Laboratory for Remote Sensing Hydrology and Spatial Modeling

Remote sensing is the science and technology of deriving information about the target object without making physical contact with the object. It generally involves data acquisition, data analysis, and information extraction and interpretation. This course aims to introduce fundamental theories of remote sensing and techniques for multispectral remote sensing image processing.

The student version of TNTmips, a remote sensing image processing system, will be used in this class to aid students to understand fundamental theories and to become familiar with various remote sensing images processing techniques.

Students may also need to develop their own R codes to conduct certain analyses.

TNTmips can be downloaded from http://www.microimages.com/.

Syllabus 2016

1 - Fundamentals (PPT-I),  

(1) Energy sources

(2) Radiometric principles

(3) Remote sensing in the visible channels and near, middle and thermal infrared spectrum

2 - Fundamentals (PPT-IIa), (PPT-IIb)  

(1) Energy interactions with the atmosphere

scattering and absorption

(2) Energy interactions with surface features

types of reflectance

spectral reflectance curves

Sample images: Images_RS_Class.zip (click to download)

DN histograms  

3 - Characteristics of remote sensing systems and images (PPT-III) 

(1) Remote sensing scanning systems

(2) Resolutions - spatial resolution, radiometric resolution, spectral resolution, and temporal resolution

(3) Digital numbers and grey-level histogram

(4) Earth observation satellites

(5) Weather satellites

4 - Image pre-processing (PPT-IV)

(I): radiometric correction

(1) radiometric correction for detector errors

(2) radiometric correction for atmospheric effects

(3) radiometric correction for topographic effects

A path radiance estimation algorithm using reflectance measurements in radiometric control areas (International Journal of Remote Sensing, 2011. PPT)

(II): geometric correction (HW-1, GCP.pdf , Georeferencing_Demo)

(1) Definitions for geometric correction

(2) Mathematical models for geometric distortion

orbit model

platform attitude model

scanner model

earth model

(3) Coordinate transformation

(4) Resampling

 Images for in-class demonstration (Taoyuan area)

• Zipped Original SPOT images (2003 and 2004) [SPOT2003&2004.zip]
• SPOT2003.rvc, SPOT2004.rvc, SPOT2003_Resampled.rvc, SPOT2004_Extractedfrom2003.rvc 
• Descriptive text of georeferencing and resampling [click to download].

 Images for in-class demonstration (Te-chi area)

• Zipped original SPOT images (2004 and 2005)  [Tachi.zip]
• SPOT5_2004.rvc,  SPOT5_2005.rvc  

5 - Digital Image Processing  (PPT-V) 

(1) Contrast enhancement

(2) Spatial filtering

(3) Spatial statistics and spectral transformations

angular second moment, contrast, entropy, vegetation indices, semivariogram, principal components

6 - Thematic Classification (I)  (PPT-VI)    

(1) Overview

(2) Class separability indices

(3) Unsupervised classification -- K-means method

Stochastic image simulation using K-means and random field simulation (PPT)   

7 - Thematic Classification (II)

(1) Nonparametric supervised classification methods (Indicator kriging in feature space, PPT)

(2) Parametric supervised classification methods

nearest-mean classifier, maximum-likelihood classifier, Bayes classifier

(3) Assessing the classification accuracies

   HW-2 (Maximum likelihood classification - Uncertainty Assessment, R code for equiprob ellipse)

  HW-3 (Maximum likelihood classification - Uncertainty Assessment, Reference-data-based confusion matrix)

Assessing Uncertainty in LULC Classification Accuracy Using Bootstrap Resampling (Remote Sensing, 2016, 8, 705; doi:10.3390/rs8090705.

8 - Retrieval of land surface parameters

(1) Landscape pattern and land surface temperature

• Comparison of landcover patterns in Taipei, Kyoto, and Tokyo (PPT)   [Article in Landscape and Urban Planning]
  
• Effect of paddy field on ambient air temperature
  
• Effect of urbanization on diurnal land surface temperature variation

(2) Reflectance

(3) Water quality

(4) Global carbon monitoring  (PPT)    

9 - Change detection  (PPT)  

(1) Overview

(2) Difference image thresholding

(3) Hypothesis-test-based approach

(4) MAD transformation approach

Reference books:

Remote Sensing-Models and Methods for Image Processing (Schowengerdt, R.A., Academic Press)

Remote Sensing Digital Image Analysis (Richards, J.A., Springer-Verlag)

Remote Sensing - the image chain approach (Schoot, J.R., Oxford University Press)

Journals:

1. Remote Sensing of Environment
2. IEEE Transaction on Geoscience and Remote Sensing
3. Photogrammetric Engineering and Remote Sensing (PE&RS)
4. International Journal of Remote Sensing
5. Remote Sensing (MDPI)

Does urbanization increase diurnal land surface temperature variation? Evidence and implications (Landscape and Urban Planning 157 (2017), 247–258)



A Feature-Space Indicator Kriging Approach for Remote Sensing Image Classification (IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 52, NO. 7, JULY 2014)

Assessing Uncertainty in LULC Classification Accuracy Using Bootstrap Resampling (Remote Sensing, 2016, 8, 705; doi:10.3390/rs8090705. Click to download.)

Unclassified pixels in feature space identified by the chi-squared threshold technique and the equal likelihood technique.