Ruiliang Pu home page

 

ESPM 298

Application of Remote Sensing in Natural Resources

 

Summer course (2nd 6-week, start: 7/7, 2003), Tu/Thu 1-4 PM, 124 Mulford

Instructors: Prof. Peng Gong, Dr. Ruiliang Pu

Office: 130 Mulford, 2-1351, rpu@nature.berkeley.edu

(Credit unit: 2)

 

The goal of this short course is to demonstrate and teach students how to practically extract and employ remote sensing information in natural resources.  Selected case studies will be presented in order to introduce advanced procedures, algorithms and techniques for the goal.  Topics will cover radiometric and geometric corrections of image data, plant spectral feature extraction, spectral mixing modeling, wildland fire mapping, neural network and panelized discriminant analysis algorithms, hyperspectral remote sensing, extraction of biophysical and biochemical parameters. Relevant exercises and laboratories will provide students with a practical opportunity to use GIS, RS, and other statistics software.

 

Prerequisites:  ESPM 271 or ESPM 172 or remote sensing background.

 

Topics:

  1. Plant spectral features and extraction techniques based on lab and in situ spectra
  2. Geometric and terrain correction to both airborne and satellite imageries
  3. Atmospheric correction to both airborne and satellite imageries
  4. Spectral mixing modeling and change detection
  5. Wildfire mapping (I): Hotspot detection
  6. Wildfire mapping (II): Burned scar mapping
  7. Classification with neural network
  8. Classification with panelized discriminant analysis
  9. Extraction of biophysical parameter (species, LAI…)
  10. Extraction of biochemical parameter (chlorophyll content, nutrient concentrations)

 

 

 

 

(Limit: 15 persons)

 

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