ECECS
Geomatic Sciences
  • Masters in Geospatial Science and Technology
  • Program Description
  • Geospatial Science and Technology refers to the science and technology used for visualization, measurement and analysis of features or phenomena that occur on the earth. This terminology has become common in the United States, and is synonymous with Spatial Information Science and Technology. Geospatial science and technology include three different technologies that are all related to mapping features from the surface of the earth. These three technology systems are: GIS (geographical Information Systems), Remote Sensing and GPS (Global Positioning Systems).

    The master program will expose the student to the principles and techniques related to geospatial data model generations, data capture and representation and will learn how these could help in the solution of different problems faced by society. Bu its integrative nature, the program will support research and application modeling in diverse disciplines such as Land Surveying, Architecture, Planning, Geography, Environmental management, Biology, Engineering and other professionals who deal on a day to day basis with geospatial data capture and analysis.

    Download the Masters in Geospatial Science and Technology Flowchart
  • Masters in Geospatial Science and Technology
  • Careers
  • The program aims to develop professionals capable of contributing to the development of geospatial systems based on the principles of Geomatics. This broad overview of potential market provides a real and varied employment spectrum for graduates of the program. Given the extent of possible applications that can be generated, Geospatial Science and Technology graduates may be employed in areas ranging from spatial data management for environmental problems to management of data for studies in the insurance market. It is expected that many students are professionals in various fields who seek to add to their profession geospatial data management capabilities.
  • Masters in Geospatial Science and Technology
  • Mission
  • The mission of the Master in Geospatial Science and Technology is to provide students thorough understanding of the technologies, quantitative techniques, models and theories used to acquire and manage geo-referenced information, and the essential foundation for analyzing geospatial process.
  • Masters in Geospatial Science and Technology
  • Objective
  • The Master in Geospatial Science and Technology aims to meet the following objectives:

    1. To serve, at the highest level, as an education and research center in Geomatic Sciences and Geospatial computing in Puerto Rico.
    2. To contribute to the reorganization and creation of policies that may benefit by the application of Geomatic techniques.
    3. To prepare high quality professionals; who are able to contribute to social and economic development.
    4. To provide society with professionals who are able to contribute to Geomatic Sciences education and research.
    5. To provide professionals with the capacity to generate research and development initiatives in the industrial field.
  • Masters in Geospatial Science and Technology
  • Outcomes
  • under construction
  • Masters in Geospatial Science and Technology
  • Curriculumn
  • Core – (12 credits)

    GEOM 6630 ‐ Geospatial Modeling & Analysis (3 credits)
    GEOM 6632 – Spatial Database Management Systems (3 credits)
    GEOM 6710 ‐ Image Acquisition, Analysis and Processing (3 credits)
    GEOM 6634 ‐ Cartography, Map Design & Geovisualisation (3 credits)


    Geospatial Technology Specialization (9 Credits)

    GEOM 6712 ‐ Advanced Image Analysis and Processing (3 credits)
    GEOM 6636 ‐ Spatial Data Quality (3 credits)
    GEOM 6638 ‐ Geospatial Programming Fundamentals (3 credits)


    Applications – (9 Credits – Select from the following)

    GEOM 6640 ‐ Geospatial Urban and Regional Applications (3 credits)
    GEOM 6642 ‐ Land Information Systems Design and Implementation (3 credits)
    GEOM 6520 ‐ GNSS for Geospatial Professionals (3 credits)
    GEOM 6644 ‐ Web Mapping Applications (3 credit)
    GEOM 6646 – Environmental Assessment and Geospatial Technology (3 credits)
    GEOM 6648 – Business Geography (3 Credits)


    Research

    GEOM 6680 ‐ Research Design and Methods (3 credits)
    GEOM 6690 ‐ Applied Geomatics Research (3 credits)
    GEOM 6691 ‐ Applied Geomatics Research Extension (0 credit) (If necessary)
  • Masters in Geospatial Science and Technology
  • Graduation Requirements
  • The degree must be approved with 36 credits at a 3.00 GPA or higher. Course distribution as follows:

    Core ‐ 12 Credits
    Geospatial Technologies – 9 Credits
    Geospatial Applications – 9 Credits
    Research – 6 Credits
  • Masters in Geospatial Science and Technology
  • Course Sampling

  • POLYTECHNIC UNIVERSITY OF PUERTO RICO
    GEOMATIC SCIENCE DEPARTMENT

    GEOM 6630 – Geospatial Modeling & Analysis

    2012 Catalog Data: Three credit hours. One, four hours lecture per week.
    Pre requisite: GEOM 5600 or undergraduate course in Geographic Information Systems and MGM 5700 or undergraduate course in Statistics.

    Description: Modeling of spatial data and data analysis most useful to professionals who use spatial data. Course provides the student with more advanced methods with an emphasis on practical techniques for problem solving.

    Textbook: Michael J. De Smith. Michael F. Goodchild, and Paul A. Longley, (2011) Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools, Third Edition. (Web version at http://www.spatialanalysisonline.com/output/)

    Reference: David L .Verbyla, (2002) Practical GIS Analysis. CRC Press. Print ISBN: 978-0-415-28609-1 eBook ISBN: 978-0-203-21793-1


    Course Objectives:

    After course completion student will be able to:
    Understand and critically review geographical research literature that employs analysis techniques & methods.
    Recognize which method should be utilized when a real-world situation calls for some sort of geospatial analysis.
    Apply common quantitative methods to describe, analyze and interpret geospatial data sets.
    Gain hands-on practice and skills in using computer software to conduct quantitative analysis.
    Course Topics:
    1. Overview: techniques and methods in geographical research
    2. Spatial Analysis fundamentals
      1. a. Geometric Operations
      2. b. Queries
      3. c. Distance Operations
      4. d. Directional Operations
      5. e. Grid Operations
    3. Data Exploration and Spatial Statistics
      1. a. Statistical Methods
      2. b. Exploratory Spatial Data Analysis
      3. c. Grid based statistics
      4. d. Point pattern
      5. e. Spatial autocorrelation
      6. f. Regression Methods
    4. Surface analysis
      1. a. Introduction
      2. b. Surface geometry
      3. c. Visibility
      4. d. Watersheds
    5. Locations analysis
      1. a. Networks
      2. b. Location and service areas
    6. 6. Geospatial modeling

    Educational Strategies:
    There will be different educational strategies used to teach the course. Among them could be mentioned conference, independent work, collaborative learning, teamwork and research. Individual work capabilities of individual work and will be developed through the work in assignments and preparation of technical papers. Teamwork and collaborative learning skills will be encouraged and evaluated through projects and effective collaboration of groups of students. Students will be train to do independent work and research and to make effective technical presentations.

    Assessment:
    Assessment will be explicit and implicit – graded lab exercises/activities and exams, participation points, and through ungraded self-assessments (which may serve as fodder for discussion forums). Assessment material will draw from textbook and other reading materials, lessons, and lab exercises/activities. The content will necessarily overlap and emphasize key concepts, however, it is critical that student diligently accomplish all weekly tasks.

    Activities:
    Activities are highly variable and may require students to download and use application-specific freeware/data from the Internet, read and report on a chosen article, discuss concepts discussion forums or research information on the Internet. Among principal activities are:

    1. Lecture and associated reading material
    2. Exercise/Lab activities
    3. Chat Room Discussions and Thought Questions – expected participation several times per week

    Technology use:
    This course makes use of diverse Geospatial software. Among them ESRI's ArcGIS and PCI Geomatica. Software is available in the GIS and the computer lab. Open Source used in courses such as Quantum GIS, GRASS or MapWindow are freely avalilable on their respective web sites. For computer requirements consult respective web site.


    Course materials will be posted on Blackboard. To access Blackboard you will need your ID and Password. Blackboard is located at: virtualcampus.pupr.edu

    Web Resources:



    Bibliography:

    Abdul-Rahman, A., & Pilouk, M. (2008). Spatial data modelling for 3D GIS. Berlin ; New York: Springer.
    Albrecht, J. (2007). Key concepts & techniques in GIS. Los Angeles [i.e. Thousand Oaks, Calif.]: SAGE Publications.
    Atkinson, P. M. (2005). GeoDynamics. Boca Raton: CRC Press.
    Atkinson, P. M., & Martin, D. (2000). GIS and geocomputation. London ; New York: Taylor & Francis.
    Batty, M., & Longley, P. (1996). Spatial analysis : modelling in a GIS environment. Cambridge
    Batty, M., University College London. Centre for Advanced Spatial Analysis, & Longley, P. (2003). Advanced spatial analysis : the CASA book of GIS. Redlands, Calif.: ESRI Press.
    Berry, J. K. (1995). Spatial reasoning for effective GIS. Fort Collins, Colo.: GIS World Books.
    Campari, I., & Frank, A. U. (1993). Spatial information theory : a theoretical basis for GIS : European conference, COSIT'93, Marciana Marina, Elba Island, Italy, September 19-22, 1993 : proceedings. Berlin ; New York: Springer-Verlag.
    Christakos, G., Serre, M. L., & Bogaert, P. (2001). Temporal GIS: advanced functions for field-based applications. Berlin ; New York: Springer.
    Clarke, G., & Stillwell, J. C. H. (2004). Applied GIS and spatial analysis. Chichester, West Sussex, England ; Hoboken, NJ: Wiley.
    DeMers, M. N. (2002). GIS modeling in raster. New York [Chichester]: Wiley.
    Elwood, S., & Cope, M. (2009). Qualitative GIS: a mixed methods approach. Los Angeles ; London: SAGE.
    Fischer, M. M., European Science Foundation., Unwin, D., & Scholten, H. J. (1996). Spatial analytical perspectives on GIS. London ; Bristol, PA: Taylor & Francis.
    Fisher, P. F., & Unwin, D. (2005). Re-presenting GIS. Chichester, England ; Hoboken, NJ: John Wiley & Sons.
    Formentini, U., Campari, I., & Frank, A. U. (1992). Theories and methods of spatio-temporal reasoning in geographic space. Berlin ; New York: Springer-Verlag.
    Frank, A. U., & Hirtle, S. C. (1997). Spatial information theory : a theoretical basis for GIS : international conference COSIT '97, Laurel Highlands, Pennsylvania, USA, October 15-18, 1997 : proceedings.
    Berlin ; New York: Springer.
    Goodchild, M. F. (1996). GIS and environmental modeling : progress and research issues. Fort Collins, CO: GIS World Books.
    Griffith, D. A., & Arlinghaus, S. L. (1996). Practical handbook of spatial statistics. Boca Raton: CRC Press.
    Lee, J., & Wong, D. W. S. (2001). Statistical analysis with ArcView GIS. New York ; Chichester [England]: John Wiley.
    Lloyd, C. D. (2010). Spatial data analysis : an introduction for GIS users. Oxford ; New York: Oxford University Press.
    Maguire, D. J., Goodchild, M. F., & Batty, M. (2005). GIS, spatial analysis, and modeling (1st ed.). Redlands, Calif.: ESRI Press.
    Malczewski, J. (1999). GIS and multicriteria decision analysis. New York: J. Wiley & Sons.
    Molenaar, M. (1998). An introduction to the theory of spatial object modelling for GIS. London ; Bristol, PA: Taylor & Francis.
    National Academies Press (U.S.), & ebrary Inc. (2006). Learning to think spatially (pp. xviii, 313 p.).
    Pilz, J. U. b. r., & SpringerLink (2009). Interfacing Geostatistics and GIS
    Verbyla, D. L. (2002). Practical GIS analysis (pp. ix, 294 p.).
    Wang, F. (2006). Quantitative methods and applications in GIS (pp. 265 p.).
    Wong, D. W. S., & Lee, J. (2005). Statistical analysis of geographic information with ArcView GIS and ArcGIS (Fully rev. & updated. ed.). Hoboken, N.J.: John Wiley & Sons
    Worboys, M., & Duckham, M. (2004). GIS : a computing perspective (2nd ed.). Boca Raton, Fla.: CRC Press.

    Classroom Policies

    Reasonable Accommodation
    A student with a disability must file a request for course accommodation at the beginning of each trimester or as soon as the need arises. Visit the Guidance and Counseling Office to follow the established institutional procedures for petitioning reasonable accommodation. The start-date for providing reasonable accommodation shall be when the student submits notification to the instructor; this does not apply retroactively as established by law. For more information, go to: www.pupr.edu/spi.

    Academic Honesty, Fraud and Plagiarism
    Acts of dishonesty, fraud and plagiarism, and other inappropriate behaviors regarding academic work are major infractions sanctioned by the Student Regulations. Major infractions, as stipulated in the Student Regulations, may result in suspension or expulsion from the University.

    Using Electronic Devices
    All cell phones and other electronic devices must be deactivated before entering class to guarantee excellence in the teaching and learning environment. Urgent situations should be addressed, as appropriate. The University bans the operation of electronic devices that provide access, storage or data transfer during assessments or examinations.


    Syllabus- GEOM 6630 - Geospatial Modeling & Analysis ©Copyright PUPR

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