Research on Inversion and Correction Method of Urban Light Environment Based on Cooperative Observation

With the continuously growing city size and the increasingly complex and changeable light environment in the city, remote sensing and ground-measured technologies have certain limitations in the research of urban night light environment. The ground-measured data are accurate but low in efficiency an...
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Autor*in:	Baogang Zhang [verfasserIn] Yiwei Li [verfasserIn] Ming Liu [verfasserIn] Yuchuan Liu [verfasserIn] Tong Luo [verfasserIn] Qingyuan Liu [verfasserIn] Lie Feng [verfasserIn] Weili Jiao [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	night light environment inversion remote sensing observation ground-measurement

Übergeordnetes Werk:	In: Remote Sensing - MDPI AG, 2009, 14(2022), 12, p 2888
Übergeordnetes Werk:	volume:14 ; year:2022 ; number:12, p 2888

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/rs14122888

Katalog-ID:	DOAJ044128711

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520			\|a With the continuously growing city size and the increasingly complex and changeable light environment in the city, remote sensing and ground-measured technologies have certain limitations in the research of urban night light environment. The ground-measured data are accurate but low in efficiency and small in scale, while the night-light remote sensing data have the characteristics of high accuracy and large coverage. In this paper, high-resolution night-light remote sensing data and high-accuracy ground-measured data were used to establish an urban ground light environment inversion method with the advantages of remote sensing and ground-measured data in a “space-ground collaboration” approach. A ground database is constructed in GIS based on 26,000 ground measurement data of 4 blocks, 3 spatial perspectives, and 3 light environment parameters. Based on the comparison of the numerical relationship between the measured data of each light environment parameter and each window, the horizontal window is selected as the target window for the ground night light environment inversion research. The urban night light environment inversion method based on the correlation between telemetry and ground- measurement is used to construct and compare the correlation between Luojia night light radiance data and 9 sets of measured data of different ground windows and different light environment parameters. The illuminance measured data of horizontal window and Luojia radiance data, both of which are highly correlated, are selected for regression analysis. The mathematical inversion model of ground illuminance is constructed based on the cubic polynomial model with the lowest RMSE among the six regression models. The inversion result not only has photometric calibration, but also is superior to the original data in terms of population data relevance and accuracy.
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spelling	10.3390/rs14122888 doi (DE-627)DOAJ044128711 (DE-599)DOAJda225d2a15424edcb8ae9a862f3263d0 DE-627 ger DE-627 rakwb eng Baogang Zhang verfasserin aut Research on Inversion and Correction Method of Urban Light Environment Based on Cooperative Observation 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the continuously growing city size and the increasingly complex and changeable light environment in the city, remote sensing and ground-measured technologies have certain limitations in the research of urban night light environment. The ground-measured data are accurate but low in efficiency and small in scale, while the night-light remote sensing data have the characteristics of high accuracy and large coverage. In this paper, high-resolution night-light remote sensing data and high-accuracy ground-measured data were used to establish an urban ground light environment inversion method with the advantages of remote sensing and ground-measured data in a “space-ground collaboration” approach. A ground database is constructed in GIS based on 26,000 ground measurement data of 4 blocks, 3 spatial perspectives, and 3 light environment parameters. Based on the comparison of the numerical relationship between the measured data of each light environment parameter and each window, the horizontal window is selected as the target window for the ground night light environment inversion research. The urban night light environment inversion method based on the correlation between telemetry and ground- measurement is used to construct and compare the correlation between Luojia night light radiance data and 9 sets of measured data of different ground windows and different light environment parameters. The illuminance measured data of horizontal window and Luojia radiance data, both of which are highly correlated, are selected for regression analysis. The mathematical inversion model of ground illuminance is constructed based on the cubic polynomial model with the lowest RMSE among the six regression models. The inversion result not only has photometric calibration, but also is superior to the original data in terms of population data relevance and accuracy. night light environment inversion remote sensing observation ground-measurement Science Q Yiwei Li verfasserin aut Ming Liu verfasserin aut Yuchuan Liu verfasserin aut Tong Luo verfasserin aut Qingyuan Liu verfasserin aut Lie Feng verfasserin aut Weili Jiao verfasserin aut In Remote Sensing MDPI AG, 2009 14(2022), 12, p 2888 (DE-627)608937916 (DE-600)2513863-7 20724292 nnns volume:14 year:2022 number:12, p 2888 https://doi.org/10.3390/rs14122888 kostenfrei https://doaj.org/article/da225d2a15424edcb8ae9a862f3263d0 kostenfrei https://www.mdpi.com/2072-4292/14/12/2888 kostenfrei https://doaj.org/toc/2072-4292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 14 2022 12, p 2888
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allfieldsSound	10.3390/rs14122888 doi (DE-627)DOAJ044128711 (DE-599)DOAJda225d2a15424edcb8ae9a862f3263d0 DE-627 ger DE-627 rakwb eng Baogang Zhang verfasserin aut Research on Inversion and Correction Method of Urban Light Environment Based on Cooperative Observation 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the continuously growing city size and the increasingly complex and changeable light environment in the city, remote sensing and ground-measured technologies have certain limitations in the research of urban night light environment. The ground-measured data are accurate but low in efficiency and small in scale, while the night-light remote sensing data have the characteristics of high accuracy and large coverage. In this paper, high-resolution night-light remote sensing data and high-accuracy ground-measured data were used to establish an urban ground light environment inversion method with the advantages of remote sensing and ground-measured data in a “space-ground collaboration” approach. A ground database is constructed in GIS based on 26,000 ground measurement data of 4 blocks, 3 spatial perspectives, and 3 light environment parameters. Based on the comparison of the numerical relationship between the measured data of each light environment parameter and each window, the horizontal window is selected as the target window for the ground night light environment inversion research. The urban night light environment inversion method based on the correlation between telemetry and ground- measurement is used to construct and compare the correlation between Luojia night light radiance data and 9 sets of measured data of different ground windows and different light environment parameters. The illuminance measured data of horizontal window and Luojia radiance data, both of which are highly correlated, are selected for regression analysis. The mathematical inversion model of ground illuminance is constructed based on the cubic polynomial model with the lowest RMSE among the six regression models. The inversion result not only has photometric calibration, but also is superior to the original data in terms of population data relevance and accuracy. night light environment inversion remote sensing observation ground-measurement Science Q Yiwei Li verfasserin aut Ming Liu verfasserin aut Yuchuan Liu verfasserin aut Tong Luo verfasserin aut Qingyuan Liu verfasserin aut Lie Feng verfasserin aut Weili Jiao verfasserin aut In Remote Sensing MDPI AG, 2009 14(2022), 12, p 2888 (DE-627)608937916 (DE-600)2513863-7 20724292 nnns volume:14 year:2022 number:12, p 2888 https://doi.org/10.3390/rs14122888 kostenfrei https://doaj.org/article/da225d2a15424edcb8ae9a862f3263d0 kostenfrei https://www.mdpi.com/2072-4292/14/12/2888 kostenfrei https://doaj.org/toc/2072-4292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 14 2022 12, p 2888
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author	Baogang Zhang
spellingShingle	Baogang Zhang misc night light environment inversion misc remote sensing observation misc ground-measurement misc Science misc Q Research on Inversion and Correction Method of Urban Light Environment Based on Cooperative Observation
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topic_title	Research on Inversion and Correction Method of Urban Light Environment Based on Cooperative Observation night light environment inversion remote sensing observation ground-measurement
topic	misc night light environment inversion misc remote sensing observation misc ground-measurement misc Science misc Q
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title	Research on Inversion and Correction Method of Urban Light Environment Based on Cooperative Observation
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author_browse	Baogang Zhang Yiwei Li Ming Liu Yuchuan Liu Tong Luo Qingyuan Liu Lie Feng Weili Jiao
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title_sort	research on inversion and correction method of urban light environment based on cooperative observation
title_auth	Research on Inversion and Correction Method of Urban Light Environment Based on Cooperative Observation
abstract	With the continuously growing city size and the increasingly complex and changeable light environment in the city, remote sensing and ground-measured technologies have certain limitations in the research of urban night light environment. The ground-measured data are accurate but low in efficiency and small in scale, while the night-light remote sensing data have the characteristics of high accuracy and large coverage. In this paper, high-resolution night-light remote sensing data and high-accuracy ground-measured data were used to establish an urban ground light environment inversion method with the advantages of remote sensing and ground-measured data in a “space-ground collaboration” approach. A ground database is constructed in GIS based on 26,000 ground measurement data of 4 blocks, 3 spatial perspectives, and 3 light environment parameters. Based on the comparison of the numerical relationship between the measured data of each light environment parameter and each window, the horizontal window is selected as the target window for the ground night light environment inversion research. The urban night light environment inversion method based on the correlation between telemetry and ground- measurement is used to construct and compare the correlation between Luojia night light radiance data and 9 sets of measured data of different ground windows and different light environment parameters. The illuminance measured data of horizontal window and Luojia radiance data, both of which are highly correlated, are selected for regression analysis. The mathematical inversion model of ground illuminance is constructed based on the cubic polynomial model with the lowest RMSE among the six regression models. The inversion result not only has photometric calibration, but also is superior to the original data in terms of population data relevance and accuracy.
abstractGer	With the continuously growing city size and the increasingly complex and changeable light environment in the city, remote sensing and ground-measured technologies have certain limitations in the research of urban night light environment. The ground-measured data are accurate but low in efficiency and small in scale, while the night-light remote sensing data have the characteristics of high accuracy and large coverage. In this paper, high-resolution night-light remote sensing data and high-accuracy ground-measured data were used to establish an urban ground light environment inversion method with the advantages of remote sensing and ground-measured data in a “space-ground collaboration” approach. A ground database is constructed in GIS based on 26,000 ground measurement data of 4 blocks, 3 spatial perspectives, and 3 light environment parameters. Based on the comparison of the numerical relationship between the measured data of each light environment parameter and each window, the horizontal window is selected as the target window for the ground night light environment inversion research. The urban night light environment inversion method based on the correlation between telemetry and ground- measurement is used to construct and compare the correlation between Luojia night light radiance data and 9 sets of measured data of different ground windows and different light environment parameters. The illuminance measured data of horizontal window and Luojia radiance data, both of which are highly correlated, are selected for regression analysis. The mathematical inversion model of ground illuminance is constructed based on the cubic polynomial model with the lowest RMSE among the six regression models. The inversion result not only has photometric calibration, but also is superior to the original data in terms of population data relevance and accuracy.
abstract_unstemmed	With the continuously growing city size and the increasingly complex and changeable light environment in the city, remote sensing and ground-measured technologies have certain limitations in the research of urban night light environment. The ground-measured data are accurate but low in efficiency and small in scale, while the night-light remote sensing data have the characteristics of high accuracy and large coverage. In this paper, high-resolution night-light remote sensing data and high-accuracy ground-measured data were used to establish an urban ground light environment inversion method with the advantages of remote sensing and ground-measured data in a “space-ground collaboration” approach. A ground database is constructed in GIS based on 26,000 ground measurement data of 4 blocks, 3 spatial perspectives, and 3 light environment parameters. Based on the comparison of the numerical relationship between the measured data of each light environment parameter and each window, the horizontal window is selected as the target window for the ground night light environment inversion research. The urban night light environment inversion method based on the correlation between telemetry and ground- measurement is used to construct and compare the correlation between Luojia night light radiance data and 9 sets of measured data of different ground windows and different light environment parameters. The illuminance measured data of horizontal window and Luojia radiance data, both of which are highly correlated, are selected for regression analysis. The mathematical inversion model of ground illuminance is constructed based on the cubic polynomial model with the lowest RMSE among the six regression models. The inversion result not only has photometric calibration, but also is superior to the original data in terms of population data relevance and accuracy.
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title_short	Research on Inversion and Correction Method of Urban Light Environment Based on Cooperative Observation
url	https://doi.org/10.3390/rs14122888 https://doaj.org/article/da225d2a15424edcb8ae9a862f3263d0 https://www.mdpi.com/2072-4292/14/12/2888 https://doaj.org/toc/2072-4292
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author2	Yiwei Li Ming Liu Yuchuan Liu Tong Luo Qingyuan Liu Lie Feng Weili Jiao
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doi_str	10.3390/rs14122888
up_date	2024-07-03T21:22:49.887Z
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The urban night light environment inversion method based on the correlation between telemetry and ground- measurement is used to construct and compare the correlation between Luojia night light radiance data and 9 sets of measured data of different ground windows and different light environment parameters. The illuminance measured data of horizontal window and Luojia radiance data, both of which are highly correlated, are selected for regression analysis. The mathematical inversion model of ground illuminance is constructed based on the cubic polynomial model with the lowest RMSE among the six regression models. 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Research on Inversion and Correction Method of Urban Light Environment Based on Cooperative Observation

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