Servizi per la didattica
PORTALE DELLA DIDATTICA

Environmental Spatial Analysis

04SQZNW, 04SQZNW, 05SQZQA

A.A. 2023/24

Course Language

Inglese

Course degree

Master of science-level of the Bologna process in Petroleum And Mining Engineering (Ingegneria Del Petrolio E Mineraria) - Torino
Master of science-level of the Bologna process in Georesources And Geoenergy Engineering - Torino
Master of science-level of the Bologna process in Pianificazione Territoriale, Urbanistica E Paesaggistico-Ambientale - Torino

Course structure
Teaching Hours
Teachers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Teaching assistant
Espandi

Context
SSD CFU Activities Area context
ICAR/01
ICAR/06
ING-IND/30
1
4
1
D - A scelta dello studente
D - A scelta dello studente
D - A scelta dello studente
A scelta dello studente
A scelta dello studente
A scelta dello studente
Valutazione CPD 2021/22
2022/23
The aim of the course is to introduce and describe some basic Geomatics techniques for data acquisition and the methodologies in order to develop basic understanding of spatially referenced data analysis and to explore the potential of Geographic Information Systems application in environmental and social studies. The course builds up on the practical skills related to climate change, geospatial data mining and mapping. It also offers more detailed discussion and wider range of geospatial data visualization methods and introduces quantitative analysis of geospatial phenomena. Besides, the course aims at providing both a theoretical understanding and a practical introduction to the use of Geomatics technologies for monitoring and analysis of environmental problems. Students are exposed to the basic techniques and practical skills of extracting relevant information also from digital imagery. Educational Approach: The course consists of computer class-based instructor presentations, supervised in-class exercises, individual consultations and a major individual term project. The course is based on "learn-by-doing" approach: basic approaches and principles presented by instructors during laboratory-based classes will be accompanied by students' extensive individual work. Some outdoor activities will be carried out for improving the practical skill of the students and for applying what they have studied during the lessons.
The course aims to introduce and describe some basic Geomatics techniques for data acquisition and the methodologies to develop a basic understanding of spatially referenced data analysis and to explore the potential of Geographic Information Systems application in environmental and social studies. The course builds upon the practical skills related to climate change, geospatial data mining and mapping. It also offers a more detailed discussion and a wider range of geospatial data visualization methods and introduces quantitative analysis of geospatial phenomena. Besides, the course aims to provide both a theoretical understanding and a practical introduction to the use of Geomatics technologies to monitor and analyse environmental problems. Students are exposed to the basic techniques and practical skills of extracting relevant information also from digital imagery. Educational Approach: The course consists of computer class-based instructor presentations, supervised in-class exercises, individual consultations and a major individual term project. The course is based on the "learn-by-doing" approach: students' extensive individual work will accompany basic approaches and principles presented by instructors during laboratory-based classes. Some outdoor activities will be carried out to improve the students' practical skill and apply what they have studied during the lessons.
In this course, the students will learn: • Basic concepts about data acquisition techniques • Basic concepts about statistics • Theory of spatial analysis • Correlation and probability estimation • Interpolation methods • Filtering techniques After attending the course, students will be able to: • Select the appropriate technique for data acquisition according to the selected purposes • Process and interpret the collected data • Describe and characterize one sample with the main statistical parameters • Estimate correlation between variables or parameters • Use the appropriate interpolation method as function of the considered problem • Apply different filtering techniques The lab activities deal with the environmental spatial analysis using climate change, hydraulic/hydrologic and petroleum data.
In this course, the students will learn: • Basic concepts about data acquisition techniques • Basic concepts about statistics • Theory of spatial analysis • Correlation and probability estimation • Interpolation methods • Filtering techniques After attending the course, students will be able to: • Select the appropriate technique for data acquisition according to the selected purposes • Process and interpret the collected data • Describe and characterize one sample with the main statistical parameters • Estimate correlation between variables or parameters • Use the appropriate interpolation method as a function of the considered problem • Apply different filtering techniques The lab activities deal with the environmental spatial analysis using climate change, hydraulic/hydrologic and petroleum data.
Pre-requisites are basic knowledge of geological and hydrogeological concepts, computing and geospatial data acquisition and visualization techniques.
Pre-requisites are basic knowledge of geological and hydrogeological concepts, computing and geospatial data acquisition and visualization techniques.
The program is divided into 5 modules of lectures, for a total duration of 60 hours, and a series of laboratories and outdoor activities. DELIVERY MODES Lessons (30 h): Module 1: How to represent and collect data. The importance of reference systems and why is important to select a proper reference system will be described in order to perform correct analyses from spatial data. Some different Geomatics techniques will be described as possible methods to collect data in a direct way or for extracting secondary information (e.g. the precipitable water vapour from GNSS measurements). Module 2: Basic concepts of theory of observations Definitions of basic concepts on measurement and estimation of a random 1D/2D variable, mean, median, standard deviation, probability density function (PDF), cumulative density function (CDF). In this module, some aspects about the measurement of real objects and statistical interpretation are considered. Moreover, it will focused the attention on correlation, accuracy and precision concepts. Module 3: The interpolation/approximation methods The interpolation methods play a crucial role in environmental spatial analysis. Different interpolation techniques such as IDW, correlogram, variogram, different Kriging (simple, universal, linear, co-Kriging) methods will be deeply analyzed and considered, focusing the attention on different kinds of applications especially related to petroleum and hydrological activities. Module 4: Data visualization and interpretation Basic concepts related to GIS/database Design procedure will be provided. The modelling procedure, external model, conceptual model (Entity/Relationship), logical model (Relational DB), internal model, cardinality, basic rules for data modelling (complex attributes, multi-values fields), 3D GIS support and visualization Digital Terrain model and digital Surface model Definition of DTM and DSM, contents (point cloud, breaklines, dead zone, …), dense model, irregular (TIN) and regular grids, estimation of surface parameters (slope, aspect, contour lines, curvature,…), visibility analysis (line of sight, skyline, viewshade, observer, …) Module 5: Filtering, model building and inversion techniques. In this module, different filtering techniques (e.g. low-pass/high pass filter) and inverse problems will be considered, especially considering hydraulic and petroleum applications. During geological modelling, for instance, it is frequent the use of filtering techniques on well log data in order to identify characteristics of the log electrical signals, improve stratigraphic correlation or remove unwanted parts of the registration. On 2D or 3D datasets (e.g. maps, distributed petrophysical values) filters can be applied in order to identify the contribution of each spatial component of a given property, remove/enhance property features or calculate trends used during petrophysical distribution. During the lesson different filtering techniques are going to be presented and analyzed that are commonly used during well data analysis and 3D geological modelling. Lab activities (30 h): The lab activities take about half of the course and are focused on themes considered during the lessons. Specific applications will be done using Geomatics and GIS software especially for geospatial analysis, focusing on analysis tools, 3D data, working with rasters, projections, and environment variables. The works are carried out in team; finally, a special report must be completed.
The program is divided into 5 modules of lectures, for a total duration of 60 hours, and a series of laboratories and outdoor activities. DELIVERY MODES Lessons (30 h): Module 1 (5h): How to represent and collect data. The importance of reference systems and why it is important to select a proper reference system will be described to perform correct analyses from spatial data. Some different Geomatics techniques will be described as possible methods to collect data in a direct way or for extracting secondary information (e.g. the precipitable water vapour from GNSS measurements). Module 2 (5h): Basic concepts of the theory of observations Definitions of basic concepts on measurement and estimation of a random 1D/2D variable, mean, median, standard deviation, probability density function (PDF), cumulative density function (CDF). In this module, some aspects of the measurement of real objects and statistical interpretation are considered. Moreover, it will focus the attention on correlation, accuracy and precision concepts. Module 3 (10h): The interpolation/approximation methods The interpolation methods play a crucial role in environmental spatial analysis. Different interpolation techniques such as IDW, correlogram, variogram, different Kriging (simple, universal, linear, co-Kriging) methods will be deeply analyzed and considered, focusing the attention on different kinds of applications especially related to petroleum and hydrological activities. Module 4 (5h): Data visualization and interpretation Basic concepts related to the GIS/database Design procedure will be provided. The modelling procedure, external model, conceptual model (Entity/Relationship), logical model (Relational DB), internal model, cardinality, basic rules for data modelling (complex attributes, multi-values fields), 3D GIS support and visualization Digital Terrain Model and Digital Surface model Definition of DTM and DSM, contents (point cloud, breaklines, dead zone, …), dense model, irregular (TIN) and regular grids, estimation of surface parameters (slope, aspect, contour lines, curvature,…), visibility analysis (line of sight, skyline, viewshade, observer, …) Module 5 (5h): Filtering, model building and inversion techniques. In this module, different filtering techniques (e.g. low-pass/high pass filter) and inverse problems will be considered, especially considering hydraulic and petroleum applications. During geological modelling, for instance, it is frequent the use of filtering techniques on well log data to identify characteristics of the log electrical signals, improve stratigraphic correlation or remove unwanted parts of the registration. On 2D or 3D datasets (e.g. maps, distributed petrophysical values), filters can be applied in order to identify the contribution of each spatial component of a given property, remove/enhance property features or calculate trends used during petrophysical distribution. During the lesson, different filtering techniques will be presented and analyzed that are commonly used during well data analysis and 3D geological modelling. Lab activities (30 h): The lab activities take about half of the course and are focused on themes considered during the lessons. Specific applications will be made using Geomatics and GIS software, especially for geospatial analysis, focusing on analysis tools, 3D data, working with rasters, projections, and environment variables. The works are carried out in a team; finally, a special report must be completed.
The course is divided in 30h of lessons and 30h of lab activities, including outdoor sessions.
The course is divided into: - 30h of lessons, where the students can learn basic concepts about data acquisition techniques, statistics, theory of spatial analysis - 30h of lab activities, including outdoor sessions, where the students can apply statistical techniques to real data, considering correlation and probability estimation, interpolation methods and filtering techniques
The main text consists of the lecture notes provided by the teacher and slides presented during the classes.
The main text consists of the lecture notes and slides provided during the course and presented during the classes, available on the teaching website. The teachers will provide this material. Suggested books: - De Marsily, G. (1986). Quantitative hydrogeology. Paris School of Mines, Fontainebleau. - Ricardo Olea https://web.archive.org/web/20170217202826/https://pubs.usgs.gov/of/2009/1103/of2009-1103.pdf - Hofmann-Wellenhof et al (2008) – GNSS Global Navigation Satellite system. Springer – New York.
Modalità di esame: Prova orale obbligatoria; Elaborato scritto prodotto in gruppo;
Exam: Compulsory oral exam; Group essay;
The exam consists of 3 parts: 1. a discussion of exercises on the entire process of environmental spatial analysis with theoretical subjects (vote/30) 2. a discussion of exercises on hydraulic problems made during practical activities (vote/30) 3. a discussion of exercises on petroleum engineering made during practical activities (vote/30). The final grade is a weighted average of the results of the 3 previous evaluations with weights: P1=0.50, P2 =0.25, P3=0.25.
Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
Exam: Compulsory oral exam; Group essay;
The exam consists of an oral interview of about 30 minutes, and it is composed of 3 parts: 1. a discussion of exercises on the entire process of environmental spatial analysis with theoretical subjects (vote/30) 2. a discussion of exercises on geostatistics and filtering problems made during practical activities (vote/30) 3. a discussion of exercises on basic statistics and interpolation data made during practical activities (vote/30). The final grade is a weighted average of the 3 previous evaluations with weights: P1 = 0.50, P2 = 0.25, P3 = 0.25. Each student must deliver a mandatory group report (max 4 students per group) on the laboratory activities developed during the course. This report will be evaluated on a score range from 0 to +2. These points will be added to the evaluation of the oral exam. The assessment will consider the ability of students to solve the task required by the lab activities, completeness of the work performed, the quality of the report itself (organization of the content, quality of the figures, the correctness of the solution etc..) and the methodology employed. The report must be uploaded in the "Elaborati" section of the "Portale della didattica" within one week before the exam date.
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.
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