Professor Ke-Sheng Cheng (Email: rslab@ntu.edu.tw)
RSLAB_BSE_NTU
No. 1, Section 4, Roosevelt Road
Bioenvironmental Syst. Eng., National Taiwan University
TNTmips can be downloaded from http://www.microimages.com/.
Syllabus 2016
(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)
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)
Images for in-class demonstration (Te-chi area)
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
(2) Reflectance
(3) Water quality
(4) Global carbon monitoring (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:
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.
RSLAB - NTU
Prof. Ke-Sheng Cheng
RSLAB_BSE_NTU
No. 1, Section 4, Roosevelt Road
Bioenvironmental Syst. Eng., National Taiwan University