1. Retrieval of Land Surface Temperature from Remote Sensing Thermal Images
Dr. Khalil Valizadeh Kamran
University of Tabriz, Iran

2. Contents  Introduction  Objectives  Four Thermal Sensors
 LST Retrieved from TABI
 LST Retrieved from ASTER
 LST Retrieved from AVHRR
 LST Retrieved from TM(ETM+)
 Concluded Notes

3. Introduction Mono-window algorithm (MWA) Split-window algorithm (SWA)
 Importance of LST retrieved from remote sensing thermal images for studies of physical, chemical and biological processes of the Earth
 Two categories of LST retrieval methods
Mono-window algorithm (MWA)
Split-window algorithm (SWA)
After reading the report, briefly talk about the importance and methodologies of LST retrieval.

4. Objectives
 Test and develop both mono-window algorithms and split-window algorithms for retrieving LST from thermal remote sensing images
 Develop softwares for calculating LST from 4 thermal sensors’ data: TABI-320, ASTER Ch13 & 14, AVHRR Ch4 & 5, and TM6 or ETM+6

5. Four Thermal sensors  TABI-320  ASTER
Thermal Airborne Broadband Imager, manufactured by ITRES
Covering thermal range: 8-12 mm, 320 pixels per line, brightness temperature data provided in Deg C X 100
Altitude up to 3048 m
 ASTER
Terra/ASTER Ch13( mm), Ch14( mm)
Spatial resolution 90 m
Be provided with scaled thermal radiance at sensor

6. Four Thermal sensors  AVHRR  TM(ETM+)
NOAA11,14/AVHRR Ch4( mm),Ch5( mm)
Scaled thermal radiance at sensor
Nominal spatial resolution 1.1 km at nadir
 TM(ETM+)
All Landsat 5 TM6 and Landsat 7 ETM+6 after July, 2001
Scaled thermal radiance (DN) with a wavelength range: mm
Spatial resolution 120 m for TM6 and 60 m for ETM+6

7. LST retrieved from TABI
 Flowchart for LST retrieval
 Mono-window algorithm (MWA)
 Application cases
 Requirements of current version

8. LST retrieved from TABI
A flowchart for LST retrieved from TABI
TABI-320 brightness temperature (BT) image
MWA needs
three parameters:
a). Transmittance
(t)
b). Emissivity (e)
c). Effective
mean
atmospheric
Temp. (Ta)
LST retrieval image
Determination of t:
with MODTRAN4 for 4 standard atmospheres
a) USA
b). Tropical
c). Mid-lat N
Summer
d). Mid-lat N
Winter
Determination of e:
Assigned for 7 land cover types:
Different combinations by vegetation, soil and water.
Determination
of Ta:
Calculated from
T0 for 4
Atmospheres
d). Mid-lat N Winter
T0: near surface air temperature (at 2 m high)

9. LST retrieved from TABI
Mono-window algorithm for LST retrieval
Where,
For T0= K
For T0= K
is TABI image in brightness temperature (K)
For more explanations for those parameters/coefficients, see the report.

10. LST retrieved from TABI
Transmittance simulated from water vapor with MODTRAN4
The estimation equations of transmittance from water vapor content for the 4 profiles have been shown on their corresponding figures

11. LST retrieved from TABI
Emissivity assigned for 7 types of land cover
For different combinations of vegetation, soil and water: e=
Determination of Ta calculated from T0
For the 4 standard atmospheric profiles:
1976 USA Ta= T0;
Tropical Ta= T0;
Mid-Lat-N-Summer Ta= T0;
Mid-Lat-N-Winter Ta= T0.
1. For substantial emissivity value for each land cover type, see the report.
2. Ta is effective mean atmospheric temperature; T0 is near surface air temperature available from a local meteorological observed station.

12. LST retrieved from TABI
Application case: Castle, Osaka, Japan
TABI BT image (oC X 100), 09/1/03,
7:50 am, Min/Max/Average:19.6/37.5/25.4oC
Retrieved LST image (oC X 100) 09/1/03, 7:50 am, Min/Max/Average:20.2/38.0/27.8oC

13. LST retrieved from TABI
Application case: Center, Osaka, Japan
TABI BT image (oC X 100)
Min/Max/Average:13.0/31.2/26.1oC
Retrieved LST image (oC X 100)
Min/Max/Average:13.5/35.2/28.6oC

14. LST retrieved from TABI
Requirements of current version
 Altitude around 1 kilometer
 Total atmospheric water vapor (g/cm2), measured from ground, for the 4 profiles: for 1976 USA, for Tropical, for Mid-lat-N summer, and for Mid-lat-N winter
 Input TABI brightness temperature in oC X 100
 Use a fixed value of emissivity over the entire scene of TABI image

15. LST retrieved from ASTER
 Flowchart for LST retrieval
 Split-window algorithm (SWA)
 Application case
 Requirements of current version

16. LST retrieved from ASTER
A flowchart for LST retrieved from ASTER
ASTER 13 & 14 scaled radiance, L-1B data
LST retrieval image
SWA needs two parameters:
a). Transmittance(t)
b). Emissivity (e)
Determination of t:
with MODTRAN4 for 4 standard atmospheres
a) USA
b). Tropical
c). Mid-lat N Summer
d). Mid-lat N Winter
Determination of e:
Assigned for 7 land cover types: Different combinations by vegetation, soil and water.
ASTER 13 & 14 brightness temperature (BT) image

17. LST retrieved from ASTER
Split-window algorithm for LST retrieval
Where,
For more explanations for those parameters/coefficients, see the report.

18. LST retrieved from ASTER
Calculation of BT for ASTER Ch13 & Ch14
Spectral radiance at sensor for Level 1B data:
Brightness temperatures for ASTER 13 & 14:
Where,

19. LST retrieved from ASTER
Transmittance simulated from wv with MODTRAN4 (I)
The estimation equations of transmittance from water vapor content (different ranges) for the 4 profiles have been shown on their corresponding figures

20. LST retrieved from ASTER
Transmittance simulated from wv with MODTRAN4 (II)
The estimation equations of transmittance from water vapor content (different ranges) for the 4 profiles have been shown on their corresponding figures

21. LST retrieved from ASTER
Emissivity assigned for 7 types of land cover
For different combinations of vegetation, soil and water: e=
For substantial emissivity value for each land cover type, see the report.

22. LST retrieved from ASTER
Application case: Tokyo, Japan
ASTER Ch 13 scaled radiance, September 05, 2003, at 10:35 am

23. LST retrieved from ASTER
Application case: Tokyo, Japan
ASTER Ch14 scaled radiance, September 05, 2003, at 10:35 am

24. LST retrieved from ASTER
Application case: Tokyo, Japan
Retrieved LST image (oC X 100)
Min/Max/Average:20.0/74.5/38.4oC

25. LST retrieved from ASTER
Requirements of current version
 Total atmospheric water vapor (g/cm2), measured from ground, for the 4 profiles: for 1976 USA, for Tropical, for Mid-lat-N summer, and for Mid-lat-N winter
 Input two ASTER thermal channels in digital number (scaled radiance)
 Use a fixed value of emissivity over the entire scene of ASTER image

26. LST retrieved from AVHRR
 Flowchart for LST retrieval
 Split-window algorithm (SWA)
 Application case
 Requirements of current version

27. LST retrieved from AVHRR
A flowchart for LST retrieved from AVHRR
LST retrieval image
SWA needs two parameters:
a). Transmittance
(t (q))
b). Emissivity (e)
Determination of t:
with LOWTRAN7 for 2 atmosphere profiles
a). Summer
b). Winter
Determination of e:
Assigned for 7 land cover types: Different combinations by vegetation, soil and water.
AVHRR 4 & 5 brightness temperature (BT) image
q: Zenith angle of viewing, ZAV

28. LST retrieved from AVHRR
Split-window algorithm for LST retrieval
(Based on Qin et al. (2001, JGR, 106(D19): )
Where,
For more explanations for those parameters/coefficients, see the report.

29. LST retrieved from AVHRR
Transmittance calculated from water vapor and ZAV (q)
For transmittances at ZAV (q=10o) for summer and winter profiles, refer to Table 4 (p22661) by Qin et al. (2001, JGR) for
and linear calculation equations of transmittance from water vapor.
For more explanations for those parameters/coefficients, see the report.

30. LST retrieved from AVHRR
Emissivity assigned for 7 types of land cover
For different combinations of vegetation, soil and water:
For substantial emissivity value for each land cover type, see the report.

31. LST retrieved from AVHRR
Application case: San Francisco, USA
AVHRR Ch4 BT image (K),
September 02, 1999, at 3:00 pm
AVHRR Ch5 BT image (K),
September 02, 1999, at 3:00 pm

32. LST retrieved from AVHRR
Application case: San Francisco, USA
Retrieved LST image (oC X 100)
Min/Max/Average:7.6/51.6/25.4oC

33. LST retrieved from AVHRR
Requirements of current version
 The algorithm with provided parameters’ values, either simulated or assigned, can be employed in the low- to middle-latitude regions of the Earth.
 Total atmospheric water vapor (g/cm2), measured from ground, for the 2 profiles, summer and winter is
 Input scaled brightness temperatures of both AVHRR channels (Ch 4 & Ch5)
 Use a fixed value of emissivity over the entire scene of AVHRR image

34. LST retrieved from TM(ETM+)
 Flowchart for LST retrieval
 Mono-window algorithm (MWA)
 Application case
 Requirements of current version

35. LST retrieved from TM(ETM+)
A flowchart for LST retrieved from TM(ETM+)
TM(ETM+)6 scaled radiance at sensor
TM (ETM+) 6 brightness temperature (BT) image
MWA needs
three parameters:
a). Transmittance
(t)
b). Emissivity (e)
c). Effective
mean
atmospheric
Temp. (Ta)
Determination of t:
with LOWTRAN7 for two profiles:
a). High T0=35oC
b). Low T0=18oC
Determination of e:
Assigned for 7 land cover types from diff. Combinations of Vegetation, soil and water.
Determination
of Ta:
Calculated from
T0 for 4 profiles:
a) USA
b). Tropical
c). Mid-lat N
Summer
d). Mid-lat N Winter
T0: near surface air temperature (at 2 m high)
LST retrieval image

36. LST retrieved from TM(ETM+)
Mono-window algorithm for LST retrieval
(Based on Qin et al. (2001, IJRS, 22(18): )
Where,
For more explanations for those parameters/coefficients, see the report.

37. LST retrieved from TM(ETM+)
Calculation of BT for TM (ETM+)6
Spectral radiance at sensor :
Brightness temperatures for TM6 or ETM+6:
Note: Using level 1G image for ETM+6 after July, 2000
Note: Using level 1G image for ETM+6 after July, 2000

38. LST retrieved from TM(ETM+)
Transmittance simulated from wv with LOWTRAN7
For transmittance for summer and winter profiles, see Table 5 (p3733) by Qin et al. (2001, IJRS) for linear calculation equations of transmittance from water vapor.
Emissivity assigned for 7 types of land cover
For different combinations of vegetation, soil and water: e=
Determination of Ta calculated from T0
1. For substantial emissivity value for each land cover type, see the report.
2. Ta is effective mean atmospheric temperature; T0 is near surface air temperature available from a local meteorological observed station.
For the 4 standard atmospheric profiles:
• 1976 USA Ta= •T0;
• Tropical Ta= •T0;
• Mid-Lat-N-Summer Ta= •T0;
• Mid-Lat-N-Winter Ta= •T0.

39. LST retrieved from TM(ETM+)
Application case: Lake Tahoe, CA/NV, USA
ETM+6 scaled radiance, October 25, 2001, at 10:30 am

40. LST retrieved from TM(ETM+)
Application case: Lake Tahoe, CA/NV, USA
Note that the small white patch near eastern lake may be caused by inputs of parameter values/pixel values out of limitation of the MWA. It will be fixed later on.
Retrieved LST image (oC X 100)
Min/Max/Average:1.1/45.7/19.1oC

41. LST retrieved from TM(ETM+)
Requirements of current version
 The algorithm with provided parameters’ values, either simulated or assigned, can be employed in most of the low- to middle-latitude regions of the Earth.
 Total atmospheric water vapor (g/cm2), measured from ground, for the 2 profiles, summer and winter is
 Input scaled radiance (DN) of TM6 or ETM+6
 Use a fixed value of emissivity over the entire scene of TM6 or ETM+6 image

42. Concluded Notes
 Both SWA and MWA for AVHRR and TM thermal images, developed by Qin et al. (2001), have been verified and validated properly. However,
 Both MWA and SWA for TABI and ASTER thermal images, developed in this project, have not been properly validated with ground truth.
 For current version of the MWA for TABI, the altitude is assumed around 1 km. If changing the altitude significantly, the estimation equations of transmittance from water vapor and derivation of Ta from T0 need to be re-simulated.
 Using a fixed emissivity over the entire scene of thermal image may be problematic for retrieving pixel-based LST.