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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. The master program will expose the student to the principles and techniques related to geospatial data model generation, data capture and representation, and will learn how these could help in the solution of different problems faced by society. By its integrative nature, the program will support research and application modeling in diverse disciplines such as Land Surveying, Architecture, Planning, Geography, Environmental Management, Biology, and Engineering, among others.Sign up for more info!
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 includes three different technologies that are all related to mapping features on 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 generation, data capture and representation, and will learn how these could help in the solution of different problems faced by society. By 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
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 the 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 insurance market. It is expected that many students are professionals in various fields who seek to add to their profession geospatial data management capabilities.
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.
The Master in Geospatial Science and Technology aims to meet the following objectives:
- To serve, at the highest level, as an education and research center in Geomatic Sciences and Geospatial computing in Puerto Rico.
- To contribute to the reorganization and creation of policies that may benefit by the application of Geomatic techniques.
- To prepare high quality professionals; who are able to contribute to social and economic development.
- To provide society with professionals who are able to contribute to Geomatic Sciences education and research.
- To provide professionals with the capacity to generate research and development initiatives in the industrial field.
The structure and sequence of the curriculum include blocks of courses classified as Core, Advanced, Geospatial Applications and Research Project.
This block of courses provides the knowledge in four fundamental areas of geospatial science and technologies. These are Geographic Information Science, Remote Sensing, Cartography and Spatial Database Management. The core courses total 12 credit-hours, distributed among 4 courses of three credit-hours each.
Advanced courses are designed to provide specialized preparation in geospatial science and technologies. Advanced courses total 9 credit-hours, distributed among 3 courses of three credit-hours each.
Students select courses related to their research interest. The idea is to reinforce geospatial research techniques on particular study areas. The student should select a total of 9 credit-hours, distributed among 3 courses of three credit-hours each.
The student must prepare a proposal for his/her Master Research Project once approved 18 credits and taken the Research Design and Methods course (GEOM 6680). The proposal must be approved by the student advisor. The student must conduct the Master Research Project under the supervision of the advisor, who is the chairperson.
Through the Master Research Project, students must demonstrate expertise of geospatial science and techniques, and the ability to apply them in a cohesive. The Master Research Project can be an application to a real case or situation. The application must prove originality and contribution to the field of Geospatial Science.
At completion, the student must submit a technical article of the Master Research Project to the Graduate School. As a final requirement, the Master Research Project will be presented at the Graduate School Design Project Expo.
The technical article should follow the publication rules established by the Graduate School of the Polytechnic University of Puerto Rico.
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)
GEOM 6712 ‐ Advanced Image Analysis and Processing (3 credits)
GEOM 6636 ‐ Spatial Data Quality (3 credits)
GEOM 6638 ‐ Geospatial Programming Fundamentals (3 credits)
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)
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)
General requirements for admission to the program are established by the Graduate School. In addition it is expected that the student has a 2.75 GPA in the bachelor degree that gives access to the program. If the candidate has a GPA lower than 2.75 he/she can request admission thru the Reconsideration Committee of the Graduate School.
Admission of any applicant to the program will be based on academic preparation. Qualified persons with a bachelor degree from a recognized and accredited university or college, who have approved credits in Geographic Information Systems (GIS) and Statistics, may be admitted directly to the program. Evidence of having these approved courses will be demonstrated through the submission of the transcript of the degree in question. The Graduate School will evaluate the applicants program’s qualifications to determine if he/she is admitted to the program directly. Applicants who do not have these courses will be required to take them as pre-requisites to the master’s program.
Students in the Graduate Program in Geospatial Science and Technology earn a Master in Geospatial Science and Technology.
The degree must be approved with 36 credits at a 3.00 GPA or higher. Course distribution is as follows:
Core – 12 Credits
Geospatial Technologies – 9 Credits
Geospatial Applications – 9 Credits
Research – 6 Credits
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
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.
1. Overview: techniques and methods in geographical research
2. Spatial Analysis fundamentals
a. Geometric Operations
c. Distance Operations
d. Directional Operations
e. Grid Operations
3. Data Exploration and Spatial Statistics
a. Statistical Methods
b. Exploratory Spatial Data Analysis
c. Grid based statistics
d. Point pattern
e. Spatial autocorrelation
f. Regression Methods
4. Surface analysis
b. Surface geometry
5. Locations analysis
b. Location and service areas
6. Geospatial modeling
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 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 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:
- Lecture and associated reading material
- Exercise/Lab activities
- Chat Room Discussions and Thought Questions – expected participation several times per week
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
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 : 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 : 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 : 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.
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.
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.
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
Acosta Hernández, Javier Lecturer, MSc. Open Information Computer Systems, Interamerican University of Puerto Rico, 2008. BSc. Civil Engineering, University of Puerto Rico Mayaguez Campus, 1992.
Cuadrado Landrau, Víctor Lecturer, MSc. Geoinformation, International Institute for Geo-Information Science and Earth Observation (ITC), Enshede, The Netherlands, 2002. B.A. Geography, University of Puerto Rico, 1998.
León Licier, Anabelle Lecturer, MSc Public Health, University of Puerto Rico School of Medical Sciences, 2009. B.A. Geography, University of Puerto Rico, 2005.
Matos Flores, Raúl – Associate Professor, Ph.D. (Candidate), Cartography, GIS and Remote Sensing, Universidad de Alcalá, Madrid, 2012; Msc. Geographic Information Systems, Huddersfield University, Great Britain, 2002; Master in Planning, Concentration: Urban Planning, University of Puerto Rico, 1997; B.A. Geography, University of Puerto Rico, 1991.
Romero González, Victor M. Assistant Professor; Ph.D. (Candidate) Topographic Engineering and Photogrammetry, Universidad Politécnica de Madrid, 2004; B.S. in Land Surveying, Polytechnic University of Puerto Rico, 1994.
Villalta Calderón, Christian A. Assistant Professor, Ph.D. in Civil Engineering, University of Puerto Rico, Mayagüez Campus, 2009; M.S.C.E., University of Puerto Rico, Mayagüez Campus, 2004; B.S.C.E. University of Costa Rica, 2001.
Martha Dumois, Ph.D.
Graduate Program Director
Phone: 787-622-8000 x. 686
The Geomatic Sciences Department offers students the opportunity to receive hands on experience, practice the concepts and techniques learned in the classroom allowing them the best opportunity to acquire current knowledge and the expertise the industry demands. In order to fulfill this commitment, these laboratories have been designed to cover all major areas of Geomatic Sciences. The Geomatic Science Department has the following laboratory facilities on campus: Geographic Information Systems Laboratory, Remote Sensing and Photogrammetry Laboratory, Surveying and Topography Laboratory and a General Computer Laboratory. These laboratories have been designed to perform a wide range of applications in each of the areas of interest.
This lab is used primarily for GIS and Cartography practice. It has several Dell Precision T5500 and Precision model T5400 workstations. It has different types of software for GIS development and geospatial analysis such as ArcGIS 10, FME, IDRISI and Manifold. Open source software is also used for educational purposes. It also has general applications software such as Microsoft Office and Open Office.
This laboratory is used for Remote Sensing and Photogrammetry related practice. It has several Dell Precision model T5500, T5400 Precision and OptiPlex 745 workstations. It has PCI Geomatics software for work in remote sensing and photogrammetry. Open source software is also used for educational purposes. It also has general application software such as Microsoft Office.
This laboratory is used for practices and courses on Surveying and Topography. It has several Dell Precision T5400 workstations. It has the AutoCAD software, Carlson Survey, Mr. CAD, AutoCAD Map and general purpose software like Microsoft Office. The Department also has surveying equipment such as Total Stations and Levels (Topcon, Leica, and South Survey). There are also Topcon GPS receivers (GR3, GMS2, and Hyper) and Trimble GPS receivers.
This lab is available for general use projects and assignments. The laboratory has several Dell Precision T5500 and two Dell T5400 workstations. It has a page layout of 8.5 X 11 inches. In addition to the aforementioned equipment, the lab has software licenses of all the instructional software found in departmental laboratories. There is also general use software such as Microsoft Office and Open Office.