Geo-Statistics
Code
200050
Academic unit
NOVA Information Management School
Credits
7.5
Teacher in charge
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Objectives
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.
Prerequisites
Not applicable.
Subject matter
1. Exploratory data analysis
1.1. Introduction
1.2. General concepts on data description
1.3. Exploratory Spatial Data Analysis (ESDA) tools
2. Deterministic methods
2.1. General concepts on spatial interpolation
2.2. Thiessen polygons (Voronoi maps)
2.3. IDW - Inverse distance weighting
2.4. Validation and cross-validation
3. Kriging
3.1. Spatial continuity analysis
3.2. Variography
3.3. Geostatistics estimation concepts
3.4. Univariate kriging
4. Geographically Weighted Regression
4.1. General concepts on regression analysis
4.2. OLS - Ordinary Least Squares
4.3. GWR - Geographically Weighted Regression
Bibliography
- 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
This curricular unit is lectured through the e-learning platform using synchronous tools (videoconference classes with the teacher) and asynchronous tools (forum, email, learning materials available in the e-learning platform). There will be a synchronous session at the end of each Learning Unit (LU). This corresponds to a 2-hour online class with the teacher, which will be dedicated to the content of each LU and to the solving of practical exercises described in the tutorials. A random set of self-evaluation exercises is available for each Learning Unit, in the e-learning platform. Students can try to answer to the self-evaluation exercises as many times as they wish.
Evaluation method
1. Exam (20% of final grade);
2. Individual report of the project (65% of final grade);
3. Oral presentation of the project (15% of final grade).