Temperature-independent spectral indices in thermal infrared bands

Becker, F.; Li, Zhao-Liang

doi:10.1016/0034-4257(90)90095-4

Cited by 329 publications

(148 citation statements)

References 17 publications

Supporting

Mentioning

142

Contrasting

Unclassified

Order By: Relevance

“…Emissivity may differ according to the viewing angle, surface moisture, and roughness as well as with vegetation [16,27]. Notwithstanding the fact that there are many algorithms that have been proposed for the estimation of LSE [28][29][30][31], in this study, the estimation of LSE with prior known LSE has been used. This is because the algorithm is more practical and has a reasonable accuracy [16,32,33].…”

Section: Estimation Of Land Surface Emissivity (Lse)mentioning

confidence: 99%

Inversion of Land Surface Temperature (LST) Using Terra ASTER Data: A Comparison of Three Algorithms

Ndossi

Avdan

2016

Remote Sensing

View full text Add to dashboard Cite

Land Surface Temperature (LST) is an important measurement in studies related to the Earth surface's processes. The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) instrument onboard the Terra spacecraft is the currently available Thermal Infrared (TIR) imaging sensor with the highest spatial resolution. This study involves the comparison of LSTs inverted from the sensor using the Split Window Algorithm (SWA), the Single Channel Algorithm (SCA) and the Planck function. This study has used the National Oceanic and Atmospheric Administration's (NOAA) data to model and compare the results from the three algorithms. The data from the sensor have been processed by the Python programming language in a free and open source software package (QGIS) to enable users to make use of the algorithms. The study revealed that the three algorithms are suitable for LST inversion, whereby the Planck function showed the highest level of accuracy, the SWA had moderate level of accuracy and the SCA had the least accuracy. The algorithms produced results with Root Mean Square Errors (RMSE) of 2.29 K, 3.77 K and 2.88 K for the Planck function, the SCA and SWA respectively.

show abstract

Section: Estimation Of Land Surface Emissivity (Lse)mentioning

confidence: 99%

Inversion of Land Surface Temperature (LST) Using Terra ASTER Data: A Comparison of Three Algorithms

Ndossi

Avdan

2016

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…T a , T c and T s are air, canopy and soil temperature, respectively. The fractional vegetation cover at a certain view angle Â was used to partition the satellite-based directional radiometric temperature (Becker and Li, 1990;Norman et al, 1995) as follows:…”

Section: P-tseb and S-tsebmentioning

confidence: 99%

Intercomparison of remote sensing‐based models for estimation of evapotranspiration and accuracy assessment based on SWAT

Gao

Long

2008

Hydrological Processes

View full text Add to dashboard Cite

Abstract:An intercomparison of daily actual evapotranspiration (ET) estimates from the single-source models (SEBAL and SEBS) and the two-source models (P-TSEB and S-TSEB) using remotely sensed data was performed to examine their utilities and limitations under a wide range of land covers and different meteorological conditions. The accuracy of ET estimates from remote sensing-based models of a selected watershed on 23 June 2005 (DOY 174) presenting large air drying power and marked contrast in underlying surface characteristics, and 25 July 2005, (DOY 206) in contrast to the meteorological and underlying surface conditions of DOY 174, were evaluated in terms of SWAT-based ET. The ET estimates from the two methodologies are shown to be comparable, indicating that S-TSEB has the highest accuracy with relative errors of 2Ð2% and 5Ð6% with reference to SWAT-based ET for DOY 174 and 206, respectively. Hence it was selected to be the basis for performing an intercomparison with other remote sensing-based models. Single-source models are very sensitive to KB 1 parameter, rendering marked differences in ET estimates because of different treatments of roughness length for heat transfer. SEBAL and SEBS yielded mean absolute percentage difference (MAPD) versus S-TSEB within 26Ð22% and 26Ð56% for DOY 174 and within 9Ð11% and 11Ð69% for DOY 206, respectively, indicating their applicability to higher vegetation cover and soil moisture availability areas under small air drying power condition. P-TSEB generated MAPD versus S-TSEB within 41Ð15% for DOY 174 and 8Ð79% for DOY 206, implying that P-TSEB is highly consistent with S-TSEB under small air drying power and less contrast in soil moisture conditions, whereas noticeable discrepancies occur under large air drying power and marked contrast in soil moisture circumstances, in particular for sparse cover. The performance of P-TSEB largely depends on the meteorological and underlying surface conditions, both exerting significant influences on the extent of coupling between vegetation and soil.

show abstract

“…2) 연구방법 Cho et al(2015)가 개선한 기존의 알고리즘(CSW_v2.0)은 다양한 대기 조건에 대하여 휘도온도차, 지표면 방출율, Frey et al, 2012, Cho andSuh, 2013b;Li et al, 2013). μm을 사용하여 복사전달방정식을 계산하는 방법 (Becker and Li, 1990;Wan and Dozier, 1996)으로 다음 식…”

Section: 서 론unclassified

Improvement of COMS land surface temperature retrieval algorithm by considering diurnal variation of air temperature

Choi¹,

Suh²

2016

Korean Journal of Remote Sensing

View full text Add to dashboard Cite

: Land Surface Temperature (LST) has been operationally retrieved from the Communication, Ocean, and Meteorological Satellite (COMS) data by the spilt-window method (CSW_v2.0) developed by Cho et al. (2015). Although the CSW_v2.0 retrieved the LST with a reasonable quality compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data, it showed a relatively poor performance for the strong inversion and lapse rate conditions. To solve this problem, the LST retrieval algorithm (CSW_v2.0) was updated using the simulation results of radiative transfer model (MODTRAN 4.0) by considering the diurnal variations of air temperature. In general, the upgraded version, CSW_v3.0 showed a similar correlation coefficient between the prescribed LSTs and retrieved LSTs (0.99), the relatively smaller bias (from -0.03 K to-0.012 K) and the Root Mean Square Error (RMSE) (from 1.39 K to 1.138 K). Particularly, CSW_v3.0 improved the systematic problems of CSW_v2.0 that were encountered when temperature differences between LST and air temperature are very large and/or small (inversion layers and superadiabatic lapse rates), and when the brightness temperature differences and surface emissivity differences were large. The bias and RMSE of CSW_v2.0 were reduced by 10-30% in CSW_v3.0. The indirect validation results using the MODIS LST data showed that CSW_3.0 improved the retrieval accuracy of LST in terms of bias (from -0.629 K to -0.049 K) and RMSE (from 2.537 K to 2.502 K) compared to the CSW_v2.0.

show abstract

Temperature-independent spectral indices in thermal infrared bands

Cited by 329 publications

References 17 publications

Inversion of Land Surface Temperature (LST) Using Terra ASTER Data: A Comparison of Three Algorithms

Inversion of Land Surface Temperature (LST) Using Terra ASTER Data: A Comparison of Three Algorithms

Intercomparison of remote sensing‐based models for estimation of evapotranspiration and accuracy assessment based on SWAT

Improvement of COMS land surface temperature retrieval algorithm by considering diurnal variation of air temperature

Contact Info

Product

Resources

About