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Advanced Mapping Sciences Course: Spatial Literacy, GIS, Cartography, and GIScience

Join our course to enhance spatial literacy, learn basic statistics principles, GIS, cartography, and GIScience. Topics include data measurements, spatial data storage, surveying, GPS, remote sensing, and more. Attend lectures and labs to master the art of geographical data analysis and mapping techniques. Earn evaluation scores through participation, exams, and projects. Stay engaged as we delve into probability, hypothesis testing, maps as communication tools, thematic map design, and more. Prepare for the final exam through practical labs and theoretical lessons. Contact us for any inquiries or special accommodations.

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Advanced Mapping Sciences Course: Spatial Literacy, GIS, Cartography, and GIScience

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  1. GTECH 201 Introduction toMapping Sciences

  2. Contact Information Instructors: Jochen Albrecht (and Tom Walter) Office: Hunter N1030 Office hours: We, Th 2-3 PM E-Mail: jochen@hunter.cuny.edu Phone: (212) 772-5221 TA: Jing Li E-Mail: JLi5@gc.cuny.edu

  3. Course Overview • Spatial literacy • Basic principles • statistics • GIS • cartography • geographic information science (GIScience)

  4. Texts • Required: none • Recommended • McGrew, J and Charles Monroe 2000 (2nd edition). An introduction to statistical problem solving in geography. McGraw-Hill. • O’Sullivan, David and David Unwin 2002. Geographic Information Analysis. Wiley. • Walford, Nigel, 1995. Geographical Data Analysis. Wiley.

  5. Policies • Attendance • Plagiarism • Special accommodations • Lab policies • Assignments

  6. Criteria for Evaluation • Participation 10% • Midterm exam 15% • Final exam 25% • Lab projects 50%

  7. Schedule Class # Date Topic 1 01/27 Introduction – the nature of data 2 01/31 The computing environment in the geography department L1 02/02 Lab 1: Computing in the geography department 3 02/03 Data measurements; data errors L2 02/07 Lab 2: introduction to Unix L3 02/09 Lab 3: how to write web pages L4 02/10 Lab 4: introduction to Excel 4 02/14 The nature of spatial data 5 02/16 Storing spatial data L5 02/17 Lab 5: introduction to ArcGIS 7 02/23 Projections 8 02/24 Surveying and digitizing L6 02/28 Lab 6: digitizing data for the vector model 9 03/02 GPS 10 03/03 Remote sensing 11 03/07 Census data 12 03/09 Mapping census data and simple spatial query L7 03/10 Lab 7: mapping census data 13 03/14 Midterm Exam L8 03/16 Lab 8: introduction to R 14 03/17 Sampling and questionnaires L9 03/21 Lab 9: questionnaire design

  8. Schedule Class # Date Topic 15 03/23 Probability and probability distributions 16 03/30 Sampling and sampling design 17 03/31 Point and interval estimation L10 04/04 Lab 10: probability distributions 18 04/06 Hypothesis testing 19 04/07 Analysis of variance L11 04/11 Lab 11: hypothesis testing 20 04/13 Chi square; goodness of fit 21 04/14 Correlation and regression L12 04/18 Lab 12: confidence measures 22 04/20 Experimental design and multivariate analysis 23 04/21 Qualitative approaches L13 05/02 Lab 13: ANOVA 24 05/04 Maps as a means of communication 25 05/05 Anatomy of a thematic map L14 05/09 Lab 14: designing a thematic map 26 05/11 Design of choropleth, dot and proportional symbol maps 27 05/12 Design of isarithmic and flow maps L15 05/16 Lab 15: cartographic studio 28 05/18 Review and where to from here 05/19 - 05/22 Final (online) Exam

  9. The Nature of Data

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