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SPATIAL VARIABILITY OG GEOLOGICAL AND CLIMATIC DATA Single discipline educational activity
Course Sheet Academic Year of enrolment:
Professor and Collaborators:
Hours of classroom activity:
Prerequisites:
Basic knowledge of statistics (mean, variance, covariance) and mathematical analysis. The concept and use of function, equation and system of equations are required.
Objectives
Contents 1) Introduction to spatial analysis;
2) Recalls of traditional statistics
3) Stochastic approach to spatial analysis;
4) Modelling of spatial dependence;
5) Punctual Kriging;
6) Block Kriging and measurement support;
Extended Syllabus 1) Types of variability. Assessment of variability. Jenny’s and Scorpan models;
2) Traditional cartographic approach. Delineation in homogeneous areas. Principles on which the traditional approach is based;
3) Traditional statistical model of spatial variability. Assumptions of normality and independence of errors;
4) Calculation of basic statistics. Fitting of a mathematical model;
5) Pros and cons of the traditional approach. Need for an alternative approach. Illustration of a case study;
6) Classification of the causes of variation. Comparison between traditional and modern approach;
7) Recalls of the traditional approach and its limitations compared to the stochastic approach;
8) Improvement of the new approach compared to the traditional one. New model of spatial prediction. Basic principles of the theory of regionalized variables;
9) Definition of stochastic variables. Definitions and formalism related to stochastic variables. Concepts of first and second order stationarity and intrinsic stationarity;
10) Definition and calculation of the experimental variogram. Omnidirectional and directional variograms. Characteristic parameters of the theoretical variogram;
11) Fitting of an authorized mathematical model to the experimental variogram. Various types of authorized models and their characteristics;
12) Definition of anisotropy. Geometric and zonal anisotropy. Mathematical treatment of different types of anisotropy;
13) Need for an estimate of the error. Definition of simple and Ordinary Point Kriging. Derivation of the Kriging system. Calculation of the variance of Kriging estimation;
14) Properties of Point Kriging. Display of Kriging weights and definition of interpolation neighbourhood. Limitations of Point Kriging;
15) Definition of Block Kriging. Concept of Support. Derivation of Block Kriging system. Calculation of the mean variogram (regularization). Differences between Point and Block Kriging;
16) Definition of Polygon Kriging. Statistical comparison between polygons. Suggestions on the choice of support. Cross Validation. Hybrid methods. Local Kriging.
Recommended Bibliography - “Introduction to Spatial Analysis”. A. Castrignanò. Aracne Editrice, 2011.
- “Analisi Spaziale mediante tecniche geostatistiche”. A. Castrignanò, G. Buttafuoco. Notes not published, 2004.
- “Agricultural Internet of Things and Decision Support for precision Smart Farming”. Edited by A. Castrignanò, B. Buttafuoco, R. Khosla, A.M. Mouazen, D. Moshou, O. Naud. AP., 2020.
- PowerPoint lecture presentations held in the classroom.
Teaching Methods The teaching includes theoretical classroom lessons of 2/4 hours alternating with individual computer sessions with the dedicated Geovariances ISATIS software of 2 hours, in order to applicate with real data what has been learned in theory.
Evaluation methods Verification of learning:
The verification process consists of both written and oral testing.
- The written test involves the compilation of a technical report on the geostatistical analysis with the Geovariances ISATIS software of a sample of spatial data.
- The oral test consists of a discussion of the technical report with clarification of the approach used.
Contacts/More Information There is a 3-hour reception time for students on a day of the week, for further clarification and in-depth study of the work done in the classroom.