Jointing Adjacent Environmental Variation Into a Deep Learning Model for Gap-Filling Passive Microwave-Based Land Surface Temperature | IEEE Journals & Magazine | IEEE Xplore

Jointing Adjacent Environmental Variation Into a Deep Learning Model for Gap-Filling Passive Microwave-Based Land Surface Temperature


Abstract:

Passive microwave-based land surface temperature (PMW LST) serves as a significant source for complementary thermal infrared LST, whereas the orbit gaps frequently result...Show More

Abstract:

Passive microwave-based land surface temperature (PMW LST) serves as a significant source for complementary thermal infrared LST, whereas the orbit gaps frequently result in missing data. Up to now, many studies have proposed methods to fill these gaps in PMW LST. However, most of these methods depend on the assumption that the missing LST is similar to that of adjacent days, yet the natural environment changes may lead to this assumption not being established. To address this, we proposed a comprehensive deep-learning model that incorporates three groups of natural variables, including atmosphere, land environment, and radiation, from both the target and adjacent days. Simultaneously, we employ two advanced microwave scanning radiometer (AMSR) LST-based simulated validations and six in-situ measurements to evaluate the model's gap-filling performance. According to the results, the proposed model achieves root mean squared error (RMSE) of 1.87 K/1.89 K and 1.69 K/1.71 K for the two AMSR LST-based validations during the daytime/nighttime. Compared with the inverse distance weighted method and an advanced deep learning model, the proposed approach improves 0.27–0.5 K (12.6% –22.6%) and 0.14–0.3 K (6.9% –14.9%) during daytime and nighttime, respectively. Furthermore, based on the results of six in-situ measurements, the gap-filled results gain the average RMSE of 3.7 K and 3.21 K during the daytime and nighttime, respectively. In addition, we find that the land environment and radiation conditions have a stronger impact during the daytime, while atmospheric conditions are more sensitive at night. These findings present a more scientific and effective gap-filling method, potentially enhancing the accuracy of land thermal environment research.
Page(s): 9682 - 9700
Date of Publication: 26 March 2025

ISSN Information:

Funding Agency:

Author image of Weizhen Ji
State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Weizhen Ji received the B.S. degree in geographic information system from the School of Municipal and Geomatics Engineering, Hunan City University, Yiyang, China, in 2018, the M.S. degree in cartography and geography information system from the School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, China, in 2021. He is currently working toward the Ph.D. degree with the...Show More
Weizhen Ji received the B.S. degree in geographic information system from the School of Municipal and Geomatics Engineering, Hunan City University, Yiyang, China, in 2018, the M.S. degree in cartography and geography information system from the School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, China, in 2021. He is currently working toward the Ph.D. degree with the...View more
Author image of Yunhao Chen
State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Beijing Key Laboratory of Environment Remote Sensing and Digital Cities, Beijing Normal University, Beijing, China
Yunhao Chen received the B.S. and M.S. degrees in resource management from Anhui University of Science and Technology, Huainan, China, in 1994 and 1997, respectively, and the Ph.D. degree in geodetic engineering from the China University of Mining and Technology, Beijing, China, in 1999.
From 2000 to 2001, he was a Postdoctoral Researcher with Beijing Normal University, Beijing, China. Since 2001, he has been with the Facu...Show More
Yunhao Chen received the B.S. and M.S. degrees in resource management from Anhui University of Science and Technology, Huainan, China, in 1994 and 1997, respectively, and the Ph.D. degree in geodetic engineering from the China University of Mining and Technology, Beijing, China, in 1999.
From 2000 to 2001, he was a Postdoctoral Researcher with Beijing Normal University, Beijing, China. Since 2001, he has been with the Facu...View more
Author image of Haiping Xia
Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou, China
Haiping Xia received the B.S. degree in geographic information system from School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China, in 2015, and the Ph.D. degree from the Faculty of Geographical Science, Beijing Normal University, China, in 2021.
She is currently working with the Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou, Chi...Show More
Haiping Xia received the B.S. degree in geographic information system from School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China, in 2015, and the Ph.D. degree from the Faculty of Geographical Science, Beijing Normal University, China, in 2021.
She is currently working with the Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou, Chi...View more
Author image of Han Gao
State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Han Gao received the B.S. degree in remote sensing science and technology from the College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing, China, in 2023. She is currently working toward the M.S. degree in cartography and geographic information system with the State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Bei...Show More
Han Gao received the B.S. degree in remote sensing science and technology from the College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing, China, in 2023. She is currently working toward the M.S. degree in cartography and geographic information system with the State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Bei...View more
Author image of Lei Zhu
School of Resource Environment and Tourism, Capital Normal University, Beijing, China
Lei Zhu received the B.S. degree in geographic information systems from the School of Municipal and Geomatics Engineering, Hunan City University, Yiyang, China, in 2020, and the M.S. degree in cartography and geographic information systems from the School of Civil and Surveying and Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, China, in 2023. He is currently working toward the Ph.D. degree in...Show More
Lei Zhu received the B.S. degree in geographic information systems from the School of Municipal and Geomatics Engineering, Hunan City University, Yiyang, China, in 2020, and the M.S. degree in cartography and geographic information systems from the School of Civil and Surveying and Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, China, in 2023. He is currently working toward the Ph.D. degree in...View more

Author image of Weizhen Ji
State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Weizhen Ji received the B.S. degree in geographic information system from the School of Municipal and Geomatics Engineering, Hunan City University, Yiyang, China, in 2018, the M.S. degree in cartography and geography information system from the School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, China, in 2021. He is currently working toward the Ph.D. degree with the State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China.
His research interests include thermal remote sensing of urban environment and retrieval and spatiotemporal downscaling of land surface temperature.
Weizhen Ji received the B.S. degree in geographic information system from the School of Municipal and Geomatics Engineering, Hunan City University, Yiyang, China, in 2018, the M.S. degree in cartography and geography information system from the School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, China, in 2021. He is currently working toward the Ph.D. degree with the State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China.
His research interests include thermal remote sensing of urban environment and retrieval and spatiotemporal downscaling of land surface temperature.View more
Author image of Yunhao Chen
State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Beijing Key Laboratory of Environment Remote Sensing and Digital Cities, Beijing Normal University, Beijing, China
Yunhao Chen received the B.S. and M.S. degrees in resource management from Anhui University of Science and Technology, Huainan, China, in 1994 and 1997, respectively, and the Ph.D. degree in geodetic engineering from the China University of Mining and Technology, Beijing, China, in 1999.
From 2000 to 2001, he was a Postdoctoral Researcher with Beijing Normal University, Beijing, China. Since 2001, he has been with the Faculty of Geographical Science, Beijing Normal University, where he is currently a Professor with the State Key Laboratory of Remote Sensing Science. His research interests include thermal remote sensing of urban environment and applications of remote sensing in ecology.
Yunhao Chen received the B.S. and M.S. degrees in resource management from Anhui University of Science and Technology, Huainan, China, in 1994 and 1997, respectively, and the Ph.D. degree in geodetic engineering from the China University of Mining and Technology, Beijing, China, in 1999.
From 2000 to 2001, he was a Postdoctoral Researcher with Beijing Normal University, Beijing, China. Since 2001, he has been with the Faculty of Geographical Science, Beijing Normal University, where he is currently a Professor with the State Key Laboratory of Remote Sensing Science. His research interests include thermal remote sensing of urban environment and applications of remote sensing in ecology.View more
Author image of Haiping Xia
Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou, China
Haiping Xia received the B.S. degree in geographic information system from School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China, in 2015, and the Ph.D. degree from the Faculty of Geographical Science, Beijing Normal University, China, in 2021.
She is currently working with the Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou, China. Her research interests include thermal sharpening and analysis of urban thermal environment.
Haiping Xia received the B.S. degree in geographic information system from School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China, in 2015, and the Ph.D. degree from the Faculty of Geographical Science, Beijing Normal University, China, in 2021.
She is currently working with the Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou, China. Her research interests include thermal sharpening and analysis of urban thermal environment.View more
Author image of Han Gao
State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Han Gao received the B.S. degree in remote sensing science and technology from the College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing, China, in 2023. She is currently working toward the M.S. degree in cartography and geographic information system with the State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing.
Her research interests include remote sensing of urban environment and spatiotemporal downscaling of land surface temperature.
Han Gao received the B.S. degree in remote sensing science and technology from the College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing, China, in 2023. She is currently working toward the M.S. degree in cartography and geographic information system with the State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing.
Her research interests include remote sensing of urban environment and spatiotemporal downscaling of land surface temperature.View more
Author image of Lei Zhu
School of Resource Environment and Tourism, Capital Normal University, Beijing, China
Lei Zhu received the B.S. degree in geographic information systems from the School of Municipal and Geomatics Engineering, Hunan City University, Yiyang, China, in 2020, and the M.S. degree in cartography and geographic information systems from the School of Civil and Surveying and Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, China, in 2023. He is currently working toward the Ph.D. degree in cartography and geographic information systems with the Key Laboratory of 3-D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing, China.
His research interests include deep learning-based geographical parameter mapping.
Lei Zhu received the B.S. degree in geographic information systems from the School of Municipal and Geomatics Engineering, Hunan City University, Yiyang, China, in 2020, and the M.S. degree in cartography and geographic information systems from the School of Civil and Surveying and Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, China, in 2023. He is currently working toward the Ph.D. degree in cartography and geographic information systems with the Key Laboratory of 3-D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing, China.
His research interests include deep learning-based geographical parameter mapping.View more

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