CIS 7030 Geospatial Analysis Assignment (2023)

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Nov 24, 2024

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Student Details ( Student should fill the content) Name Batch Number Student ID Cardiff Met ID : ICBT ID : Scheduled unit details Unit code CIS 7030 Unit title Geospatial Analysis Assignment Details Nature of the Assessment Assignment Topic of the Case Study GIVEN Learning Outcomes covered YES Word count 4000 words Due date / Time 30 th November 2023 Declaration I certify that the attached material is my original work. No other person’s work or ideas have been used without acknowledgement. Except where I have clearly stated that I have used some of this material elsewhere, I have not presented it for examination / assessment in any other course or unit at this or any other institution Signature Date Result (Assessor use only) Marks by 1 st Assessor Name & Signature of the 1 st Assessor Agreed Mark Marks by IV: Name & Signature of the IV For Office use only (hard copy assignments) Receipt date Received by

Assignment Type & Title: For student use: Critical feedback on the individual progression towards achieving the assignment outcomes For 1 st Assessor use: Assessment feedback Strengths Area for improvements Name & Signature of the Assessor : Dat e : Comments by the IV Name & Signature of the IV: Date :

CIS 7030 -Geospatial Analysis Weighting of assessment: 100% total marks Word Limits: 4000 Words Learning Outcomes On successful completion of the module students should be able to: 1. Synthesise underlying geospatial concepts and apply them appropriately; 2. Critically evaluate forms of social analytics, applying appropriate techniques on social information; 3. Determine, design, prototype and implement geospatial applications; 4. Critically evaluate and identify emerging technologies and research areas relevant to geospatial analystics. Task 01: How geospatial data science can be used for business. (10 Marks) Propose a business plan to enhance the business using geospatial data science. Hint - Geospatial data science can benefit businesses by providing valuable insights for market analysis, customer segmentation, location intelligence, and resource optimization. By leveraging spatial data, businesses can make informed decisions, improve operational efficiency, target the right audience, and gain a competitive advantage. To enhance a business using geospatial data science, the proposed business plan could include.  integrating location data into customer profiling,  conducting spatial analysis to identify target markets and optimal store locations,  utilizing geospatial analytics for supply chain optimization, and  incorporating location-based marketing strategies. Note - This plan aims to leverage geospatial data science to improve decision-making, enhance customer experiences, and maximize operational efficiency for sustainable business growth. Task 02: Descriptive explanations (Marks 20) Discuss the following topics/techniques for conducting geospatial data analysis.  Exploratory Spatial Data Analysis  Spatial Statistical Models  Geovisualization  Machine learning for Geo-spatial data analysis Your answer should contain the following key points. (But not limited to those.) 1. An example describes real-world usage. 2. A code snippet/s that supports your answer.

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Task 03 – Predictive analytics for geospatial application (Marks 30) "The usage of geospatial technology is extremely minimal in Sri Lanka, compared to other countries in the world." Propose a predictive model for one of the following questions. 1. Propose a complete analysis to predict natural disasters (E.g.- flooding) in Sri Lanka. (It should be a complete analysis to predict disasters in Sri Lanka. Further follow the process of gathering historical disaster data, collecting relevant spatial data (e.g., rainfall, topography), applying spatial data science techniques (e.g., spatial statistics, machine learning), and developing predictive models to assess risk and aid in decision-making for disaster management and mitigation efforts.) 2. Propose a complete analysis to identify the most optimal location for establishing a new school/hospital. This is to identify the most optimal location for establishing a new school/hospital. Hence a complete analysis must be performed, including gathering data on population density, transportation accessibility, demographic characteristics, infrastructure availability, etc. By applying spatial analysis techniques, such as suitability modeling and spatial clustering. The analysis aims to identify areas with high demand and accessibility, ensuring the new facility's effectiveness and impact on the target population. Note: Your answer must encompass the following factors. Spatial Data Collection, Spatial Data Preprocessing, Spatial Feature Extraction, Spatial Exploratory Data Analysis (ESDA), Spatial Machine Learning, Spatial Validation and Prediction, Spatial Visualization and Interpretation, Spatial Uncertainty Analysis Task 04 – Geospatial Application (Marks 35) Develop a predictive dashboard to predict and monitor the geo-distribution of an event/incident (E.g.: - a special event like a Book Fair) using social media data. Hint - Your application collects and preprocesses relevant social media data, analyzes patterns and clusters, and incorporates predictive models based on historical data. The dashboard displays a map with visual markers, key metrics, and alerting mechanisms to provide real-time insights and facilitate effective monitoring of the event/incident's geographic distribution. Your dashboard should adequately implement the following aspects (but not limited to). Data Collection, Data Preprocessing, Data Analysis, Predictive Modeling, etc. Marks distribution Task 01_10 marks Task 02_20 marks Task 03_30 marks Task 04_35 marks Correct documentation/formatting and references – 5 Marks ASSIGNMENT INSTRUCTIONS  Minimum of 15 quality references (books, journal articles etc.) are expected.

 In-text and end-text referencing (Harvard referencing)  4,000-words (excluding reference, bibliography, appendices, code etc.)  You cannot use materials submitted in any other unit Marking Scheme Mark Range Criteria 80 – 100 An excellent report is given that shows evidence of extensive research: brilliant motivation/rationale of the project with an excellent design, discussion of data sources / APIs and justification of choice. A well written, efficient, functional project for social computing has been developed and a thorough test plan, findings with visualisations and storytelling are evident. Excellent key results with limitations and conclusions are depicted. An excellent presentation is also given and the student demonstrates a brilliant understanding of the implementation, APIs and techniques used. The report format and references are at the top end of this band - the work is of publishable quality. 70 – 79 An excellent report is given that shows evidence of detailed research: brilliant motivation/rationale of the project with an excellent design, discussion of data sources / APIs and justification of choice. A well written, efficient, functional project has been developed with clear evidence of testing, findings with visualisations and storytelling. A clear presentation is also given and the student demonstrates an excellent understanding of the implementation, APIs and techniques used. The report format and references are excellent with minor typos and errors. 60 – 69 A very good report is given that shows evidence of detailed research: good motivation/rationale of the project with a detailed design, discussion of data sources / APIs and justification of choice. A well written, functional project has been developed with some evidence of testing, findings with visualisations and storytelling. A clear presentation is also given and the student demonstrates a very good understanding of the implementation, APIs and techniques used. The report format and references are very good with some typos and errors. 50 – 59 A good report is given that shows evidence of research: some motivation/rationale of the project with a good design, discussion of data sources / APIs and justification of choice, though these could be expanded upon. A functional project has been developed with some

evidence of testing, findings with visualisations and storytelling. However, the visualisations and discussion could be enhanced. A good presentation is given and the student demonstrates a good understanding of the implementation, APIs and techniques used. The report format and references are good with some typos and errors. 40 – 49 A basic report is given that shows some evidence of research: limited or no motivation/rationale of the project with a basic design, limited discussion of data sources / APIs and justification of choice - these need to be expanded upon. A functional project has been developed but there is little to no evidence of testing and visualisations. Only a basic presentation is given and the student only demonstrates a basic understanding of the implementation, APIs and techniques used. The report format and references are basic with major typos and errors. 35 – 39 A very basic report is given that shows little to no evidence of research: no motivation/rationale of the project with only a very basic design, data sources / APIs and justification of choice. A limited project has been developed that does not meet all functional requirements and little to no evidence of testing and visualisations is evident. Only a basic presentation is given and the student demonstrates little to no understanding of the implementation, APIs and techniques used. The report format and references are poor with major typos and errors. Under 35 Limited or no evidence of research: no motivation/rationale of the project with no design, data sources / APIs and justification of choice is given. No functional project has been submitted with no testing and visualisations and no meaningful results produced. No presentation is given. The report format is very poor and no or little references with major errors. REPORT STRUCTURE  Paper Size : A4  Word Count : 4000 words  Printing Margins : LHS; RHS: 1 Inch  Binding Margin : ½ Inch  Header and Footer : 1 Inch  Printing : Single Sided  Basic Font Size : 12  Font Style : Arial/Times New Roman  Presentation : Bound Document

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Important Information for Students  The final version of your individual assignment softcopy needs to be uploaded to the Turnitin via Cardiff Met Moodle before the deadline. For TURNITIN submission please log on to www.cardiffmet.ac.uk and submit through the Moodle.  The final version of your individual assignment soft copy (word format only) must be uploaded to ICBT SIS on or before the deadline. Please log on to www.icbtsis.lk to upload your assignment. The softcopy should be named as MSc IT-(subject number) (followed by the Cardiff met student ID. E.g. for Technology Project Management CIS_7008 _2000000  Students are expected to keep a backup of all the assignments. ICBT and Cardiff Metropolitan University have all the right to re call for soft copy of any assignment at any time during the course.  Please note that plagiarism is treated as a serious offence and therefore the work you produce must be individual and original although may work in groups in some instances (Please refer to Student Handbook on Plagiarism & Cheating).  All sources of information must be referenced using “Harvard referencing ” where a reference listing should be included at the end of the assignment.  Please note that the submission date given for this assignment is the final date that you can upload the assignment. No late submissions are allowed by the system.  Please refer to Student Handbook on Assignments – Re-submission, mitigating circumstances procedure.

 Please include the assignment coversheet and feedback sheet in your softcopy of the assignment. Please avoid copying assignment question in your answer file.  The submission instructions of Turnitin and ICBT SIS will be circulated 10 days before the submission deadline.

CIS 7030 Geospatial Analysis Assignment (2023)

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