝑙𝑏𝑎𝑠𝑒 − 𝑀𝑒𝑎𝑠𝑢𝑟𝑒𝑑𝑏𝑎𝑠𝑒 @ 𝑡𝑖𝑚𝑒𝑥

Eq. 1

If we assume that your rover unit used the same satellites to measure positions on

campus as the nearest base station was using to measure itself, then any observed “differences” at the base can, in turn, be applied as “corrections” to rover data; hence, differential corrections.

𝐶𝑜𝑟𝑟𝑒𝑐𝑡𝑟𝑜𝑣𝑒𝑟 @ 𝑡𝑖𝑚𝑒𝑥= 𝑅𝑎𝑤𝑟𝑜𝑣𝑒𝑟 @ 𝑡𝑖𝑚𝑒𝑥

− 𝐷𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑐𝑒𝑏𝑎𝑠𝑒 @ 𝑡𝑖𝑚𝑒𝑥 Eq. 2

Trimble GPS correction software is designed to perform differential corrections swiftly. Speed is good for the professional, but that same speed can be bad for the student because it’s difficult to watch what is happening and learn. So, follow these directions and you’ll be able to watch the process and get a better sense of how differences at the nearest CORS are used to correct your raw rover data.

1. Open the Utilities > Differential Correction… utility. You might be prompted to save your data file if you made any changes: the choice is yours to make.

a. Select the SSF file(s) you wish to correct. i. [Next]


b. Processing type i. Select Code Processing Only

ii. [Next] c. [Change…] the Correct Settings

i. Output positions 1. Corrected only

ii. GPS Filtering 1. Elevation mask = 10° 2. Minimum Signal-to-Noise ratio = 33 3. Maximum PDOP = 3 4. DO re-correct real-time code positions

iii. [Next] d. Base Data

i. Browse Base Provider Search and Select… the CORS, CHAMBERSBURG (PAFC), PENNSYLVANIA site, which is the closest base station. Choosing this option instructs the software to access the CORS server via the Internet and request base station data.

ii. Use the known position from base provider. iii. DO Confirm base data and base position before processing. iv. [NEXT]

e. Output folder i. Use the same folder as the input file

ii. Create a unique filename … iii. [START]

Question 7: How many base files, if any, did the software download for you? Question 8: How much coverage (amount of temporal overlap, expressed as a percent) exists

between your rover data and the base data?

iv. [CONFIRM]

Question 9: How many (#) and what share (%) of your positions were not differentially corrected? Why?

Question 10: Given how satellites-receiver geometry can change over time, it is likely that you measured some raw positions more precisely than others. How many (#) and what share (%) of your corrected positions fell into each “range” of precision-related uncertainty? See Bolstad (2016) Figures 5-11, 5-12, and 5-31

v. [CLOSE]

2. File > Close your uncorrected datafile (*.SSF). 3. File > Open your corrected datafile (*.COR).

Question 11: Did you lose any features during differential correction? (#,%)?


Step 6. Filter your positions one more time and export your features. Follow these directions – and you’ll be able to average position data in Trimble’s *.COR format to make features in Esri shapefile format.

1. Open the Utilities > Export… tool. a. Select your corrected (*.COR) data file as input. b. Choose your output folder (where the shapefile will be created). c. Choose the Sample ESRI Shapefile Setup option. d. [Properties…]

i. Data 1. Export all Features – Positions and Attributes 2. Uncheck “Include Not in Feature Positions”

ii. Output 1. For each input file create output Subfolder(s) of the same name.

iii. Attributes (for the output attribute table) 1. Export menu attributes as Code Value 1 2. All features (check all of the following)

a. PDOP b. HDOP c. Correction status d. Receiver type e. Date recorded f. Time recorded g. Data File Name h. Total positions i. Filtered positions j. Data Dictionary Name

3. Point features (check at least the following) a. Height b. Vertical Precision c. Horizontal precision

4. Area features (check at least the following) a. Average Horizontal Precision b. Average Vertical Precision c. Worst Horizontal Precision d. Worst Vertical Precision

iv. Units 1. Use Export Units = meters with 1 digit of decimal precision

v. Position Filter

1. Minimum Geometry = 3D (5 or more) 2. Maximum PDOP = 3 3. Maximum HDOP = 3 4. Check every option but one: uncheck Uncorrected positions

vi. Coordinate system

1. Use Current Export Coordinate System [Change]


a. US State Plane 1983 b. Pennsylvania South 3702 c. NAD 1983 (Conus) d. Meters e. Meters f. MSL

vii. ESRI Shapefile (ignore)

viii. [OK] e. [OK]

Question 12: How many features were discarded because their supporting positions did not

pass through the final quality assurance filter? You may close your corrected data file and close your GPS Pathfinder Office session when you have finished exporting your data into ESRI shapefile format.

If you need a break, then this point in the lab is a natural break. Quality Control (QC) methods Bolstad (2016: p621-631) Quality Control is an industry term that refers to qualitative and quantitative assessments of data, calculations, maps, etc. At this point, we know that all of the differentially corrected GNSS data that survived the QA process are acceptable. We still do not know, however, how accurate those data are. Are they flawless? Or are they barely acceptable?. Question 13: Qualitatively assess your data by building a stand-alone map (NOT an inline map-

figure this time) that can be attached to your lab report. Describe the visual quality of your data in text and prose (Do they look right? Do they seem complete?). Your map should use the locations of campus buildings and roads as reference layers (data provided on the course website) and the locations of your surviving features. Symbolize your features. Most of you have taken cartography – you know the fundamentals of good map design. And, at a minimum, label your survey marks.

Question 14: Quantitatively assess the accuracy of your survey mark coordinates. (How accurate

are they? How complete are they?) Guesses or fuzzy feelings will receive zero credit. Your claims need to be supported by a metric RMSE statistic. Show all work. See Bolstad (2016: p628-631) for a worked example.

Question 15: Define the terms ‘error’, ‘precision’ and ‘accuracy’, and use examples from your

work to demonstrate that you understand the differences among these three interrelated but different terms.


Deliverables Complete a well-written report of the lab exercise. Include your name, date, and page

numbers. Your report should include five sections and headings: Purpose, Objectives, Methods and Data, Results and Answers, and Summary. Provide concise purpose and objectives using your own words, and describe the important methods and input data you used to address the tasks listed above. In the Results and Answers section, address any issues or questions prompted during the lab. Include tables and figures in the same order you refer to them. In the Summary section, describe how you accomplished the purpose of the lab (i.e., how well did you answer the research question); then identify anything that you learned, or anything that remains problematic. Your List of References should list any and every published work that you used to support your work.

All lab reports should be typed and printed on 8.5” by 11” stock. Before drafting your report, set your right and bottom page margins to be 0.7”; set your left margin to 1.2”; set your top margin to 1.2”; and set your header margin to 0.7”. Put your name and the lab title in the document header. Set the normal font face to be Bookman Antiqua, Bookman Old Style, or Georgia; never use Times New Roman or any kind of decorative font. Also, set the normal font size to be

11 points. Use single line spacing. Include page numbers on every page. Major section headings should be in bold face. All tables must be inserted into the body of your report and conform to the formatting and margin requirements. Question 16: Last, create a folder and name it using your surname. Next, make sure the folder

contains copies of only the following: 1. Your data dictionary (ddf) file; 2. Your raw positions data file (*.ssf); 3. Your differentially-corrected positions data file (*.cor); 4. And copies of the shapefiles that you exported.

Last, after you’ve filled your folder with only the items listed above, then ZIP the folder into an archive and send the archive to me as an email attachment. If you don’t use this link in the PDF [email protected], then be sure to type “GIS3 GNSS” as your subject line.

mailto:[email protected]?subject=GIS3%20GNSS


Appendix A: The survey marks Four marks on campus serve as ground control points. Each mark is well labeled and anchored to the ground with a spike. All marks were recently occupied and verified, but some can become obscured easily by grass or loose debris.

Figure A1: A low-cost and uniquely labeled survey mark.

Survey mark SM001 is located in the yard behind Shearer Hall. It is near the parking lot, where two sidewalks merge, near a cement urn (the urn is moved occasionally), and close to the end wall of Rowland Hall.


Survey mark SM002 is situated along Adams Drive and near the pedestrian bridge that leads to the Cora L. Grove Spiritual Center. Look at the corner of the T-type intersection between sidewalks.

Survey mark SM004 is located at the north end of campus where Lancaster Drive changes from a two-lane road to a one-lane path. From this spot and looking due south, you can easily see the Ric H. Luhrs Performing Arts Center. This mark is the mark that is closest to the Hockey Rink and the Student Recreation Center.


Survey mark SM006 is located in the oldest and westernmost part of campus, and behind Horton and Gilbert Halls. From Gilbert Drive, follow the striped pedestrian path toward the old one-room schoolhouse and stop at the top of the stairs.

Survey marks SM003 and SM005 were destroyed during campus construction projects.

Global Navigation Satellite Systemswebspace.ship.edu/sadrzy/geo420/labs/GIS3_Lab_GNSS_QA_QC.pdf ·...

Documents

Transcript of Global Navigation Satellite Systemswebspace.ship.edu/sadrzy/geo420/labs/GIS3_Lab_GNSS_QA_QC.pdf ·...