# Presentation: 380463

## Estimation of Broadband Emissivity from ASTER TIR Using Spectral Libraries

- May 21-22, 2002
- Ecosystem Working Group, ASTER Science Team Meeting
- Kenta Ogawa*+, Thomas Schmugge*, Frederic Jacob* and Andrew French*
- *USDA/ARS Hydrology and Remote Sensing Lab., +Hitachi Ltd.

**Notes:**
Today, I would like to talk about estimation of broadband emissivity from ASTER data.  The purpose of this study is to estimating long-wave surface broadband emissivity using ASTER data for land surface energy balance.

## Energy balance at land surface

** ... broadband emissivity

**Notes:**
Let me review the energy balance at land surface.  Wavelength of electromagnetic wave can be divided in short-wave and long-wave.  Short-wave energy came from sun and some portion of them are reflected at surface.  We focus on long-wave.  The rage will be 3 - 100 micron.  The down welling energy come from atmosphere and clouds if there are.  

During the daytime, upwelling radiance is larger than down welling radiance.  The net radiation can be express as this.  The electromagnetic energy will be converted to sensitive heat flux, latent heat flux, and/or ground heat flux.  

The upwelling energy can express using Stephan Boltzman’s constant.  The energy is proportional to the fourth power of surface temperature and also proportional to emissivity.  

Because we have little information of distribution of surface emissivity, a constant emissivity is often used for land surface in energy balance study and general circulation models, GCMs.  We are looking for the possibility to reduce the uncertainty.  The spatial variation of broadband emissivity may cause a feedback and affect surface temperature.

## Long-wave energy balance

- Net radiation at long-wave (*Rn**L*) is proportional to emissivity

**
- B()...Plank function
- with Kirchhoff’s Law

**Notes:**
Surface broadband thermal infrared emissivity is an important parameter for estimating the long-wave surface energy balance.  
Surface broadband emissivity is an important parameter for estimating the long-wave surface energy.  Mostly, the broadband emissivity may vary significantly, because the spectral emissivity variation ranges from 0.7 to 1.0 for bare soils and rocks (see Fig. 1) in the 8-12 m range, there is smaller variation in the 5-8 m and 12-14 m ranges.  

## Effect of uncertainty in emissivity

- 0.1 in broadband emissivity
- (0.9 ~ 1.0)

*L*↑* - **L*↓
- long-wave net radiation
- 150 W/m2

- 15 [W m-2] in net radiation
- (135 ~ 150 [W m-2] )

- 3 K in surface temperature or
- 200 mm y-1 in evaporation

- Radiation forcing
- by green house gases: 2.5 W/m2
- since 1900

**Notes:**
This is an example how the uncertainty of emissivity can affect the surface energy balance study.  Let me assume the net radiation is 150 W/m2 and the uncertainty is 0.1.  As I said before, the net radiation is proportional to emissivity, then the uncertainty will be 15 W/m2.  The difference is about corresponding to the emission from surface temperature in 3 K or 200 mm/y in evaporation.  Of course it is NOT realistic that the all difference will be converted to evaporation, but you can understand that 15 W/m2 is significant value.  

We also note that the radiation forcing by all green house gases including carbon dioxide, is about 2-3 W/m2 (in global average).  

## Effect of uncertainty in emissivity

- 0.1 in emissivity
- (0.9 ~ 1.0)

- Radiation forcing
- by green house gases: about
- 2.5 W/m2

- 0.02
- using ASTER

- 15 [W m-2] in net radiation
- (135 ~ 150 [W m-2] )

- 3 K in surface temperature or
- 200 mm y-1 in evaporation

**Notes:**
The purpose of this study is to reduce the uncertainty of broadband emissivity.  If we can reduce the uncertainty to the equivalent to ASTER/TIR channel spectral emissivity: 0.02, the uncertainty that come from uncertainty of emissivity will be reduced to less than 3 W/m2.  

## Overview

**Notes:**
This diagram shows the overview of this study.  

First we used ASTER/TIR data to get five channel spectral emissivity through atmospheric correction and temperature emissivity separation.

Next, we assumed to express the broadband emissivity as a linear combination of channel emissivities of ASTER/TIR.  

To get the linear model, we produced a dataset of the broadband emissivity, and channel emissivities for ASTER/TIR, using spectral libraries.  Then we calibrate and validate a regression using the dataset.  

Finally, we estimated broadband emissivities with ASTER/TIR using the calibrated linear model.  

## Spectral libraries

- ASTER Spectral library
- John Hopkins University (JHU)
- MODIS Emissivity library
- University of California Santa Barbara (UCSB)
- Soil, vegetation, water, ice, snow, and rock samples (257 samples)

**Notes:**
We used two spectral library, JHU and UCSB.  

We focused on natural terrestrial materials such as soil, vegetation, water, ice, snow, and rock.

This slide shows you the average and range of spectral emissivity for data from both libraries.  The range is larger both over [3 – 5] m and [8 – 10] m regions than in other wavelength regions.  Because the emitted energy is low over 3 to 5 m at around 300 K, it is expected that the emissivity from 8 to 10 m (ASTER channel 10, 11, 12) will strongly affect the broadband emissivity.  

## Definition of broadband emissivity

***1**, ****2*: 3, 14 m
- Surface temperature, *T*: 300 [K]
- B(**)...Planck function

**Notes:**
We defined the broadband emissivity.  

Where  is surface thermal infrared emissivity,  is the wavelength, B is the Planck function, and T is surface temperature.  In this study, we selected a wavelength range, 1=3.3 m to 2=14.0 m, since spectral libraries covered this wavelength range.  We assume T = 300 K in this analysis.  We computed the difference of broadband emissivity caused by variation of target temperature.  It was smaller than 0.005 over the range from 270 K to 330 K.  We note that the emission at wavelengths longer than 14 m is about 40 % to 50 % of the total blackbody radiation and that we have no spectral emissivity data of these longer wavelengths.  

Where  is surface thermal infrared emissivity,  is the wavelength, B is the Planck function, and T is surface temperature.  In this study, we selected a wavelength range, 1=3.3 m to 2=14.0 m, since spectral libraries covered this wavelength range.  We assume T = 300 K in this analysis.  We computed the difference of broadband emissivity caused by variation of target temperature.  It was smaller than 0.005 over the range from 270 K to 330 K.  We note that the emission at wavelengths longer than 14 m is about 40 % to 50 % of the total blackbody radiation and that we have no spectral emissivity data of these longer wavelengths.  

## Histogram of broadband emissivity

**Notes:**
They ranged from 0.89 to 0.99 for natural surfaces, such as, rocks, soils, vegetation, water, ice, and snow.

The calculated broadband emissivities range from 0.885 to 0.994.  Mean emissivity of rock, soil, vegetation, and water is 0.938, 0.955, 0.967, and 0.982 respectively.

Note: vegetation samples are single leafs 

## Estimation of broadband emissivity

- Multiple linear regression

***** **= a**10** ****10** + a**11** ****11** + a**12** ****12** **	**	**+ a**13** ****13** + a**14** ****14** + c*

***N **	*...emissivity of channel N
*a**N**	*...coefficients
*c**	*...constant

**Notes:**
Then, we assumed that the broadband emissivity can be expressed as a linear combination emissivities for the five ASTER/TIR channels.
We assume that broadband emissivity can be expressed in (3) as:  

The center wavelengths of ASTER channel 10 to 14 are 8.3, 8.65, 9.1, 10.6, 11.3 m, respectively.  Then we calibrate and validate the coefficients of (3) using two spectral libraries.

We did not include the effect of ASTER emissivity product error at this time.

## Results of regression

- Calibration (JHU)
- 150 samples
- RMSE: 0.006, Max error: 0.023
- Validation (UCSB)
- 107 samples
- RMSE: 0.005, Max error: 0.016
- Larger error in mafic rock (low SiO2 contents)
- Bias for high emissivity (> 0.97) samples

**Notes:**
The linear regression was calibrated using JHU Library and validated with the UCSB Library.  The absolute error on the estimated broadband emissivity was less than 0.01 for 93 % of all samples and RMSE was 0.0051 over an emissivity range from 0.91 to 0.99 in validation.  

## Broadband emissivity map from ASTER

- Jornada, New Mexico, USA in May, 2001

- Low emissivity in bare soil
- High emissivity in mountain and agricultural fields

**Notes:**
Finally, this calibrated regression was applied to emissivities computed from the data acquired with ASTER/TIR over the Jornada Experimental Range in New Mexico to produce a map of broadband emissivity for this area.

This calibrated regression was finally applied to emissivities computed from ASTER/TIR data acquired over the Jornada Experimental Range in New Mexico.  The result is shown in Fig. 3.  The histogram of extracted emissivities is shown in Fig. 4.  Emissivities range from 0.93 to 0.97 with the average ~0.95.  

The yellow and red area in the upper center to lower center of the image corresponds to a ridge with a few vegetation.  Another bright area in lower left corresponds to agricultural fields along the Rio Grande River.  These areas have higher emissivities range from 0.96 to 0.97.  

The blue area at upper left and right edge is bare soil or sparsely vegetated sites.  The upper right area is for the gypsum  at white sand.  These areas have lower emissivities that range from 0.93 to 0.95.  

## Conclusion & future study

- Conclusion
- Using ASTER TIR emissivity, we can estimate broadband emissivity with error less than 0.01 RMSE
- excluding atmospheric correction, TES
- Future study
- Evaluate include ASTER emissivity errors
- Validate with ground truth of net radiation
- Apply the method to surface energy balance model

**Notes:**
The results of the spectral libraries analysis suggest that the estimation of broadband emissivity of 3-14 mm using the linear regression from emissivities of ASTER/TIR channels is potentially accurate and the expected RMSE is lower than 0.01 for the emissivity range from 0.90 to 0.99.  
The estimated broadband emissivity using the regression in Jornada site showed the variation of 0.04, from 0.93 to 0.97.  

This study was supported by the ASTER Project of NASA’s EOS-Terra Program.  

## Questions?

- Contact
- E-mail: _[kenta@hydrolab.arsusda.gov](mailto:kenta@hydrolab.arsusda.gov)_
- More Information
- http://hydrolab.arsusda.gov/~kenta/