Margherita FIANI | REMOTE SENSING TECHNOLOGIES FOR CIVIL AND ENVIRONMENTAL ENGINEERING APPLICATIONS
Margherita FIANI REMOTE SENSING TECHNOLOGIES FOR CIVIL AND ENVIRONMENTAL ENGINEERING APPLICATIONS
| 8802100006 | |
| DEPARTMENT OF CIVIL ENGINEERING | |
| P.H.D. COURSE | |
| RISK AND SUSTAINABILITY IN CIVIL, ARCHITECTURAL AND ENVIRONMENTAL ENGINEERING SYSTEMS | |
| 2020/2021 |
| YEAR OF COURSE 1 | |
| YEAR OF DIDACTIC SYSTEM 2020 | |
| ANNUALE |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| ICAR/06 | 3 | 21 | LESSONS |
| Objectives | |
|---|---|
| EXPECTED LEARNING RESULTS AND COMPETENCE TO ACQUIRE: KNOWLEDGE OF THE PHYSICAL PRINCIPLES OF REMOTE SENSING, ACTIVE AND PASSIVE SENSORS, METHODS AND INSTRUMENTS FOR DATA PROCESSING AND ANALYSIS, WITH REFERENCE TO COMPUTATIONAL ASPECTS AND ENVIRONMENTAL ENGINEERING APPLICATIONS KNOWLEDGE AND UNDERSTANDING SKILLS: ACQUIRE THE KNOWLEDGE OF THE PHYSICAL PRINCIPLES OF REMOTE SENSING AND ON THE SENSORS ON BOARD SATELLITES AND THEIR USE IN THE VARIOUS FIELDS OF ENGINEERING. ACQUIRE THE SKILLS NEEDED TO ANALYZE DATA AND DATA SETS FOR ENVIRONMENTAL APPLICATIONS. ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING: HAVING COMPETENCE AND OPERATIVE AUTONOMY ON TECHNICAL AND MANAGEMENT TASKS. HAVING SKILLS TO MONITOR PHENOMENA THROUGH THE ELABORATION OF REMOTE SENSED DATA. THE DESCRIPTION OF A FEW APPLICATIONS ON CASE STUDIES IN DIFFERENT CONTEXTS WILL BE ESSENTIAL TO APPLY THE KNOWLEDGES ACHIEVED DURING THE THEORETICAL LESSONS. AUTONOMY OF JUDGMENT: TO BE ABLE TO IDENTIFY THE BEST DATA, METHODS AND SOFTWARE FOR THE DIFFERENT APPLICATIONS OF ENVIRONMENTAL REMOTE SENSING. COMMUNICATION SKILLS: BEING ABLE TO USE TECHNICAL LANGUAGE. LEARNING SKILLS: BEING ABLE TO APPLY THE ACQUIRED KNOWLEDGE TO CONTEXTS DIFFERENT FROM THOSE PRESENTED DURING THE COURSE AND BEING ABLE TO MONITOR THE EVOLUTION OF NEW KNOWLEDGE IN THE FIELD. |
| Prerequisites | |
|---|---|
| NONE |
| Contents | |
|---|---|
| THIS COURSE PROVIDES AN OVERVIEW ON PRINCIPLES OF REMOTE SENSING AND ITS INSTRUMENTS FOCUSING ON THE MOST INNOVATIVE MONITORING AND DOCUMENTATION TECHNIQUES OF THE NATURAL OR BUILT ENVIRONMENT. THE COURSE IS ORGANIZED IN THREE MODULES. THE 1ST MODULE PROVIDES BASIC KNOWLEDGE ON THE PHYSICAL PRINCIPLES OF REMOTE SENSING, ACTIVE AND PASSIVE SENSORS, MATHEMATICAL MODELS AND THE MAIN TECHNIQUES FOR DATA PROCESSING. THE 2ND MODULE PROVIDES THE TOOLS FOR THE CONTINUOUS MONITORING OF FRESHWATER ENVIRONMENTS WITH APPLICATION TO RIVERS, WETLANDS AND ARTIFICIAL AND NATURAL LAKES. THE 3RD MODULE PROVIDES AN OVERVIEW OF THE USE AND ASSIMILATION OF GROUND DISPLACEMENT DATA DERIVED FROM THE DIFFERENTIAL INTERFEROMETRIC PROCESSING OF IMAGES ACQUIRED BY DINSAR IN GEOTECHNICAL STUDIES. THE COURSE IS ORGANIZED INTO THREE MODULES. MODULE 1 : TOPOGRAPHIC MAPPING AND TERRAIN MODELING USING SPACEBORNE, UAV AND GROUND-BASED REMOTE SENSING TECHNIQUES. ENVIRONMENTAL APPLICATIONS. LESSON 1 PHYSICAL PRINCIPLES OF REMOTE SENSING. THE ELECTROMAGNETIC SPECTRUM. REMOTE SENSING METHODS: VISIBLE, INFRARED AND MICROWAVE. REMOTE SENSING IMAGES: SPECTRAL, SPATIAL, RADIOMETRIC, AND TEMPORAL RESOLUTIONS. RADIATION LAWS. ACTIVE SENSORS USED IN REMOTE SENSING: RADAR E LIDAR. PASSIVE SENSORS: OPTICAL AND ELECTRO-OPTICAL VIS AND NIR. MAIN APPLICATIONS OF RADAR SENSORS AND INTERFEROMETRIC TECHNIQUES. SATELLITE ORBITS. EARTH OBSERVATION MISSIONS. METHODS OF PROCESSING AND ANALYSIS OF REMOTE SENSING DATA. MATHEMATICAL MODELS FOR GEOREFERENCING OF OPTICAL SATELLITE IMAGES. METHODS OF PRODUCING A DTM. LESSON 2 CARTOGRAPHIC APPLICATIONS OF SATELLITE IMAGE DATA. ALGORITHMS AND TOOLS FOR LIDAR AND UAV DATA PROCESSING. REMOTE SENSING FOR NATURAL HAZARDS ASSESSMENT AND DISASTER RISK MANAGEMENT. MODULE 2 : CONTINUOUS MONITORING OF FRESHWATER ENVIRONMENTS FOR OPTIMIZED PROTECTION, RESTORATION AND MANAGEMENT LESSON 1 DESCRIPTION OF SATELLITE MONITORING TOOLS. FREE DATASETS, FEATURES, PERFORMANCE AND DOWNLOADING. MULTISPECTRAL AND SAR DATA PROCESSING. AUTOMATIC EXTRACTION AND MEASUREMENT OF SURFACES COVERED BY WATER. APPLICATIONS IN THE FIELD OF MANAGEMENT, REQUALIFICATION AND PROTECTION OF AQUATIC ENVIRONMENTS. LESSON 2 PRACTICAL EXERCISE. EACH STUDENT WILL CHOOSE A CASE STUDY, WETLAND, RIVER OR LAKE AND WILL IMPLEMENT ALGORITHMS FOR PRE-PROCESSING AND AUTOMATIC CLASSIFICATION OF WATER SURFACES. UPON THE STUDENT'S REQUEST, IT WILL ALSO BE POSSIBLE TO MAKE OBSERVATIONS OF THE DYNAMICS OF URBANIZATION, VEGETATION AND WILD FIRES. MODULE 3: ASSIMILATION OF UNCONVENTIONAL MONITORING DATA IN GEOTECHNICAL ENGINEERING APPLICATIONS (SUBSIDENCE/LANDSLIDE ANALYSIS, MONITORING AND MODELLING) LESSON 1 BASICS OF DIFFERENTIAL INTERFEROMETRY SYNTHETIC APERTURE RADAR (DINSAR) DATA. DATA AVAILABILITY AND OVERVIEW OF APPLICATIONS. LIMITS/POTENTIAL OF DINSAR DATA USE FOR GEOTECHNICAL STUDIES. PROCEDURES AND CASE STUDIES DEALING WITH THE MAPPING, CONTINUOUS MONITORING AND MODELLING OF SUBSIDENCE-INDUCED SETTLEMENTS AFFECTING URBAN AREAS IN DIFFERENT GEO-ENVIRONMENTAL CONTESTS AND ANALYSIS OF CONSEQUENCES ON BUILDINGS AND INFRASTRUCTURES. MULTI-SCALAR APPROACHES FOR CONVENTIONAL/ UNCONVENTIONAL DATA INTERPRETATION UNDER THE PERSPECTIVE OF SUSTAINABLE SUBSIDENCE RISK MITIGATION WILL BE PRESENTED. LESSON 2 PROCEDURES AND CASE STUDIES DEALING WITH THE CHARACTERIZATION (GEOMETRIC AND KINEMATIC) AND MONITORING OF (ACTIVE/REACTIVATED) SLOW-MOVING LANDSLIDE PHENOMENA AFFECTING BUILT-UP AREAS IN DIFFERENT GEO-ENVIRONMENTAL CONTESTS AND ANALYSIS OF CONSEQUENCES ON BUILDINGS AND INFRASTRUCTURES. MULTI-SCALAR APPROACHES FOR CONVENTIONAL/UNCONVENTIONAL DATA INTERPRETATION AND THEIR CONTRIBUTION TO SUSTAINABLE SLOW-MOVING LANDSLIDE RISK MITIGATION WILL BE PRESENTED. |
| Teaching Methods | |
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| THEORETICAL LESSONS AND APPLIED LABS |
| Verification of learning | |
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| WRITTEN EXAM (WITH OPEN AND MULTIPLE CHOICE QUESTIONS) |
| Texts | |
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| SLIDES OF THE LESSONS AND LECTURE NOTES PROVIDED BY THE TEACHERS |
| More Information | |
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| https://www.diciv.unisa.it/en/teaching |
BETA VERSION Data source ESSE3 [Ultima Sincronizzazione: 2022-05-23]
