KGG102 Student Assessment

KGG102 Student Assessment :

KGG102 Assessment Task 2

Due date: Friday 28^th April, 5 pm (17:00)

Assessment Released: Tuesday 14^th March

Marks Released: 15 calendar days after the due date

Weight: 20% of unit total

KGG102 Problem statement

Real world features can be represented in a GIS in either a vector or a raster data model. The choice of data model will depend on the type of data being collected (discrete, e.g. contours or continuous, e.g. an elevation model), the method being used to collect the data (e.g. airborne instrument such as a camera capturing images or a field survey capturing point, line and polygon features with a GNSS device), and the type of analysis that we wish to conduct and which data model best suits the analysis techniques we plan to use.

When preparing data sets for our analysis there are situations where we have to vectorise a raster data set or rasterise a vector data set. Preparing data sets for an analysis in a GIS environment requires technical skills and knowledge of data handling, management and reporting.

In assessment task 2, we are providing you with a hypothetical, yet realistic, project in which you will be required to build a GIS data set using skills that you have acquired during computer practicals 2, 3, 4 and 5, and complete some short answer KGG102 questions about the creation of this dataset.

Part I: Digitising Features From a Scanned Paper Map (60%) Background and Dataset:

The George Town Council wants to carry out an audit of land cover south of George Town in order to contribute to the Federal Government’s Carbon Bank scheme proposal. Searching through archives you have found an old Forestry Commission map of Bell Bay and George Town which could be useful. As a first step in the process, the topographic features in the map need to be converted into an electronic format to identify the different land cover classes.

The Council has asked you, as a GIS consultant, to georeference the Bell Bay map, digitise the features off the scanned forestry map so further analysis can be performed on the forest type polygons. To help you with your work, they have provided you with some shapefiles of the area. The dataset includes:

1. River Lines

• Feature Class: River_MGA2020.shp

• Geographic coordinate system: MGA2020

• Data source: Lines Features of rivers in a selected area of the Bell Bay area. Digitised by M.Williams in 2022 from the Tasmania 1:25 000 forest type series. 4844, Bell Bay / Forestry Commission of Tasmania.
• Transport Segments

• Feature Class: Transport_MGA2020.shp

• Geographic coordinate system: MGA2020

• Data source: Line Features of the road network in a selected area of the Bell Bay area. Digitised by M.Williams in 2022 from the Tasmania 1:25 000 forest type series. 4844, Bell Bay / Forestry Commission of Tasmania.
• Water Bodies

• Feature Class: Water_MGA2020.shp

• Geographic coordinate system: MGA2020

• Data source: Polygon Features of water bodies in a selected area of the Bell Bay area. Digitised by M.Williams in 2022 from the Tasmania 1:25 000 forest type series. 4844, Bell Bay / Forestry Commission of Tasmania.

Please refer to the detailed instructions in practicals 3, 4 and 5 to complete the tasks below.

Tasks

You are required to do the following:

• Georeference the scanned Bell Bay forestry map.Use the provided coordinates to georeference the corners of the mapUse the provided transport segments layer to produce an additional 6 GCPs
  • Digitise the forest types boundaries into a new polygon feature class
    • Create a bounding box polygon for the area of interest (refer to practical 4 for details)
    • Remove the areas covered by waterbodies from your bounding box polygon

• Use the split tool and various digitising tools to create separate polygons for each forest class region
  • Create a topology for your feature dataset
    • Create topological rules (refer to practical 5 for details)
    • Validate the topology and show any remaining errors and exceptions
    • Define an attribute domain for the forest type in forest type feature class (Table 1)
    • Follow the instructions in practical 6 to establish the required fields and the domain
    • Assign the correct forest class for each polygon in the attribute table using the classes in Table 1 below

Table 1: Simplified forest type codes

Forest type code	Attribute code	Attribute Description
V	V	Cultivation and pasture
S, c/o K.S, S.Wg, S.Vz, K.S, S.E4f	S	Scrub
WS	W	Wasteland
Wr	Wr	Bare rock or ground
Vz, Vz.S, Vz.E4f	Vz	Rough grazing
T.S,	T	Secondary species
f/d E3c.S	E3	Mature eucalypt (27-41m)
E4d, E4b.S, E4d.K.S, E4d.VS,E4d.S, E4c.S	E4	Mature eucalypt (15-27m)
E5d.K.S	E5	Mature eucalypt (<15m)

Part II: Evaluating Georeferencing and Digitising in Creating a GIS dataset (40%)

Evaluating the choices you, as the GIS analyst, made related to georeferencing and digitising is crucial because the accuracy and quality of spatial data produced depend on the choices made during these processes. Choosing the appropriate coordinate system, accuracy standards for georeferencing, and selecting the right digitising technique, tool, and resolution for digitising, can have a significant impact on the reliability, precision, and usefulness of the resulting spatial data. Moreover, evaluating these choices can help identify and address

potential errors, biases, or inconsistencies in the data, and ensure that it meets the requirements of the project or application. Thus, careful evaluation of the primary data sources and the choices made related to georeferencing and digitising is essential in your efforts to produce high-quality spatial data that can support informed decision-making and further analysis. In the second part of assessment task 2, you are required to address the following short answer questions, which will assist you in undertaking a self-evaluation of the choices you made during the data creation process.

Question 1: How did you choose the coordinate system for your datasets, and what factors influenced your decision? (maximum of 200 words)

Question 2: What is the accuracy of the georeferenced data you produced, how did you evaluate the accuracy of your new dataset, and what steps did you take to improve it? (maximum of 200 words)

Question 3: Digitising has potential for error and inaccuracy, how did you find those errors and how did you fix them? (maximum of 200 words)

Question 4 (for KGG539 only): What were some of the biggest challenges you faced during the georeferencing and digitising process, and how did you overcome them? (maximum of 200 words)

Submission

In this KGG102 assessment you are required to submit two (2) documents to the Assessment Task 2 dropbox:

Part I

1. Submit a PDF with the following items:
   1. A screenshot showing the location and distribution of your GCPs
   1. A screenshot of the Control Point Table for your GCPs and the final overall error (RMSE) in metres.
   1. A screenshot of your forest attribute domain showing all the coded values of the forest type domain

A screenshot of your geodatabase topology rules

• A screenshot showing the entire map area with the error inspector displayed. Change the symbology of the forest layer to a single symbol and then validate the dataset before taking the screenshot. Make sure the number of errors is displayed at the bottom of the screenshot, otherwise you will be penalised.

Part II

Submit a second PDF document with answers to the three (3) questions (if in KGG102) or the four (4) questions (if in KGG539) in Part II. Each answer should be a maximum of 200 words each, as per the description in Part II.

Feedback and Grades

Feedback and grades will be provided in MyLO within 15 working days (3 calendar weeks) after the due date. Assessments received after the due date will receive a late penalty. Five

percent (5%) of the total available KGG102 assessment task mark will be deducted for every calendar day (i.e. including weekends) that the assessment is late.

Late Submission of Assessments

Late submissions will not be accepted after the cut-off date, which is defined as more than 10 calendar days after the due date, or after assessments have been returned to other students (i.e. within 15 working days after due date), whichever occurs first. KGG102 Assessments that have not been submitted by the cut-off date will receive a mark of zero (0) and will not receive feedback.

Requests for Extensions

A request for an extension must be submitted by the KGG102 assessment due date, except where a student can provide evidence that it was not possible to do so. If you require an extension of more than 1 or 2 days, please provide evidence that you require an extension. Extensions are granted solely at the discretion of the unit coordinator.

Academic Integrity

All submissions will be sent to Turnitin to be checked for originality. Students who have submitted an assessment task that has been found to have potentially breached the University’s academic integrity policy will be reported to the Academic Integrity Advisor. There will be no exceptions to this rule. Students are required to have completed the mandatory Academic Integrity Module in MyLO, and therefore be familiar with what is considered to be a breach of academic integrity. In the event of a potential breach, marks will be withheld until a ruling is delivered by the academic integrity advisor. The unit coordinator or other teaching staff cannot provide comment to students until the ruling has been released.

Statement on the use of Artificial Intelligence

You can use generative Artificial Intelligence (AI) to learn, just like you would study with a classmate or ask a friend for advice.

You are not permitted to present the output of generative AI as your own work for your assignments or other assessment tasks. This constitutes an academic integrity breach.

Assessment Criteria

The assessment criteria for this assessment task are based on the following:

• Application of GIS data creation knowledge to practical problems

• Completeness and correctness of georeferencing and digitised datasets

• Interpret the appropriateness of the analysis and data creation methods used

Note: all answers should be given in metric units and the unit should be included in the answer (where applicable). Details of grades and marking criteria are given in the following two tables.

Part I (60%)	HD	DN	CR	PP	NN	X
Georeferencing of the map
Geodatabase configuration
Quality of digitising
Accuracy of digitising
Part II (40%)	HD	DN	CR	PP	NN	X
Evaluation of Coordinate Systems
Evaluation of Georeferencing Method
Evaluation of Digitising Method
Data Creation Challenges (KGG539)

Mark range	Quality of student work
80 – 100 HD	Achieved all that could reasonably be expected in the time available. Mistakes, if any, are trivial. Exemplary work.
70 – 80 DN	Excellent work, highly focused and relevant with few errors, some minor errors towards lower end of the range. Clear text and tables, little superfluous material.
60 – 70 CR	No more than two major deficiencies and no major flaws. Good content, structure, and presentation.
50 – 60 PP	No major flaws (marks of 0 or 1) but a large number of deficiencies.
40 – 50 NN	Some evidence of knowledge and understanding to indicate familiarity with subject area though may be confused and/or unfocused. Some relevant material but omits key points and/or contains significant errors.
20 – 40 NN	A fail – a large number of major flaws and shows limited evidence of knowledge and understanding. Presentation is poor in most assessed elements.

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