Lecture at RS & GIS FoS, AIT

AT76.9004 : Selected Topic: Remote Sensing for Land Surface Monitoring

Rationale:

This course is designed to provide advanced theories and techniques of remote sensing for land surface monitoring based on the fundamental knowledge acquired by "AT76.03 (Remote Sensing)" or "AT76.12 (Fundamental Remote Sensing)". It focuses on theories and techniques to estimate physical parameters on surface, especially reflectance, albedo and temperature, which are deeply related to various terrestrial applications of remote sensing.

Pre-requisite(s):

AT76.03 (Remote Sensing) or AT76.012 (Fundamental Remote Sensing)

Course Outline:

  1. Introduction
  2. Atmospheric Shortwave Radiative Transfer Modeling
    1. Radiative Transfer Equation
    2. Surface Statistical BRDF (Bidirectional Reflectance Distributin Function Modesl)
    3. Atmospheric Optical Properties
    4. Solving Radiative Transfer Equations
  3. Canopy Reflectance Modeling
    1. Canopy Radiative Transfer Formulation
    2. Leaf Optical Models
    3. Solving Radiative Transfer Equations
  4. Satellite Sensor Radiometric Calibration
    1. Postlaunch Calibration Methods
    2. Calibration Coefficients for Landsat TM (Thematic Mapper) and AVHRR (Advanced Very High Resolution Radiometer) Reflective Bands
  5. Atmospheric Correction of Optical Imagery
    1. Methods for Correcting Single-Viewing-Angle Imagery
    2. Methods for Correcting Multiangular Observations
    3. Methods for Estimating Total Column Water Vapor Content
  6. Estimation of Land Surface Biophysical Variables
    1. Statistical Methods
    2. Optimization Inversion Method
    3. Lookup Table Methods
    4. Hybrid Inversion Methods
  7. Estimation of Surface Radiation Budget: I. Broadband Albedo
    1. Boradband Albedo Characteristics
    2. Narrowband-Broadband Conversion
    3. Direct Estimation of Surface Broadband Albedos
  8. Estimation of Surface Radiation Budget: II Longwave
    1. Monochromatic Radiative Transfer Formulation and Solutions
    2. Line-by-Line Methods
    3. Band Models
    4. Atmospheric Correction Methods
    5. Split-Window Algorithm for Estimating LST (Land Surface Temperature)
    6. Multispectral Algorithms for Separating Temperature and Emissivity
  9. Four-Dimensional Data Assimilation
    1. Assimilation Algorithms
    2. Minimization Algorithms
    3. Data Assimilation in Hydrology
    4. Data Assimilation with Crop Growth Models
  10. Validation and Spatial Scaling
    1. Rationale of Validation
    2. Validation Methodology
    3. Spatial Scaling Techniques
  11. Applications
    1. Methodologies for Integrating Remote Sensing with Ecological Process Models
    2. Drought Monitoring
    3. Urban Heat Effects
    4. Forest Fire

Textbook:

Lecture notes provided by the instructor.

References:

Shunlin Liang, Quantitative Remote Sensing of Land Surfaces, Wiley Interscience, 2004

Journals/Magazines/Websites:

Grading System:

The final grade will computed according to the following weight distribution :

Instructor(s):

Dr. Junichi Susaki


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