Modified linear scaling and quantile mapping mean bias correction of MODIS land surface temperature for surface air temperature estimation for the lowland areas of Peninsular Malaysia

MODIS land surface temperature data (MODIS Ts) products are quantified from the earth surface’s reflected thermal infrared signal via sensors onboard the Terra and Aqua satellites. MODIS Ts products are a great value to many environmental applications but often subject to discrepancies when compared...

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Main Authors: Saiful Bahari, Nurul Iman, Muharam, Farrah Melissa, Zulkafli, Zed, Mazlan, Norida, Husin, Nor Azura
Format: Article
Published: MDPI 2021
Online Access:http://psasir.upm.edu.my/id/eprint/94237/
https://www.mdpi.com/2072-4292/13/13/2589
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spelling my.upm.eprints.942372023-05-09T01:51:02Z http://psasir.upm.edu.my/id/eprint/94237/ Modified linear scaling and quantile mapping mean bias correction of MODIS land surface temperature for surface air temperature estimation for the lowland areas of Peninsular Malaysia Saiful Bahari, Nurul Iman Muharam, Farrah Melissa Zulkafli, Zed Mazlan, Norida Husin, Nor Azura MODIS land surface temperature data (MODIS Ts) products are quantified from the earth surface’s reflected thermal infrared signal via sensors onboard the Terra and Aqua satellites. MODIS Ts products are a great value to many environmental applications but often subject to discrepancies when compared to the air temperature (Ta) data that represent the temperature measured at 2 m above the ground surface. Although they are different in their nature, the relationship between Ts and Ta has been established by many researchers. Further validation and correction on the relationship between these two has enabled the estimation of Ta from MODIS Ts products in order to overcome the limitation of Ta that can only provide data in a point form with a very limited area coverage. Therefore, this study was conducted with the objective to assess the accuracy of MODIS Ts products, i.e., MOD11A1, MOD11A2, MYD11A1, and MYD11A2 against Ta and to identify the performance of a modified Linear Scaling using a constant and monthly correction factor (LS-MBC), and Quantile Mapping Mean Bias Correction (QM-MBC) methods for lowland area of Peninsular Malaysia. Furthermore, the correction factor (CF) values for each MBC were adjusted according to the condition set depending on the different bias levels. Then, the performance of the pre- and post-MBC correction for by stations and regions analysis were evaluated through root mean square error (RMSE), percentage bias (PBIAS), mean absolute error (MAE), and correlation coefficient (r). The region dataset is obtained by stacking the air temperature (Ta_r) and surface temperature (Ts_r) data corresponding to the number of stations within the identified regions. The assessment of pre-MBC data for both 36 stations and 5 regions demonstrated poor correspondence with high average errors and percentage biases, i.e., RMSE = 3.33–5.42 °C, PBIAS = 1.36–12.07%, MAE = 2.88–4.89 °C, and r = 0.16–0.29. The application of the MBCs has successfully reduced the errors and bias percentages, and slightly increased the r values for all MODIS Ts products. All post-MBC depicted good average accuracies (RMSE and MAE < 3 °C and PBIAS between ±5%) and r between 0.18 and 0.31. In detail, for the station analysis, the LS-MBC using monthly CF recorded better performance than the LS-MBC using constant CF or the QM-MBC. For the regional study, the QM-MBC outperformed the others. This study illustrated that the proposed LS-MBC, in spite of its simplicity, managed to perform well in reducing the error and bias terms of MODIS Ts as much as the performance of the more complex QM-MBC method. MDPI 2021-07-02 Article PeerReviewed Saiful Bahari, Nurul Iman and Muharam, Farrah Melissa and Zulkafli, Zed and Mazlan, Norida and Husin, Nor Azura (2021) Modified linear scaling and quantile mapping mean bias correction of MODIS land surface temperature for surface air temperature estimation for the lowland areas of Peninsular Malaysia. Remote Sensing, 13 (13). art. no. 2589. pp. 1-28. ISSN 2072-4292 https://www.mdpi.com/2072-4292/13/13/2589 10.3390/rs13132589
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description MODIS land surface temperature data (MODIS Ts) products are quantified from the earth surface’s reflected thermal infrared signal via sensors onboard the Terra and Aqua satellites. MODIS Ts products are a great value to many environmental applications but often subject to discrepancies when compared to the air temperature (Ta) data that represent the temperature measured at 2 m above the ground surface. Although they are different in their nature, the relationship between Ts and Ta has been established by many researchers. Further validation and correction on the relationship between these two has enabled the estimation of Ta from MODIS Ts products in order to overcome the limitation of Ta that can only provide data in a point form with a very limited area coverage. Therefore, this study was conducted with the objective to assess the accuracy of MODIS Ts products, i.e., MOD11A1, MOD11A2, MYD11A1, and MYD11A2 against Ta and to identify the performance of a modified Linear Scaling using a constant and monthly correction factor (LS-MBC), and Quantile Mapping Mean Bias Correction (QM-MBC) methods for lowland area of Peninsular Malaysia. Furthermore, the correction factor (CF) values for each MBC were adjusted according to the condition set depending on the different bias levels. Then, the performance of the pre- and post-MBC correction for by stations and regions analysis were evaluated through root mean square error (RMSE), percentage bias (PBIAS), mean absolute error (MAE), and correlation coefficient (r). The region dataset is obtained by stacking the air temperature (Ta_r) and surface temperature (Ts_r) data corresponding to the number of stations within the identified regions. The assessment of pre-MBC data for both 36 stations and 5 regions demonstrated poor correspondence with high average errors and percentage biases, i.e., RMSE = 3.33–5.42 °C, PBIAS = 1.36–12.07%, MAE = 2.88–4.89 °C, and r = 0.16–0.29. The application of the MBCs has successfully reduced the errors and bias percentages, and slightly increased the r values for all MODIS Ts products. All post-MBC depicted good average accuracies (RMSE and MAE < 3 °C and PBIAS between ±5%) and r between 0.18 and 0.31. In detail, for the station analysis, the LS-MBC using monthly CF recorded better performance than the LS-MBC using constant CF or the QM-MBC. For the regional study, the QM-MBC outperformed the others. This study illustrated that the proposed LS-MBC, in spite of its simplicity, managed to perform well in reducing the error and bias terms of MODIS Ts as much as the performance of the more complex QM-MBC method.
format Article
author Saiful Bahari, Nurul Iman
Muharam, Farrah Melissa
Zulkafli, Zed
Mazlan, Norida
Husin, Nor Azura
spellingShingle Saiful Bahari, Nurul Iman
Muharam, Farrah Melissa
Zulkafli, Zed
Mazlan, Norida
Husin, Nor Azura
Modified linear scaling and quantile mapping mean bias correction of MODIS land surface temperature for surface air temperature estimation for the lowland areas of Peninsular Malaysia
author_facet Saiful Bahari, Nurul Iman
Muharam, Farrah Melissa
Zulkafli, Zed
Mazlan, Norida
Husin, Nor Azura
author_sort Saiful Bahari, Nurul Iman
title Modified linear scaling and quantile mapping mean bias correction of MODIS land surface temperature for surface air temperature estimation for the lowland areas of Peninsular Malaysia
title_short Modified linear scaling and quantile mapping mean bias correction of MODIS land surface temperature for surface air temperature estimation for the lowland areas of Peninsular Malaysia
title_full Modified linear scaling and quantile mapping mean bias correction of MODIS land surface temperature for surface air temperature estimation for the lowland areas of Peninsular Malaysia
title_fullStr Modified linear scaling and quantile mapping mean bias correction of MODIS land surface temperature for surface air temperature estimation for the lowland areas of Peninsular Malaysia
title_full_unstemmed Modified linear scaling and quantile mapping mean bias correction of MODIS land surface temperature for surface air temperature estimation for the lowland areas of Peninsular Malaysia
title_sort modified linear scaling and quantile mapping mean bias correction of modis land surface temperature for surface air temperature estimation for the lowland areas of peninsular malaysia
publisher MDPI
publishDate 2021
url http://psasir.upm.edu.my/id/eprint/94237/
https://www.mdpi.com/2072-4292/13/13/2589
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score 13.211869