The objective of this curricular unit is to teach the students the basic concepts of standard geostatistics and spatial statistics. Students will learn the main theoretical concepts related to the spatial interpolation of attributes using deterministic methods and geostatistics procedures, which are based on the spatial autocorrelation of the observed data. Students will also learn the theoretical background of spatial regression and how to set up and carry out standard spatial exploratory and regression analyses. The students will work on computer programs to practice the theoretical concepts. Students are expected to evaluate the potential of spatial statistics for their own research.
Ana Cristina Marinho da Costa
Weekly - Available soon
Total - Available soon
Portuguese. If there are Erasmus students, classes will be taught in English
Tutorials and other material provided by the teachers.
Deutsch, C. V.; Journel, A. G., 1998. Geostatistical Software Library and User’s Guide. Oxford University Press, New York, USA.
Goovaerts, P., 1997. Geostatistics for Natural Resources Evaluation. Oxford University Press, Inc, New York, USA.
Isaaks, E. H.; Srivastava, R. M., 1989. An Introduction to Applied Geostatistics. Oxford University Press, Inc, New York, USA.
Fotheringham A.S., Brunsdon C., Charlton M. (2002) Geographically Weighted Regression: the analysis of spatially varying relationships. Wiley, Chichester, UK.
Soares, A. 2000. Geoestatística para as Ciências da Terra e do Ambiente. Instituto Superior de Técnico, IST Press. Lisboa, Portugal.
The curricular unit is based on theoretical lectures and practical application of methods using software applications, such as Excel and ArcGIS. A variety of instructional strategies will be applied, including lectures, slide show demonstrations, step-by-step tutorials on using the tools and techniques in the ArcGIS software, questions and answers. The practical component is geared towards solving problems and exercises, including discussion and interpretation of results.
1. Two individual reports with the answers to the proposed problems (15% of final grade the first one, and 10% the second one);
2. Exam (30% of final grade);
3. Oral presentation of the project (10% of final grade);
4. Report of the project (35% of final grade).
The project can be developed individually or in groups of 2 students.
The curricular unit is organized in four Learning Units (LU):
LU1. Exploratory data analysis
LU2. Deterministic methods
LU4. Geographically Weighted Regression
Programs where the course is taught:
- Master degree program in Geospatial Technologies
- Master of Geographic Information Systems and Science
- PostGraduate in Smart Cities
- PostGraduate in Geographic Information Systems and Science
- PostGraduate in Information Systems Governance
- PostGraduate in Information Management and Business Intelligence in Healthcare
- PostGraduate in Enterprise Information Systems