REMOTE SENSING

Paolo ADDESSO REMOTE SENSING

0622700076
DIPARTIMENTO DI INGEGNERIA DELL'INFORMAZIONE ED ELETTRICA E MATEMATICA APPLICATA
EQF7
COMPUTER ENGINEERING
2020/2021



YEAR OF COURSE 2
YEAR OF DIDACTIC SYSTEM 2017
SECONDO SEMESTRE
CFUHOURSACTIVITY
324LESSONS
324EXERCISES
Objectives
THE COURSE AIMS TO PROVIDE THE ELEMENTS TO COMPREHEND AND UTILIZE THE METHODS EXPLOITED IN REMOTE SENSING AND TO OUTLINE ITS MAIN APPLICATIONS
KNOWLEDGE AND UNDERSTANDING: REMOTE SENSING SYSTEMS; CLASSIFICATION METHODS; IMAGE PROCESSING
APPLIED KNOWLEDGE AND UNDERSTANDING: ANALYSIS OF RADAR SYSTEMS AND SATELLITE SYSSTEMS; FEATURE EXTRACTION; APPLICATIONS TO ENVIRONMENTAL CONTROL
MAKING JUDGEMENT: TO SELECT METHODS FOR IMAGE PROCESSING AND SCENE CLASSIFICATION: TO ASSESS COMPARATIVELY THE PERFORMANCE OF REMOTE SENSING SYSTEMS
COMMUNICATION SKILLS: TO WORK IN TEAMS; TO DISCUSS ABOUT TECHNICAL AND THEORETICAL QUESTIONS; TO REPORT CORRECTLY THE SOLUTION:OF A DECISION AND/OR CLASSIFICATION PROBLEM
LEARNING SKILLS: TO BE ABLE TO APPLY THE ACQUIRED METHODS TO DIFFERENT CONTEXTS.
Prerequisites
FOR THE SUCCESSFUL ACHIEVEMENT OF THE OJECTIVES BASIC METHODOLOGICAL TOOLS IN MATHEMATICS AND STATISTICS ARE REQUIRED, AS WELL AS THE FUNDAMENTALS OF DIGITAL SIGNAL PROCESSING.
Contents
INTRODUCTION TO REMOTE SENSING
ELECTROMAGNETIC SPECTRUM; ACTIVE VS PASSIVE REMOTE SENSING; SENSORS: GROUND BASED, AIRBORNE, SPACEBORNE; SATELLITE CHARACTERISTICS (ORBITS); SATELLITES FOR EARTH OBSERVATION; LABORATORY IN A GROUND STATION, HARDWARE AND MAIN OPERATIONS (5 HOURS OF LESSON AND 3 HOURS OF LABORATORY)

PASSIVE REMOTE SENSING
RESOLUTIONS: SPATIAL (PIXEL AND SCALE), SPECTRAL, RADIOMETRIC AND TEMPORAL; CAMERAS AND AREIAL PHOTOGRAPHS; MULTISPETRAL SCAN; INTERACTION WITH TARGET AND ATMOSPHERE; SENSOR MODEL; GEOMETRIC DISTORSIONS. (10 HOURS OF LESSON AND 3 HOURS OF EXERCISE)

ACTIVE REMOTE SENSING
MICROWAVE REMOTE SENSING: RADAR FUNDAMENTALS; GEOMETRY VS SPATIAL RESOLUTION; IMAGE DISTORSION; INTERACTION WITH TARGET; SPECKLE; SAR: FUNDAMENTALS, GEOMETRY, PROCESSING, EXAMPLES OF AIRBORNE AND SPACEBORNE SAR, MODES (STRIPMAP, SPOTLIGHT, SCANSAR); SAR INTERFEROMETRY. (5 HOURS OF LESSON)

PROCESSING FOR REMOTELY SENSED IMAGES
NOISE REDUCTION, CONTRAST ENHANCEMENT, SPATIAL FILTERING, SPATIAL FOURIER TRANSFORM; MULTI-IMAGE PROCESSING: SPECTRAL RATIOING, PRINCIPAL COMPONENTS, IHS TRANSFORM; MULTI-TEMPORAL ANALYSIS: CHANGE DETECTION; MULTI-SENSOR DATA FUSION; SUPERVISED AND UNSUPERVISED CLASSIFICATION; INTRODUCTION TO IDL AND ENVI FOR PROCESSING REMOTELY SENSED IMAGES (12 HOURS OF LESSON AND 10 HOURS OF EXERCISE)
Teaching Methods
THE COURSE INCLUDES THORETICAL LECTURES AND CLASSROOM EXERCISES. SOME COMPUTER ASSISTED EXERCISES ARE DEVOTED TO LANGUAGES FOR IMAGE PROCESSING (IDL, ENVI). LABORATORY PRACTICES ARE DEVELOPED IN A GROUND STATION (RESLEHM CENTER)
Verification of learning
THE GOAL OF THE FINAL EXAM IS, FIRST , THE EVALUATION OF THE KNOWLEDGE AND UNDERSTANDING OF THE CONCEPTS PRESENTED IN THE COURSE AND, SECOND, THE PERSONAL JUDGEMENT, THE COMMUNICATION SKILLS AND THE LEARNING ABILITIES.
THE FINAL EXAM CONSISTS OF A DISCUSSION ON A PROJECT WORK (MAY BE A GROUP WORK) AND AN ORAL INTERVIEW:

THEDISCUSSSION ABOUT THE PROJECT WORK IS AIMED TO ASCERTAIN THE CAPACITY TO APPLY THE SIGNAL AND IMAGE PROCESSING METHODS PRESENTED IN THE COURSE TO SOME TYPICAL REMOTE SENSING PROBLEM.

THE ORAL INTERVIEW AIMS TO ASSESS THE ACQUIRED KNOWLEDGE ALSO ON THE TOPICS NOT COVERED BY THE PROJECT. THE ORAL EXPOSITION AND THE MATHEMATICAL ARGUMENTS ARE CREDITED WITH HIGHER SCORES.

CONCERNING THE FINAL SCORE, EXPRESSED OUT OF THIRTY, THE PROJECT CONTRIBUTES FOR 50% WHILE THE ORAL INTERVIEW FOR 50%. FULL MARKS WITH DISTINCTION MAY BE GIVEN TO STUDENTS WHO DEMONSTRATE THAT THEY CAN APPLY THE ACQUIRED KNOWLEDGE WITH CONSIDERABLE AUTONOMY TO EXERCISES AND THEORETICAL ISSUES. IN CASE OF NO PASS, THE PROJECT WORK CAN BE SAVED TOWARD THE REPETITION OF THE EXAM.

Texts
LK: T.M: LILLESAND, R.W.KIEFER: REMOTE SENSING AND IMAGE INTERPRETATION, J. WILEY, 1994

CCRS: FUNDAMENTALS OF REMOTE SENSING WEB TUTORIAL

J: A.K. JAIN: FUNDAMENTALS OF DIGITAL SIGNAL PROCESSING, PRENTICE HALL, 1989

OQ: C. OLIVER- S- QUEGAN: UNDERSTANDING SYNTHETIC APERTURE RADAR IMAGES, ARTECH HOUSE, 1998

SCHOWENGERDT, ROBERT A. REMOTE SENSING: MODELS AND METHODS FOR IMAGE PROCESSING. ELSEVIER, 2006
More Information
THE LECTURES ARE OFFERED IN ENGLISH. TEXBOOKS AND REFERENCE MATERIAL ARE IN ENGLISH.
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