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Remote Sensing
&
GIS Applications
Lokhaze Ali
PhD Student Environmental Engineering (NUST)
RemoteSensing&GISApplications
2
RemoteSensing&GISApplications
3
Multispectral vs Hyperspectral Bands
• Multispectral imagery generally refers to 3
to 10 bands that are represented in pixels
• Hyperspectral imagery consists of much
narrower bands (10-20 nm)
• Hyperspectral image could have hundreds
of thousands of bands
• This uses an imaging spectrometer
• The main difference between multispectral
and hyperspectral is the number of
bands and how narrow the bands are
RemoteSensing&GISApplications
4
Multispectral Bands in Landsat 8
Band 1: Coastal aerosol (0.43-0.45 um)
Band 2: Blue (0.45-0.51 um)
Band 3: Green (0.53-0.59 um)
Band 4: Red (0.64-0.67 um)
Band 5: Near infrared NIR (0.85-0.88 um)
Band 6: Short-wave Infrared SWIR 1 (1.57-1.65 um)
Band 7: Short-wave Infrared SWIR 2 (2.11-2.29 um)
Band 8: Panchromatic (0.50-0.68 um)
Band 9: Cirrus (1.36-1.38 um)
Band 10: Thermal Infrared TIRS 1 (10.60-11.19 um)
Band 11: Thermal Infrared TIRS 2 (11.50-12.51 um)
RemoteSensing&GISApplications
5
3D Cube of Farmland
• 320 X 320 Pixels Farmland Area
• 193 Spectral Bands
RemoteSensing&GISApplications
6
Levels of Data
Level 1B Level 2 Level 3
Calibration to Radiance Aerosol Retrieval
Algorithm
Spatial & Temporal
Averaging
Ref: Dr. Pawan Gupta (NASA), 2015
RemoteSensing&GISApplications
7
Cyclone Chapala
3rd November 2015
RemoteSensing&GISApplications
8
Cyclone Megh
9th November 2015
RemoteSensing&GISApplications
9
Forecasting Models
RemoteSensing&GISApplications
10
MODIS Real Time Image
RemoteSensing&GISApplications
11
Remote Sensing
Resolution
• Low spatial resolution (>30 meters)
• Medium resolution (5-30 meters)
• High resolution (1-5 meters)
• Very high resolution (< 1 meter)
RemoteSensing&GISApplications
12
Very High Resolution
RemoteSensing&GISApplications
13
Comparison of Top of Atmosphere and
Surface Reflectance
RemoteSensing&GISApplications
14
Aerosol Optical Depth (AOD)
Aerosol optical depth is
quantitative measure of
the extinction of the
solar radiation by
aerosol scattering
between the point of
observation and the top
of the atmosphere
15
#Aerosols
MODIS Monthly AOD Results 2015 over Pakistan
RemoteSensing&GISApplications
16
MODIS Monthly AOD Results 2014 over Pakistan
RemoteSensing&GISApplications
17
MODIS Monthly AOD Results 2013 over Pakistan
RemoteSensing&GISApplications
18
Important Links
• EOSDIS Worldview
https://earthdata.nasa.gov/labs/worldview/
• Pakistan Meteorological Department Precipitation Model
http://www.pmd.gov.pk/loop.htm
• Landsat Gallery
http://landsat.usgs.gov/gallery.php
• Digital Globe
http://global.digitalglobe.com/sites/default/files/DG-RemoteSensing-WP.pdf
• Cyclone Chapala
http://earthobservatory.nasa.gov/IOTD/view.php?id=86951&src=fb
RemoteSensing&GISApplications
19

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Remote Sensing and GIS Applications

  • 1. Remote Sensing & GIS Applications Lokhaze Ali PhD Student Environmental Engineering (NUST)
  • 4. Multispectral vs Hyperspectral Bands • Multispectral imagery generally refers to 3 to 10 bands that are represented in pixels • Hyperspectral imagery consists of much narrower bands (10-20 nm) • Hyperspectral image could have hundreds of thousands of bands • This uses an imaging spectrometer • The main difference between multispectral and hyperspectral is the number of bands and how narrow the bands are RemoteSensing&GISApplications 4
  • 5. Multispectral Bands in Landsat 8 Band 1: Coastal aerosol (0.43-0.45 um) Band 2: Blue (0.45-0.51 um) Band 3: Green (0.53-0.59 um) Band 4: Red (0.64-0.67 um) Band 5: Near infrared NIR (0.85-0.88 um) Band 6: Short-wave Infrared SWIR 1 (1.57-1.65 um) Band 7: Short-wave Infrared SWIR 2 (2.11-2.29 um) Band 8: Panchromatic (0.50-0.68 um) Band 9: Cirrus (1.36-1.38 um) Band 10: Thermal Infrared TIRS 1 (10.60-11.19 um) Band 11: Thermal Infrared TIRS 2 (11.50-12.51 um) RemoteSensing&GISApplications 5
  • 6. 3D Cube of Farmland • 320 X 320 Pixels Farmland Area • 193 Spectral Bands RemoteSensing&GISApplications 6
  • 7. Levels of Data Level 1B Level 2 Level 3 Calibration to Radiance Aerosol Retrieval Algorithm Spatial & Temporal Averaging Ref: Dr. Pawan Gupta (NASA), 2015 RemoteSensing&GISApplications 7
  • 8. Cyclone Chapala 3rd November 2015 RemoteSensing&GISApplications 8
  • 9. Cyclone Megh 9th November 2015 RemoteSensing&GISApplications 9
  • 11. MODIS Real Time Image RemoteSensing&GISApplications 11
  • 12. Remote Sensing Resolution • Low spatial resolution (>30 meters) • Medium resolution (5-30 meters) • High resolution (1-5 meters) • Very high resolution (< 1 meter) RemoteSensing&GISApplications 12
  • 14. Comparison of Top of Atmosphere and Surface Reflectance RemoteSensing&GISApplications 14
  • 15. Aerosol Optical Depth (AOD) Aerosol optical depth is quantitative measure of the extinction of the solar radiation by aerosol scattering between the point of observation and the top of the atmosphere 15 #Aerosols
  • 16. MODIS Monthly AOD Results 2015 over Pakistan RemoteSensing&GISApplications 16
  • 17. MODIS Monthly AOD Results 2014 over Pakistan RemoteSensing&GISApplications 17
  • 18. MODIS Monthly AOD Results 2013 over Pakistan RemoteSensing&GISApplications 18
  • 19. Important Links • EOSDIS Worldview https://earthdata.nasa.gov/labs/worldview/ • Pakistan Meteorological Department Precipitation Model http://www.pmd.gov.pk/loop.htm • Landsat Gallery http://landsat.usgs.gov/gallery.php • Digital Globe http://global.digitalglobe.com/sites/default/files/DG-RemoteSensing-WP.pdf • Cyclone Chapala http://earthobservatory.nasa.gov/IOTD/view.php?id=86951&src=fb RemoteSensing&GISApplications 19