2010 CuttingEdge Workshop Detecting submarine springs in Florida's coastal zone using thermal remote sensing data Teaching GIS and Remote Sensing in the 21 st Centry Abuduwasiti Wulamu, PhD Department of Earth & Atmospheric Sciences, Saint Louis University

Mapping submarine springs in Florida 2 Aug 8 – 12, 2010 © Abduwasit Ghulam Overview  Lab Description  Objective  Data  Retrieval of Surface temperature  Signatures of submarine springs from thermal anomaly  Conclusion  Acknowledgements

Mapping submarine springs in Florida 3 Aug 8 – 12, 2010 © Abduwasit Ghulam Course Settings  College Level 4XX  Geospatial Methods  Remote Sensing  Lab  Middle or end of semester  A class project or lab assignment

Mapping submarine springs in Florida 4 Aug 8 – 12, 2010 © Abduwasit Ghulam Lab Description  Objective  Familiarize students with thermal remote sensing with a practical example  Stimulate creative thinking skills  Data  Landsat ETM+  Census dataset  Field collections

Tallahassee, Florida Study area

Geovis.USGS.GOV How to get the data

Mapping submarine springs in Florida 7 Aug 8 – 12, 2010 © Abduwasit Ghulam How to get the data

Mapping submarine springs in Florida 8 Aug 8 – 12, 2010 © Abduwasit Ghulam How to get the data

Mapping submarine springs in Florida 9 Aug 8 – 12, 2010 © Abduwasit Ghulam How to get the data

Mapping submarine springs in Florida 10 Aug 8 – 12, 2010 © Abduwasit Ghulam How to get the data Unzip the downloaded data

??? Why there are two thermal bands with Landsat ETM+?

Theoretical background Retrieval of surface temperature

Mapping submarine springs in Florida 13 Aug 8 – 12, 2010 © Abduwasit Ghulam Thermal radiation

Mapping submarine springs in Florida 14 Aug 8 – 12, 2010 © Abduwasit Ghulam Workflow DN DN – to Radiance BT Radiance to at sensor temperature LST At sensor brightness temperature to surface temperature

Mapping submarine springs in Florida 15 Aug 8 – 12, 2010 © Abduwasit Ghulam Radiometric Calibration DN  Radiance  DN  Radiance where the LMIN and LMAX are the spectral radiances for each band at digital numbers 1 and 255. DN is the pixel DN value, λ is the wavelength. One gets LMIN and LMAX values from the header file. dbook_htmls/chapter11/chapter11.html

Mapping submarine springs in Florida 16 Aug 8 – 12, 2010 © Abduwasit Ghulam Radiometric Calibration Radiance  Brightness temperature  Planck’s function Where, C 1 = × W m 2 ; C 2 = ×10 -2 m K

Mapping submarine springs in Florida 17 Aug 8 – 12, 2010 © Abduwasit Ghulam Radiometric Calibration Radiance  Brightness temperature Let K 1 = C 1 / λ 5, and K 2 = C 2 / λ, and satellite measured radiant intensity B λ (T) = L λ Description K 1 (W m -2 sr -1 µm -1 )K 2 (Kelvin) Landsat 7 – ETM Landsat 5 – TM

Mapping submarine springs in Florida 18 Aug 8 – 12, 2010 © Abduwasit Ghulam Land Surface Temperature BT  LST  λ is the wavelength of emitted radiance. λ = 11.5 μ m (Markham and Barker, 1986) and ρ = h × c/ σ = m K. Here, σ is Boltzmann constant (1.38 * 10 − 23 J/K), h is Planck’s constant (6.26 * 10 − 34 Js) and c is velocity of light (2.998 * 10 8 m/s).Markham and Barker, 1986 Artis and Carnahan, 1982Artis and Carnahan, Survey of emissivity variability in thermography of urban areas, Rem. Sens. Environ. 12 (1982), pp. 313–329.

Mapping submarine springs in Florida 19 Aug 8 – 12, 2010 © Abduwasit Ghulam Land surface temperature  BT  LST  Radiative Transfer – MODTRAN  Quasi-physical models JIMÉNEZ-MUÑOZ, J.C., SOBRINO, J.A A generalized single- channel method for retrieving land surface temperature from remote sensing data. Journal of Geophysical Research, 108, doi: /2003JD QIN, Z., KARNIELI, A., BERLINER, P A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. International Journal of Remote Sensing, 22, pp Srivastava, Majumdar and Bhattacharya. (2009). Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data. Advances in Space Research, 431(10):

Implementing using ENVI Retrieval of surface temperature

Basic Tools  Band Math DN  Radiance (( )/( ))*(B6- 1.0) Radiance  Brightness Temperature D/(alog(666.09D/B6+1D)) Implementing using ENVI

Mapping submarine springs in Florida 22 Aug 8 – 12, 2010 © Abduwasit Ghulam Implementing using ENVI File  Open Image file 

Mapping submarine springs in Florida 23 Aug 8 – 12, 2010 © Abduwasit Ghulam Implementing using ENVI Color compositing

Mapping submarine springs in Florida 24 Aug 8 – 12, 2010 © Abduwasit Ghulam Radiometric calibration DN  at sensor temperature Basic Tools  Preprocessing  Calibration Utilities  Landsat Calibration

Mapping submarine springs in Florida 25 Aug 8 – 12, 2010 © Abduwasit Ghulam ENVI Color Mapping Display Window Tools  Color Mapping  Envi Color Tables Select RainBow

ArcGIS classification ENVI Color Mapping GIS Visualization

Save File As Save Image As Export to ArcMap Export to ArcGIS

Mapping submarine springs in Florida 28 Aug 8 – 12, 2010 © Abduwasit Ghulam Export Image to ArcMap Save Image asSave File As

Mapping submarine springs in Florida 29 Aug 8 – 12, 2010 © Abduwasit Ghulam Save Image As Display Window Tools  Color Mapping  Envi Color Tables Select RainBow

Mapping submarine springs in Florida 30 Aug 8 – 12, 2010 © Abduwasit Ghulam Export Image to ArcMap

Mapping submarine springs in Florida 31 Aug 8 – 12, 2010 © Abduwasit Ghulam Visualization

Mapping submarine springs in Florida 32 Aug 8 – 12, 2010 © Abduwasit Ghulam Visualization

Mapping submarine springs in Florida 33 Aug 8 – 12, 2010 © Abduwasit Ghulam Visualization

Mapping submarine springs in Florida 34 Aug 8 – 12, 2010 © Abduwasit Ghulam Visualization Classification in ArcMap

Mapping submarine springs in Florida 35 Aug 8 – 12, 2010 © Abduwasit Ghulam Visualization From ENVI Color Mapping

Mapping submarine springs in Florida 36 Aug 8 – 12, 2010 © Abduwasit Ghulam Validation

Mapping submarine springs in Florida 37 Aug 8 – 12, 2010 © Abduwasit Ghulam Conclusion  Extensive field work, validation needed  Geologic controls, e.g., fractures, aquifers that channels groundwater to the oceans need to be indentified  Radar and Optical data fusion is helpful  As stated earlier, the objective of this lab is to teach students how to use thermal remote sensing, rather than presenting a “solid” scientific research

Mapping submarine springs in Florida 38 Aug 8 – 12, 2010 © Abduwasit Ghulam Acknowledgements & References  Locational information for the spring vents that were verified on the Taylor County coast provided by Tom Greenhalgh from Florida Geological Survey  Artis and Carnahan, Survey of emissivity variability in thermography of urban areas, Rem. Sens. Environ. 12 (1982), pp. 313–329. Artis and Carnahan, 1982  JIMÉNEZ-MUÑOZ, J.C., SOBRINO, J.A A generalized single-channel method for retrieving land surface temperature from remote sensing data. Journal of Geophysical Research, 108, doi: /2003JD  QIN, Z., KARNIELI, A., BERLINER, P A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. International Journal of Remote Sensing, 22, pp  Srivastava, Majumdar and Bhattacharya. (2009). Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data. Advances in Space Research, 431(10):  pt pt  

Mapping submarine springs in Florida 39 Aug 8 – 12, 2010 © Abduwasit Ghulam Questions and Discussion