[1] D R Li, X Li. An overview on data mining of nighttime light remote sensing. Acta Geodaetica et Cartographica Sinica, 44, 591-601(2015).
[2] M Yang, S X Wang, Y Zhou et al. Review on applications of DMSP/OLS night-time emissions data. Remote Sensing Technology and Application, 26, 45-51(2011).
[3] Y B Chen, Z H Zheng, Z F Wu et al. Review and prospect of application of nighttime light remote sensing data. Progress in Geography, 38, 205-223(2019).
[4] Y M Zheng, Y R He, X R Wang et al. Application review and prospect of nighttime light remote sensing data. Remote Sensing Information, 35, 1-14(2020).
[5] B L Yu, C X Wang, W K Gong et al. Nighttime light remote sensing and urban studies: Data, methods, applications and prospects. National Remote Sensing Bulletin, 25, 342-364(2021).
[6] N Levin, C C M Kyba, Q L Zhang et al. Remote sensing of night lights: A review and an outlook for the future. Remote Sensing of Environment, 237, 111443(2020).
[7] X Fang. VIIRS day/night band data application overview. Science and Technology Innovation Herald, 8, 42-43(2015).
[8] S S Hu. VIIRS Low-light Channel Data Radiometric Calibration and Application Technology(2019).
[9] M D Jiang, L Chen, Y Q He et al. Nighttime aerosol optical depth retrievals from VIIRS day/night band data. National Remote Sensing Bulletin, 26, 493-504(2022).
[10] Z S Wang, R O Roman, V L Kalb et al. Quantifying uncertainties in nighttime light retrievals from Suomi-NPP and NOAA-20 VIIRS Day/Night Band data. Remote Sensing of Environment, 263, 112557(2021).
[11] J Zhang, J S Reid, S D Miller et al. Strategy for studying nocturnal aerosol optical depth using artificial lights. International journal of remote sensing, 29, 4599-4613(2008).
[12] C Y Cao, J Xiong, S Blonski et al. Suomi NPP VIIRS sensor data record verification, validation, and long-term performance monitoring. Journal of Geophysical Research Atmospheres, 118, 11664-11678(2013).
[13] S Lee, C Y Cao. Soumi NPP VIIRS Day/Night Band stray light characterization and correction using calibration view data. Remote Sensing, 8, 138(2015).
[14] X X Xiong, J Butler, K Chiang et al. VIIRS on-orbit calibration methodology and performance. Journal of Geophysical Research Atmospheres, 119, 5065-5078(2013).
[15] C Y Cao, D F Luccia, X X Xiong et al. Early on-orbit performance of the visible infrared imaging radiometer suite onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. IEEE Transactions on Geoscience and Remote Sensing, 52, 1142-1156(2013).
[16] S Lee, K Chiang, X X Xiong et al. The S-NPP VIIRS day-night band on-orbit calibration/characterization and current state of SDRproducts. Remote Sensing, 6, 12427-12446(2014).
[17] S Mills, E Jacobson, J Jaroń et al. Calibration of the VIIRS Day/Night Band (DNB), 17-21.
[18] S Uprety, C Y Cao, Y L Gu et al. Calibration improvements in S-NPP VIIRS DNB sensor data record using version 2 reprocessing. IEEE Transactions on Geoscience and Remote Sensing, 57, 9602-9611(2019).
[19] G G Guo, W Fan, J L Xue et al. Identification for operating pelagic light-fishing vessels based on NPP/VIIRS low light imaging data. Transactions of the Chinese Society of Agricultural Engineering, 33, 245-251(2017).
[20] J J Li, S Qiu, Y Zhang et al. Performance assessments of VIIRS DNB on-orbit radiometric calibration accuracy and stability on SNPP and NOAA-20. Journal of Infrared and Millimeter Waves, 40, 809-819(2021).
[21] L B Liao, S Weiss, S Mills et al. Suomi NPP VIIRS day-night band on-orbit performance. Journal of Geophysical Research Atmospheres, 118, 12705-12718(2013).
[22] S Qiu, X Shao, C Y Cao et al. Feasibility demonstration for calibrating Suomi-national Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite day/night band using Dome C and greenland under moon light. Journal of Applied Remote Sensing, 10, 016024(2016).
[23] S S Hu, S Ma, W Yan et al. Using two different targets for the calibration of S-NPP VIIRS day night band under lunar illumination, 10255(2016).
[24] S S Hu, S Ma, J Jiang et al. Research progress on radiation calibration and data application of spaceborne low-light imager. Acta Optica Sinica, 41, 9-23(2021).
[25] S Ma, Y X Huang, W Yan et al. Calibration of low-level light sensor using deep convective clouds. Journal of Infrared and Millimeter Waves, 34, 630-640(2015).
[26] S Ma, W Yan, Y X Huang et al. Vicarious calibration of S-NPP/VIIRS day-night band using deep convective clouds. Remote Sensing of Environment, 158, 42-55(2015).
[27] C Y Cao, Y Bai. Quantitative analysis of VIIRS DNB nightlight point source for light power estimation and stability monitoring. Remote Sensing, 6, 11915-11935(2014).
[28] S Ma, W Yan, Y X Huang et al. Calibration method of low light sensor based on bridge lights. Journal of Atmospheric & Oceanic Technology, 33, 1123-1134(2016).
[29] S S Hu, S Ma, W Yan et al. Feasibility of a specialized ground light source for night-time low-light calibration. International Journal of Remote Sensing, 39, 2543-2559(2018).
[30] T Gan, Y L Yuan, W C Zhai et al. Design and test of in-site radiometric calibration reference light source for spaceborne low light level remote sensors. Journal of Applied Optics, 41, 140-144(2020).
[31] W Zhao, J W Tang, W Yan et al. Using modified-6S to simulate the remote sensor signal of moon. Chinese Space Science and Technology, 27, 27-32(2007).
[32] X Z Zeng, L L Tang. Analysis of lunar irradiance model based on the SeaWiFS lunar observations. Journal of University of Chinese Academy of Sciences, 36, 663-670(2019).
[33] L Zhang, P Zhang, X Q Hu et al. Comparison of lunar irradiance models and validation of lunar observation on earth. National Remote Sensing Bulletin, 21, 864-870(2017).
[34] H H Kieffer, T C Stone. The spectral irradiance of the moon. The Astronomical journal, 129, 2887-2901(2005).
[35] H H Kieffer, J M Anderson. Use of the moon for spacecraft calibration over 350 to 2500 nm.
[36] T C Stone, H H Kieffer. Assessment of uncertainty in ROLO lunar irradiance for on-orbit calibration. Proceedings of SPIE -The International Society for Optical Engineering, 5542, 300-310(2004).
[37] S D Miller, R E Turner. A dynamic lunar spectral irradiance data set for NPOESS/VIIRS day/night band nighttime environmental applications. IEEE Transactions on Geoscience and Remote Sensing, 47, 2316-2329(2009).
[38] J Wang, M Zhou, X Xu et al. Development of a nighttime shortwave radiative transfer model for remote sensing of nocturnal aerosols and fires from VIIRS. Remote Sensing of Environment, 241, 111727(2020).
[39] M Min, J Zheng, P Zhang et al. A low-light radiative transfer model for satellite observations of moonlight and earth surface light at night. Journal of Quantitative Spectroscopy and Radiative Transfer, 247, 106954(2020).
[40] R S Johnson, J Zhang, E J Hyer et al. Preliminary investigations toward nighttime aerosol optical depth retrievals from the VIIRS day/night band. Atmospheric Measurement Techniques, 6, 1245-1255(2013).
[41] J Wang, C Aegerter, X G Xu et al. Potential application of VIIRS day/night band for monitoring nighttime surface PM2.5 air quality from space. Atmospheric Environment, 124, 55-63(2016).
[42] W Li, X Q Zheng. A haze monitoring method combined VIIRS images with real-time observation data interpolation in Beijing. Acta Geodaetica et Cartographica Sinica, 44, 123-128(2015).
[43] C L Su, L Su, L F Chen et al. Retrieval of aerosol optical depth using NPP VIIRS data. National Remote Sensing Bulletin, 19, 977-982(2015).
[44] W H Zhang. Research on the Retrieving of High Temporal Resolution Aerosol Optical Properties from Remote Sensing Data over East Asian(2016).
[45] B Y Ge, L K Yang, X F Chen et al. Study on aerosol optical depth retrieval over land from Himawari-8 data based on dark target method. National Remote Sensing Bulletin, 22, 38-50(2018).
[46] L She, H K Zhang, Z Q Li et al. Himawari-8 aerosol optical depth (AOD) retrieval using a deep neural network trained using aeronet observations. Remote Sensing, 12, 4125(2020).
[47] S Y Shi, T H Cheng, X F Gu et al. Multisensor data synergy of Terra-MODIS, Aqua-MODIS, and Suomi NPP-VIIRS for the retrieval of aerosol optical depth and land surface reflectance properties. IEEE Transactions on Geoscience and Remote Sensing, 6, 1-18(2018).
[48] G Wei, Y Q Hou, Y Zha. Analysis of aerosol type changes in Wuhan City under the outbreak of COVID-19 epidemic. Remote Sensing For Natural Resources, 33, 238-245(2021).
[49] L X Wang, H Zhang, Q Xu. VIIRS aerosol optical depth retrieval based on high resolution surface reflectance ratio database. Journal of Geomatics Science and Technology, 38, 295-300(2021).
[50] T M McHardy, J Zhang, J S Reid et al. An improved method for retrieving nighttime aerosol optical thickness from the VIIRS day/night band. Atmospheric Measurement Techniques Discussions, 8, 4773-4783(2015).
[51] J L Zhang, S L Jaker, J S Reid et al. Characterization and application of artificial light sources for nighttime aerosol optical depth retrievals using the Visible Infrared Imager Radiometer Suite Day/Night Band. Atmospheric Measurement Techniques, 12, 3209-3222(2019).
[52] X J Wang, X H Mu, G J Yan. Quantitative analysis of aerosol influence on Suomi-NPP VIIRS nighttime light in China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 3557-3568(2020).
[53] M Zhou, J Wang, X Chen et al. Nighttime smoke aerosol optical depth over U.S. rural areas: First retrieval from VIIRS moonlight observations. Remote Sensing of Environment, 267, 112717(2021).
[54] L J Yang, H Q Xu, Z F Jin. Estimation of ground-level PM2.5 concentrations using MODIS satellite data in Fuzhou, China. National Remote Sensing Bulletin, 22, 64-75(2018).
[55] X P Wang, W B Sun, K N Zheng et al. Estimating hourly PM2.5 concentrations using MODIS 3 km AOD and an improved spatiotemporal model over Beijing-Tianjin-Hebei, China. Atmospheric Environment, 222, 117089(2020).
[56] B Kianian, Y Liu, H H Chang. Imputing satellite-derived aerosol optical depth using a multi-resolution spatial model and random forest for PM2.5 prediction. Remote Sensing, 13, 126(2021).
[57] X H Cui, J F Xie, F Zhang et al. Establishment of PM2.5 forecasting model based on deep learning. Beijing Surveying and Mapping, 22-27(2017).
[58] B Geng, Y B Sun, Q L Zeng et al. Refined spatiotemporal estimation model of PM2.5 based on deep learning method. China Environmental Science, 41, 3502-3510(2021).
[59] L Y Liu, Y J Zhang, Y S Li et al. PM2.5 inversion using remote sensing data in eastern China based on deep learning. Environmental Science, 41, 1513-1519(2020).
[60] J S Wu, F Yao, W F Li et al. VIIRS-based remote sensing estimation of ground-level PM2.5 concentrations in Beijing-Tianjin-Hebei: A spatiotemporal statistical model. Remote Sensing of Environment, 184, 316-328(2016).
[61] H F Jin. Review of PM2.5 monitoring based on remote sensing technology. Geomatics & Spatial Information Technology, 39, 133-136(2016).
[62] J S Wu, X Wang. Research progress of retrieval ground-level PM2.5 concentration based on AOD data. Environmental Science & Technology, 40, 68-76(2017).
[63] X R Zhao, H Q Shi, P L Yang et al. Inversion algorithm of PM2.5 air quality based on nighttime light data from NPP-VIIRS. National Remote Sensing Bulletin, 21, 291-299(2017).
[64] X R Zhao, H Q Shi, H Yu et al. Inversion of nighttime PM2.5 mass concentration in Beijing based on the VIIRS day-night band. Atmosphere, 10, 136(2016).
[65] K Li, C S Liu, P L Jiao. Estimation of nighttime PM2.5 concentration in Shanghai based on NPP/VIIRS day-night band data. Acta Scientiae Circumstantiae, 39, 1913-1922(2019).
[66] D Fu, X Xia, M Duan et al. Mapping nighttime PM2.5 from VIIRS DNB using a linear mixed-effect model. Atmospheric Environment, 178, 214-222(2018).
[67] H J Chen, Y M Xu, Y P Mo et al. Estimating nighttime PM2.5 concentrations in Huai'an based on NPP/VIIRS nighttime light data. Acta Scientiae Circumstantiae, 42, 342-351(2022).
[68] D R Li, G Zhang, X Shen et al. Design and processing night light remote sensing of LJ-1 01 satellite. National Remote Sensing Bulletin, 23, 1011-1022(2019).
[69] L Zhong, X S Liu. Application potential analysis of LJ1-01 new nighttime light data. Bulletin of Surveying and Mapping, 132-137(2019).
[70] G Zhang, Y R Shi, M Z Xu. Evaluation of LJ1-01 nighttime light imagery for estimating monthly PM2.5 concentration: A comparison with NPP-VIIRS nighttime light data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 3618-3632(2020).
[71] C C Li, J T Mao, Q H Liu et al. Research on the air pollution in Beijing and its surroundings with MODIS AOD products. Chinese Journal of Atmospheric Sciences, 27, 869-880(2003).
[72] Z Q Li, H Xu, Y Zhang et al. Remote sensing of haze pollution based on satellite data: Method and system design. Environmental Monitoring in China, 30, 159-165(2014).
[73] Z Q Li, H Xu, Y Zhang et al. Joint use of active and passive remote sensing for monitoring of severe haze pollution in Beijing. National Remote Sensing Bulletin, 17, 919-928(2013).
[74] J M Xiang, S Y Zhu, G X Zhang et al. Progress in haze monitoring by remote sensing technology. Remote Sensing Technology and Application, 34, 12-20(2019).
[75] L F Chen, S S Chen, L J Zhong et al. Statistic method of particulate matter concentration based on the satellite observations combining with ground measurements in PRD. Tropical Geography, 35, 7-12(2015).
[76] W Ge, L F Chen, Y D Si et al. Haze spectral analysis and detection algorithm using satellite remote sensing data. Spectroscopy and Spectral Analysis, 36, 3817-3824(2016).
[77] W Li, Z X Chen, Z Y Xia. Identification of urban haze at night based on nighttime remote sensing. Computer Knowledge and Technology, 17, 91-93(2021).
[78] Y Z Wu, K F Shi, B L Yu et al. Analysis of the impact of urban sprawl on haze pollution based on the NPP-VIIRS nighttime light remote sensing data. Geomatics and Information Science of Wuhan University, 46, 777-789(2021).
[79] S R Liu, K F Shi, Y Z Wu et al. Remotely sensed nighttime lights reveal China's urbanization process restricted by haze pollution. Building and Environment, 206, 10835(2021).
[80] W J Li, X Y Peng, M J Li. Research and test on distinguish daytime fog using geostationary satellite in Zhejiang Province. Meteorological and Environmental Sciences, 40, 95-101(2017).
[81] Y X Bao, Y Shao, X Li. Visibility inversion of a haze process in Beijing by remote sensing based on MODIS satellite observations. Transactions of Atmospheric Sciences, 41, 710-719(2018).
[82] X K Zhou, W Yan, H Bai et al. Detection of heavy fogs and low clouds during nighttime using DMSP-OLS data. Remote Sensing Information, 27, 86-90(2012).
[83] L Xia, K B Mao, Z W Sun et al. Introduction of Suomi NPP VIIRS and its application on cloud detection. Advances in Geosciences, 3, 271-276(2013).
[84] L Xia, K B Mao, Z W Sun et al. Method for detecting cloud at night from VIIRS data based on DNB. Remote Sensing for Land & Resources, 26, 74-79(2014).
[85] C Y Cao, B Zhang, F Xia et al. Exploring VIIRS night light long-term time series with CNN/SI for urban change detection and aerosol monitoring. Remote Sensing, 14, 3126(2022).
