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.

General characterization





Responsible teacher

Ana Cristina Marinho da Costa


Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English


Not applicable.


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.

Teaching method

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.

Evaluation method

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.

Subject matter

The curricular unit is organized in four Learning Units (LU):

LU1. Exploratory data analysis

LU2. Deterministic methods

LU3. Kriging

LU4. Geographically Weighted Regression