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Generalized split-window algorithm for estimate of Land Surface Temperature from Chinese geostationary FengYun meteorological satellite (FY-2C) data

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SENSORS 2008年第2期8卷 933-951页

作者： Tang, Bohui Bi, Yuyun Li, Zhao-Liang Xia, Jun Chinese Acad Sci Key Lab Water Cycle & Related Land Surface Proc Inst Geog Sci & Nat Resources Res Beijing 100101 Peoples R China Grad Univ Chinese Acad Sci Beijing Peoples R China TRIO LSIIT UMR CNRS ENSPS 7005 F-67412 Illkirch Graffenstaden France Chinese Acad Agr Sci Inst Agr Resources & Reg Planning Beijing 100086 Peoples R China

On the basis of the radiative transfer theory, this paper addressed the estimate of Land Surface Temperature (LST) from the Chinese first operational geostationary meteorological satellite-FengYun-2C (FY-2C) data in two thermal infrared channels (IR1, 10.3-11.3 mu m and IR2, 11.5-12.5 mu m), using the Generalized split-window (GSW) algorithm proposed by Wan and Dozier (1996). The coefficients in the GSW algorithm corresponding to a series of overlapping ranging of the mean emissivity, the atmospheric Water Vapor Content (WVC), and the LST were derived using a statistical regression method from the numerical values simulated with an accurate atmospheric radiative transfer model MODTRAN 4 over a wide range of atmospheric and surface conditions. The simulation analysis showed that the LST could be estimated by the GSW algorithm with the Root Mean Square Error (RMSE) less than 1 K for the sub-ranges with the Viewing Zenith Angle (VZA) less than 30 degrees or for the sub-rangs with VZA less than 60 degrees and the atmospheric WVC less than 3.5 g/cm(2) provided that the Land Surface Emissivities (LSEs) are known. In order to determine the range for the optimum coefficients of the GSW algorithm, the LSEs could be derived from the data in MODIS channels 31 and 32 provided by MODIS/Terra LST product MOD11B1, or be estimated either according to the land surface classification or using the method proposed by Jiang et al. (2006);and the WVC could be obtained from MODIS total precipitable water product MOD05, or be retrieved using Li et al.' method (2003). The sensitivity and error analyses in term of the uncertainty of the LSE and WVC as well as the instrumental noise were performed. In addition, in order to compare the different formulations of the split-window algorithms, several recently proposed split-window algorithms were used to estimate the LST with the same simulated FY-2C data. The result of the intercomparsion showed that most of the algorithms give comparable result

关键词： Land Surface Temperature FY-2C data split-window algorithm

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Angular effect of MODIS emissivity products and its application to the split-window algorithm

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ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2011年第4期66卷 498-507页

作者： Ren, Huazhong Yan, Guangjian Chen, Ling Li, Zhaoliang Beijing Normal Univ State Key Lab Remote Sensing Sci Sch Geog Beijing 100875 Peoples R China Chinese Acad Sci Inst Geog Sci & Nat Resources Res Beijing 100101 Peoples R China

The angular effects of emissivity are ignored in current land surface temperature (LST) products. As a result, the directionality of these LST products limits their further application in many fields. Accurate correction of the angular problem of LST products requires explicit understanding of the angular effects of emissivity at the pixel scale. Currently, nearly ten years of global emissivity products of MODIS are available. However, the pixel-scale directionality of emissivity has never been analyzed. By performing a statistical analysis of 5-year MODIS emissivity products over most of East Asia, we generated the empirical relationships between the directional emissivity, land cover, and seasonal variations. Two look-up tables (LUTs) of directional emissivity were created for typical land cover types and applied to the generalized split-window algorithm to modify the MODIS LST. The results showed that the angular effect of emissivity could introduce a significant bias of -1-3 K to the 1 km resolution LST. Finally, the spatial scale effects of emissivity were analyzed, and it was found that the temperature differences caused by scale effects fell within +/-0.5 K for most pixels if 5 km emissivity was used in 1 km LST retrieval. Therefore, wide use of the LUTs can be expected. (C) 2011 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

关键词： MODIS emissivity Angular effects split-window algorithm

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A Practical split-window algorithm for Estimating Land Surface Temperature from Landsat 8 Data

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REMOTE SENSING 2015年第1期7卷 647-665页

作者： Du, Chen Ren, Huazhong Qin, Qiming Meng, Jinjie Zhao, Shaohua Peking Univ Inst Remote Sensing & Geog Informat Syst Beijing 100871 Peoples R China Minist Environm Protect Satellite Environm Applicat Ctr Beijing 100094 Peoples R China

This paper developed a practical split-window (SW) algorithm to estimate land surface temperature (LST) from Thermal Infrared Sensor (TIRS) aboard Landsat 8. The coefficients of the SW algorithm were determined based on atmospheric water vapor sub-ranges, which were obtained through a modified split-window covariance-variance ratio method. The channel emissivities were acquired from newly released global land cover products at 30 m and from a fraction of the vegetation cover calculated from visible and near-infrared images aboard Landsat 8. Simulation results showed that the new algorithm can obtain LST with an accuracy of better than 1.0 K. The model consistency to the noise of the brightness temperature, emissivity and water vapor was conducted, which indicated the robustness of the new algorithm in LST retrieval. Furthermore, based on comparisons, the new algorithm performed better than the existing algorithms in retrieving LST from TIRS data. Finally, the SW algorithm was proven to be reliable through application in different regions. To further confirm the credibility of the SW algorithm, the LST will be validated in the future.

关键词： Land Surface Temperature (LST) Landsat 8 split-window algorithm Thermal Infrared (TIR)

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Derivation of split-window algorithm to retrieve land surface temperature from MSG-1 thermal infrared data

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EUROPEAN JOURNAL OF REMOTE SENSING 2015年第1期48卷 719-742页

作者： Labbi, Abdelkader Mokhnache, Ammar Univ Constantine 1 Fac Exact Sci Dept Phys Constantine 25017 Algeria

One of the most important parameters in the exchange of energy between the ground and the atmosphere is the land surface temperature (LST). In this work, a split-window algorithm for deriving LST from the first Meteosat Second Generation satellite (MSG-1) data using the two thermal infrared channels IR10.8 and IR12.0 is proposed and validated with in-situ measured temperatures. This algorithm is obtained starting from the radiance transfer equation and requires the knowledge of total atmospheric water vapor content (TAWV) and the surface emissivity (epsilon(10.8) and epsilon(12)). First, we have simplified the Planck function to retrieve the radiance at MSG-1 from the temperature. Then, the Roberts model was used to create a relationship between atmospheric transmittance and TAWV. Next, sensitivity analysis of the algorithm indicates that the possible error of viewing angle has relatively insignificant impact on the probable LST estimation error, which is sensible to the possible error of ground emissivity and TAWV. Finally, two methods have been used to validate the proposed algorithm. On the one hand, the results show a root mean square error (RMSE) equals 0.79 K and an average accuracy equals 0.45 K for the comparison with another algorithm. On the other hand, the results show a RMSE equals 2.75 K and an average accuracy equals 1.96 K for the comparison with in-situ measurements. We conclude that the proposed algorithm is able to provide an accurate LST.

关键词： Land surface temperature split-window algorithm MSG-1 Roberts model total atmospheric water vapor content

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Practical split-window algorithm for retrieving land surface temperature over agricultural areas from ASTER data

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JOURNAL OF APPLIED REMOTE SENSING 2014年第1期8卷

作者： Wang, Songhan He, Longhua Southeast Univ Sch Transportat Nanjing 210096 Jiangsu Peoples R China Chinese Acad Sci Nanjing Inst Geog & Limnol Nanjing 210008 Jiangsu Peoples R China

A practical split-window algorithm which involves two parameters (transmittance and emissivity) utilized to retrieve land-surface temperature over agricultural areas from the Advanced Spaceborne Thermal Emission and Reflection Radiometer data is presented. First, by calculating the relationship between thermal radiation intensity and temperature, the Planck function is simplified using exponential function which is applied to deduce the split-window algorithm. Second, how to obtain transmittance from water vapor content and the method for estimating emissivity using normalized difference vegetation index are discussed in detail. Sensitivity analysis demonstrates that the algorithm is not sensitive to these two parameters. Finally, a standard atmospheric simulation method has been used to validate the proposed algorithm, and comparison between the algorithm and the prior study has been carried out. The results indicate that the average accuracy is 0.32 K for the case without error in both transmittance and emissivity, which is better than the prior algorithm. The accuracy is also 0.32 K when the transmittance is computed from the water content by piecewise cubic polynomial fit. The accuracy is about 0.30 K similar to 0.33 K corresponding to different Pv (Pv is the proportion of vegetation) values, which indicates that this algorithm is suitable for different land surface types over agricultural areas. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： Land-surface temperature Advanced Spaceborne Thermal Emission and Reflection Radiometer split-window algorithm Planck function

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A radiance-based split-window algorithm for land surface temperature retrieval: Theory and application to MODIS data

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INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 2019年 76卷 204-217页

作者： Wang, Mengmeng He, Guojin Zhang, Zhaoming Wang, Guizhou Wang, Zhihua Yin, Ranyu Cui, Shiai Wu, Zhijie Cao, Xiaojie China Univ Geosci Wuhan Fac Informat Engn Wuhan Hubei Peoples R China Chinese Acad Sci Inst Remote Sensing & Digital Earth Beijing Peoples R China Key Lab Earth Observat Hainan Prov Sanya Peoples R China Chinese Acad Sci Inst Geog Sci & Nat Resources Res State Key Lab Resources & Environm Informat Syst Beijing Peoples R China Longyan Univ Coll Resources Engn Longyan Peoples R China

The split-window algorithm is the most commonly used method for land surface temperature (1ST) retrieval from satellite data. Simplification of the Planck's function, as an important step in developing the SWA, allows us to directly relate the radiance to the temperature toward solving the radiative transfer equation (RTE) set. In this study, Planck's radiance relationship between two adjacent thermal infrared channels was modeled to solve the RTE set instead of simplification of the Planck's function. A radiance-based split-window algorithm (RBSWA) was developed and applied to Moderate Resolution Imaging Spectroradiometer (MODIS) data. The performance of the RBSWA was assessed and compared with three most common brightness temperature-based split-window algorithms (BTBSWAs) by using the simulated data and satellite measurements. Simulation analysis showed that the 1ST retrieval using RBSWA had a Root Mean Square Error (RMSE) of 0.5 K and achieved an improvement of 0.3 K compared with three BTBSWAs, and the 1ST retrieval accuracy using RBSWA was better than 1.5 K considering uncertainties in input parameters based on the sensitivity analysis. For application of RBSWA to MODIS data, the results showed that: 1) comparison between 1ST from MODIS 1ST product and 1ST retrieved using RBSWA showed a mean RMSE of 1.33 K for 108 groups of MODIS image covering continental US, which indicates RBSWA is reliable and robust;2) when using the measurements from US surface radiation budget network as real values the RMSE of the RBSWA algorithm was 2.55 K and was slightly better than MODIS 1ST product;and 3) through the cross validation using Advanced Spaceborne Thermal Emission and Reflection Radiometer 1ST product, the RMSE of the RBSWA algorithm was 2.23 K and was 0.28 K less than that of MODIS 1ST product. We conclude that the RBSWA for 1ST retrieval from MODIS data can attain a better accuracy than the BTBSWA.

关键词： Land surface temperature split-window algorithm Simplification of Planck's function MODIS

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HIGH-RESOLUTION LAND SURFACE TEMPERATURE RETRIEVAL FROM GF5-02 VIMI DATA USING AN OPERATIONAL split-window algorithm

HIGH-RESOLUTION LAND SURFACE TEMPERATURE RETRIEVAL FROM GF5-...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Heidarian, Peyman Li, Hua Zhang, Zelin Li, Ruibo Liu, Qinhuo Tan Yumin Beihang Univ Sch Transportat Sci & Engn Beijing 102200 Peoples R China Chinese Acad Sci Aerosp Informat Res Inst Beijing 100101 Peoples R China

ISBN: (纸本)9798350360332;9798350360325

High-resolution land surface temperature (LST) product holds significant importance in quantifying surface heat, monitoring climate change, assessing environmental health, and water resource management. Therefore, accurate LST retrieval improves our understanding of detailed thermal characteristics of the Earth's surface. In this research, we developed an operational split-window algorithm for generationg high-resolution LST products from Gaofen5-02 (GF5-02) Visible and Infrared Multispectral Imager (VIMI) data. The coefficients of the split-window algorithm are simulated utilizing the MODTRAN 5.2 atmospheric radiative transfer model, with the global atmospheric profile library of SeeBor V5.0. The land surface emissivities in VIMI bands 11 and 12 are estimated using the ASTER global emissivity dataset (GED) based on the vegetation cover method. The GF5-02 VIMI LSTs are validated using in-situ data collected from the Huailai experiment site in China. Preliminary results show the accuracy of the GF5-02 LST products is satisfactory, exhibiting a bias of -0.03 K and a Root Mean Square Error (RMSE) of 2.42 K.

关键词： Land surface temperature emissivity split-window algorithm validation

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Retrieval of Land Surface Temperature from Landsat 8 OLI and TIRS: A Comparative Analysis Between Radiative Transfer Equation-Based Method and split-window algorithm

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Remote Sensing in Earth Systems Sciences 2023年第1-2期6卷 1-21页

作者： Ali, Sk Ajim Parvin, Farhana Ahmad, Ateeque Department of Geography Aligarh Muslim University (AMU) UP Aligarh 202002 India

The system of observation and capturing the earth resource features have been improving with the scientific revolution and technological development in remote sensing techniques. In comparison with the previous Landsat series, Landsat 8 OLI and TIRS (Operational Land Imager and Thermal Infrared Sensor) is the latest applications of thermal infrared sensor for the Landsat project offers two adjacent thermal bands that has a great advantage for retrieving land surface temperature. In this study, an effort was made to compare two different approaches of land surface temperature retrieval method from TIRS data including the radiative transfer equation (RTE) and the split-window algorithm (SWA). The objective of this study was to estimate land surface temperature from TIRS data of Landsat 8 using different techniques and compare with actual ground temperature for pre-monsoon, monsoon, and post-monsoon season to determine accurate technique and thermal band. In this regard, twelve ground stations such as New Delhi, Noida, Ghaziabad, Bulandshahr, Gurugram, Faridabad, Muradnagar, Safdarjung airport, Indira Gandhi international airport, Rajiv Chowk, Dadri, and Kirti Nagar were marked on Landsat 8 product with Path 146 and Row 40. Based on analysis, the result shows that the radiative transfer equation (RTE) using band 10 has highest accuracy with the lowest root mean square error (1.0334 ℃, 1.5189 ℃, and 1.4197 ℃, respectively for pre-monsoon, monsoon, and post-monsoon), while RTE using band 11 and split-window algorithm (SWA) using band 10 and 11 has lower accuracy with higher root mean square error (> 2.0 ℃ in all cases). Thus, it is recommended that for those methods LST retrieval using single band, band 10 using RTE has higher accuracy than band 11 and split-window algorithm. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Land surface temperature Landsat 8 OLI and TIRS Radiative transfer equation split-window algorithm

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LAND SURFACE TEMPERATURE RETRIEVAL FROM NIGHTTIME MID-INFRARED MODIS DATA USING A split-window algorithm

LAND SURFACE TEMPERATURE RETRIEVAL FROM NIGHTTIME MID-INFRAR...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Fang, Lingyu Lie, Hua Sun, Lin Li, Ruibo Shandong Univ Sci & Technol Coll Geodesy & Geomat Qingdao 266590 Peoples R China Chinese Acad Sci Aerosp Informat Res Inst State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China

ISBN: (纸本)9781665403696

In this study, a split-window(SW) algorithm is tested to retrieve the land surface temperature (LST) from nighttime mid-infrared MODIS data. At first, the SW algorithm's coefficients were derived using MODTRAN simulations with the TIGR atmospheric profile database. Then, the input emissivities of the SW algorithm were directly calculated using the MODIS MYD11B1 products. At last, the LST was retrieved using the Aqua MODIS bands 22 and 23 data. The retrieved LSTs were compared with the MODIS MYD11A1 products and validated using ground measurements collected from four ground sites in northwest China. The validation results indicate that the developed SW algorithm provides better accuracy than the MYD11A1 LST products, with a mean bias of -0.76K and a mean root-mean-square error (RMSE) of 1.3K. Experiments show that the split-window algorithm is also applicable in the mid-infrared channel at night, and can produce accurate land surface temperature results.

关键词： MODIS land surface temperature split-window algorithm mid-infrared

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HIGH-RESOLUTION SEA SURFACE TEMPERATURE RETRIEVAL FROM GF5-02 VIMI DATA USING A NONLINEAR split-window algorithm

HIGH-RESOLUTION SEA SURFACE TEMPERATURE RETRIEVAL FROM GF5-0...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Tan, Mingming Li, Hua Xin, Xiangrong Li, Ruibo Lu, Yifan Xiao, Qing Chinese Acad Sci Aerosp Informat Res Inst Beijing 100094 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Shandong Univ Sci & Technol Sch Surveying & Spatial Informat Qingdao 266590 Peoples R China

ISBN: (纸本)9798350360332;9798350360325

Sea Surface Temperature (SST) is a pivotal parameter in studying the energy balance and material exchange between the ocean and the atmosphere. Obtaining high-precision SST is of significant importance for a deep understanding of the dynamic changes in the ocean and atmospheric systems. This study utilized a nonlinear split-window algorithm for deriving 40m SST from Chinese Gaofen5-02 (GF5-02) Visible and Infrared Multispectral Imager (VIMI). The coefficients of the algorithm were simulated utilizing the MODTRAN 5.2 atmospheric radiative transfer model and the global atmospheric profile library of SeeBor V5.0. The retrieved VIMI SST was validated using iQuam SST measurements (in-situ measurements) and the MODIS SST products. The results of the cross-validation demonstrate a reasonable accuracy of the produced VIMI SST products, exhibiting a bias of 1.34 K and an RMSE of 2.68 K.

关键词： GF5-02 satellite sea surface temperature split-window algorithm validation

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