ECTS - University of Pisa
By the end of the course, students will have acquired knowledge about the main mechanisms behind remote sensing systems for earth observation, with both optical and radar sensing technologies.
Ongoing assessments to monitor academic progress will be carried out in the form of joint practical activities or meetings between the lecturer and groups of students developing a specific project.
By the end of the course, students will be able to:
- identify and understand the peculiarities of a remote sensing system for earth observation (EO)
- select, obtain and use EO data products
- make basic usage of a data processing software environment for EO datasets (ESA SNAP)
- develop proficiency about using MATLAB for data handling, display, feature extraction and representation (e.g., surface temperature features or land cover classes by thematic mapping)
- get acquainted with atmospheric radiative transfer models by using the MODTRAN software
- understand the operative principle of a radar system
- know the main elements of a radar transmitter-to-receiver chain
- provide a rough design of a SAR sensor for Earth Observation
- interpret and analyze the statistical properties of a SAR image
The method described for the assessment criteria of knowledge applies also to the assessment criteria of skills.
Develop an awareness of the multidisciplinary aspects in designing a remote sensing service based on spacecraft missions. This approach is useful both for participating in the multidisciplinary design of new missions and for developing services based on existing missions.
The assessment is performed by systematic interaction with students during group work and practical sessions.
Basic usage of MATLAB is required. In particular, prior knowledge about handling multidimensional datasets and indexing techniques in MATLAB is strongly advised.
Elements of Probability Theory and Statistics
Even though not strictly required, basic knowledge of Communication Theory is strongly advised
"Optical" module:
- Main aspects of radiometry and radiative transfer in the optical domain. Concepts of spatial, spectral and radiometric resolution.
- First concepts of mapping and classification techniquesbased on radiometric images in the optical domain. Basic hints to radar altimetry concepts.
- Principles of radiometry. Fundamental radiometricquantities. Radiative transfer at the interface between two media. Calculation of the sun irradiance atTOA. Water mapping features in the NIR/SWIR. Introduction to temperature estimations in the TIR.
- Basics of atmospheric radiative transfer. Main mechanisms in the VIS/NIR/SWIR bands. Main mechianisms in the TIR band. Concept of surface BRDF. Introduction to aerosol (Mie) and molucules (Rayleigh) scattering. Phase functions. Lambert-Beer law. Optical thickness. Simplified two-layers flat atmospheric model.
- Introduction to multi/hyperspectral acquisition concepts. Survey of the main missions for Earth Observation based on multi/hyperspectral optical payloads.
- Concepts of IFOV, swath and revisit. Concept of processing level. Examples inSentinel and Landsats missions. Basic concept of radiometric calibration.
- Processing chain of electro-optical systems: spatial sampling and sensor response; spectral response of the sensor; data quantisation and calibration. Concepts of feature space, feature selection, clustering and class dicriminability for multi/hyperspectraldata.
- Supervised vs unsupervised classification strategies. The concept of bi-dimensional histogram. Introduction to the "k-means" clustering algorithm. Main data formats and extraction of subsets (spatial / spectral).
- Basic concepts of multivariate data analysis applied to multi/hyperspectral data. Production and analysis of 2D density plots. Class segmentation in the feature space and production of thematic maps.
- The radiative transfer model MODTRAN. Main input and output atmospheric optical parameters and definition of the model geometry. Model calculation of spectral transmittance, solar irradiance and diffused skylight.
- Model simulation of total radiance at-sensor in the VIS/NIR/SWIR domain. Simulations with spectral Lambertian surfaces at the lower bound of the atmosphere. Evaluation of Rayleigh scattering effects by analysing multiple geometries. Calculation of spectral transmittance and at-sensor radiance in the TIR domain. Discussion of model-based atmospheric correction strategies for multispectral data.
"Radar/SAR module":
The Radar/SAR module of the course is organized in two parts.
The former (~10h theory + ~5h practice) introduces fundamental concepts about radar systems:
The latter part (~10h theory + ~5h practice) focuses on Synthetic Aperture Radar systems:
Reference books for this course are:
- Schowengerdt, Robert A. Remote sensing: models and methods for image processing. Elsevier, 2006.
- Richards, John A. Remote sensing digital image analysis. Berlin: Springer, 1999.
- Driggers, R. G., Cox, P., & Edwards, T. (1999). Introduction to Infrared and Electro-Optical Systems. Artech House. Inc., Norwood, MA(USA).
- G. Picardi, Elaborazione del segnale radar, Franco Angeli, 1991. (in Italian)
- Merrill Skolnik, Introduction to radar systems, McGraw-Hill, 1984
- C. Oliver, S. Quegan Understanding Synthetic Aperture Radar Images, Artech House, 1998.
The exam consists in a practical test making use of the learned portals, software and working environments, followed by discussion of theoretical aspects.
For those who followed the course and participated actively to the in itinere activities, the exam consists in discussion of such activities and explanation of their theoretical background.
