School of Engineering and Technology, (SET)  
 
Semester Offering: January
 
AT76.10 : Advanced Remote Sensing  3(2-3) [Elective course]
Course objectives:

This course aims at providing students with advanced Remote Sensing analytical techniques required in various applications; how to extract high-level information from RS data. The techniques taught covers coupling of model parameters and remote sensing data for several applications including the most recent data assimilation techniques, atmospheric correction, Multi-temporal/Multi-Resolution data analysis, OGC Web Services such as Web Map Service, Web Feature Service, and Field Sensor Network. This lecture covers Synthetic Aperture Radar technique as well.

 
Learning Outcomes:

Atmospheric Correction, Moderate to Low Resolution RS, Vegetation Change and Crop Modeling, Sediment and Water Discharge Analysis, Field Sensor Network, Multi-Temporal – Multi-Resolution data Analysis, Synthetic Aperture Radar System, OGC Web Services.

 
Pre-requisite(s):

AT76.03 (Remote Sensing)

 
Course Outline:

I.                Introduction

II.             Atmospheric Correction
1.        Second Simulation of the Satellite Signal in the Solar Spectrum (6S) System
2.        Absorbing effects & Scattering effects
3.        Atmospheric correction and its application

III.           Moderate to Low Resolution RS
1.        MODIS and NOAA satellite system
2.        Geometric and Radiometric correction
3.        Cloud Free Composite

IV.          Vegetation Change and Crop Modeling
1.        Vegetation restoration modeling
2.        Data Assimilation Technique using GA
3.        Soil-Water-Atmosphere-Plant Crop Model (SWAP)
4.        SWAP model parameter estimation using GA

V.            Sediment and Water Discharge Analysis
1.        Sediment and Water discharge model
2.        Model parameter estimation
3.        Validation

VI.          Field Sensor Network
1.        Field Sensor Network for Monitoring and Modeling
2.        OGC Sensor Web Enablement (SWE)
3.        OGC Sensor Observation Service (SOS)
4.        Sensor Service GRID(SSG)

VII.        Multi-Temporal / Multi-Resolution data Analysis
1.        Agriculture activity monitoring
2.        Evapotranspiration monitoring

VIII.     OGC Web Services
1.        Web Map Service
2.        Web Feature Service
3.        Web Coverage Service
4.        System design, implementation and configuration

IX.          Synthetic Aperture Radar System
1.        Radar System and Microwave
2.        SAR system geometry
3.        Interaction between microwave and targets
4.        SAR data processing
5.        Multi-polarization SAR
6.        SAR Interferometry
7.        Applications

 
Laboratory Sessions:

Students will be requested to analyze remote sensing images based on methodology taught in the lecture session. ENVI, ER-Mapper, 6S atmospheric correction software, 3D computer graphics software, open source Web-GIS software will be used in the session.

 
Learning Resources:

Textbook:

Lecture notes

 
Reference Books:
John A. Richards:
Remote Sensing Digital Image Analysis, Springer-Verlag, 1993

R.C. Gonzales, R. E. Woods:
Digital Image Processing, Addison Wesley, 1993

R. A. Schowengerdt:
Techniques for Image Processing and Classification in Remote Sensing, Academic Press, 1983

 
Journals and Magazines:

International Journal of Photogrammetry and Remote Sensing; (ISPRS)
Photogrammetric Engineering and Remote Sensing
Asian Journal of Geoinformatics
Sensors

 
Teaching and Learning Methods:

N/A

 
Evaluation Scheme:

Final grades will be computed according to the following percentage distribution:

Mid-semester Examination     30%
Final Examination    40%,
Assignments/Lab Assignments/Mini Project   30%.

Examination will be closed book.