| Hafta |
Konu |
| 1 |
Introduction |
| 2 |
Feature Extraction |
| 3 |
Classification Practice |
| 4 |
OUTLINE:
• Classification accuracy
• Error matrix
• Some issues
ALT BAŞLIKLAR
Sources of Error in Remote-Sensing-Derived Information, Why do we need ? What is Accuracy Assessment? Accuracy & Precision, Spatial Accuracy vs. Thematic Accuracy, Steps for performing
Thematic Accuracy Assessment, Sampling scheme, Why we need reference points ? , Systematic Sampling, Commonly Used Methods of Generating Reference Points, Reference data capture, Error matrix, Accuracy Assessment Measures - Kappa coefficient (KHAT), Improving Classification, Numerical examples. |
| 5 |
• Purpose
• Vegetation Indices
• Simple, Intrinsic Indices
• Indices which use a soil line
• Atmospherically corrected indices
• Examples
• Practice
ALT BAŞLIKLAR
Spectral Vegetation Indices (SVI), Physical Basis,
3 groups of Vegetation Indices
i) Simple, Intrinsic Indices (Difference Vegetation Index (DVI), Ratio-based Vegetation Indices (RVI), Normalized Difference Vegetation Index (NDVI));
ii) Indices which use a Soil line (Perpendicular Vegetation Index (PVI), Soil Adjusted Vegetation Index (SAVI), Transformed SAVI (TSAVI), Modified Soil Adjusted Vegetation Index (MSAVI));
iii) Atmospherically corrected indices (Atmospherically Resistant Vegetation Index (ARVI), Global Environmental Monitoring Index (GEMI))
Leaf Area Index (LAI), Global Leaf Area Index, Some Issues |
| 6 |
OUTLINE:
• Principal Component Analysis (PCA)
• Examples
• Some issues
ALT BAŞLIKLAR
Inter-bands Correlation, Principal Component Analysis (PCA), Geometric Interpretation of PCA, Spectral Domain Transformation, eigenvectors/Eigen values, numerical example (one for no correlation, one for showing correlation and application of PCA), examples, What are the assumptions of PCA? (i.e. linear and non linear), advantages, disadvantages, application areas |
| 7 |
OUTLINE:
• Purpose
• Tasseled Cap transformation
• Examples
ALT BAŞLIKLAR
Spectral Domain Transformation, the origin of the method, difference with PCA, relationship with soil line, crop trajectories, each TC parameters and their use, Why do we need Tasseled Cap, Disturbance Index (DI) based on the Tasseled Cap transformation, examples, application areas, advantages, disadvantages |
| 8 |
HAFTA – CHANGE DETECTION
OUTLINE:
• What is change ?
• Change detection
• Change detection methods
• Some issues
ALT BAŞLIKLAR
What is change ? earth is dynamic, goals, Types of change, Why is change important? Changes on the landscape, Applications of change detection techniques, interesting/uninteresting change, basic model, Remote Sensing System Considerations (Temporal Resolution, look angle, Spatial Resolution, Spectral Resolution, radiometric Resolution) & environmental characteristics, Data Pre-processing, The change detection technique categories, Most common change detection technique categories, Change Detection: Visual Analysis, Images Overlay, Image Algebra Change Detection, Multiple Date Composite Image Change Detection, Multitemporal Change Detection, Post-classification Comparison Change Detection, Advantages of Post-Classification Change Detection, change detection matrix, The accuracies of change detection |
| 9 |
OUTLINE:
• Flashback to TIR remote sensing
• Main TIR applications
• Urban Heat Island (UHI)
ALT BAŞLIKLAR
TIR concepts, Physical Basis, Kinetic & Radiant Temperatures, Emissivity, Emissivity versus wavelength, atmospheric windows for TIR, thermal crossover times, diurnal radiant temperatures cycles, Thermal Data Interpretation Elements, Applications of TIR SENSING and application examples, heat island effect, The ALBEDO effect, Rural vs Urban, Wind & Urban Heat Islands, Why the urban heat island effect occurs ? TYPES OF HEAT ISLANDS, Basic Characteristics of Surface and Atmospheric Urban Heat Islands (UHIs), Relation with Surface Air Temperatures, exxamples, Is this Global Warming ? Sensor systems operating in the thermal IR region & comparisons, LAND SURFACE TEMPERATURE (LST) DETERMINATION, UHI mitigation techniques, Combating Urban Heat Islands |
| 10 |
OUTLINE:
? Microwave region
? Types of microwave sensing
? Brief History of RADAR Remote Sensing
? Radar resolution
? RADAR system components
? RADAR surface interactions
? Image examples
ALT BAŞLIKLAR
Microwave RS concepts, Why use microwave remote sensing?, Optical data and radar comparison & complementarity, Advantages compared to optical remote sensing, Passive Microwave Sensing (i.e. brief overview, application areas, advantages/disadvantages), ACTIVE MICROWAVE SENSORS (imaging/non-imaging), Imaging sensors (SLAR, SAR), RADAR System Components, Brief History , RADAR image geometry, SLR, Spatial resolution of SLR (Range resolution & Azimuth resolution), Synthetic Aperture Radar (SAR), Why SAR ? Doppler Effect, Wwavelength and Polarization effect, Radar Image Distortions, RADAR/Surface Interactions, Surface Geometry, Surface Electrical Characteristics, Surface roughness, RADAR/Soil, RADAR/Vegetation, RADAR/Water, Image/application examples |
| 11 |
OUTLINE:
? Microwave region
? Types of microwave sensing
? Brief History of RADAR Remote Sensing
? Radar resolution
? RADAR system components
? RADAR surface interactions
? Image examples
ALT BAŞLIKLAR
Microwave RS concepts, Why use microwave remote sensing?, Optical data and radar comparison & complementarity, Advantages compared to optical remote sensing, Passive Microwave Sensing (i.e. brief overview, application areas, advantages/disadvantages), ACTIVE MICROWAVE SENSORS (imaging/non-imaging), Imaging sensors (SLAR, SAR), RADAR System Components, Brief History , RADAR image geometry, SLR, Spatial resolution of SLR (Range resolution & Azimuth resolution), Synthetic Aperture Radar (SAR), Why SAR ? Doppler Effect, Wwavelength and Polarization effect, Radar Image Distortions, RADAR/Surface Interactions, Surface Geometry, Surface Electrical Characteristics, Surface roughness, RADAR/Soil, RADAR/Vegetation, RADAR/Water, Image/application examples |
| 12 |
11. HAFTA – Hyperspectral Remote Sensing
OUTLINE:
• What is hyperspectral sensing ?
• Spectral libraries
• Pure pixels - Endmember
• Some issues / examples
ALT BAŞLIKLAR
Conventional Remote Sensing, broadly defined spectral regions, How wide are the individual bands?, Spectral Resolution / # Bands, Trade-off between 3 Image Resolutions (spatial/spectral/radiometric resolutions), Why Hyperspectral Remote Sensing ?, Need for continuous spectrum data, Spectroscopy, imaging spectroscopy, Hyperspectral vs. Multispectral RS, HYPERSPECTRAL DATA CUBE, Levels of Spectral Information, Hyperspectral Data Analysis, Spectral Library, ASTER Spectral Library, USGS Spectral Library, The mixed pixel problem, Spectral matching, Endmember spectra, Mixed-pixel decomposition, Data Mixing Models, Spectral mixture analysis, HIS noise, Signal-To-Noise Ratio, HSI denoising techniques, Hyperspectral image processing, Challenges in HS image processing, Applications of Hyperspectral Imaging, Drone-borne/UAV hyperspectral imaging, HS satellites, Image examples |
| 13 |
11. HAFTA – Hyperspectral Remote Sensing
OUTLINE:
• What is hyperspectral sensing ?
• Spectral libraries
• Pure pixels - Endmember
• Some issues / examples
ALT BAŞLIKLAR
Conventional Remote Sensing, broadly defined spectral regions, How wide are the individual bands?, Spectral Resolution / # Bands, Trade-off between 3 Image Resolutions (spatial/spectral/radiometric resolutions), Why Hyperspectral Remote Sensing ?, Need for continuous spectrum data, Spectroscopy, imaging spectroscopy, Hyperspectral vs. Multispectral RS, HYPERSPECTRAL DATA CUBE, Levels of Spectral Information, Hyperspectral Data Analysis, Spectral Library, ASTER Spectral Library, USGS Spectral Library, The mixed pixel problem, Spectral matching, Endmember spectra, Mixed-pixel decomposition, Data Mixing Models, Spectral mixture analysis, HIS noise, Signal-To-Noise Ratio, HSI denoising techniques, Hyperspectral image processing, Challenges in HS image processing, Applications of Hyperspectral Imaging, Drone-borne/UAV hyperspectral imaging, HS satellites, Image examples |