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Evaluation of Qimingxing-1 Nighttime Light Image source Remote Sensing Data[J]. Remote Sensing,
[J]. Geomatics and Information Science of Wuhan 2020, 12(12): 1910.
University, 2023, 48(8):1273-1285. [16] VERNON HENDERSON J, STOREYGARD A,
[6] CHEN J Q, WEI H, LI N, et al. Exploring the WEIL D N. Measuring Economic Growth from Outer
Spatial-Temporal Dynamics of the Yangtze River Space[J]. The American Economic Review, 2012,
Delta Urban Agglomeration Based on Night-Time 102(2): 994-1028.
Light Remote Sensing Technology[J]. IEEE Jour‑ [17] JIANG S N,WEI G E,ZHANG Z K,et al. Detecting
nal of Selected Topics in Applied Earth Observa‑ the Dynamics of Urban Growth in Africa Using
tions and Remote Sensing, 2020, 13: 5369-5383. DMSP/OLS Nighttime Light Data [J]. Land,
[7] BERGANTINO A S, DI LIDDO G, PORCELLI 2021, 10(1): 13.
F. Regression-Based Measure of Urban Sprawl for [18] LI X, GE L L, CHEN X L. Detecting Zimbabwe’s
Italian Municipalities Using DMSP-OLS Night- Decadal Economic Decline Using Nighttime Light
Time Light Images and Economic Data[J]. Applied Imagery[J]. Remote Sensing, 2013, 5(9): 4551-
Economics, 2020, 52(38): 4213-4222. 4570.
[8] HE X, ZHANG Z M, YANG Z J. Extraction of Ur‑ [19] 张悦, 李众, 曲春红 . 非洲农业现代化发展: 现状、
ban Built-up Area Based on the Fusion of Night- 挑 战 与 机 遇[J]. 中 国 食 物 与 营 养 , 2021, 27(6):
Time Light Data and Point of Interest Data[J]. Royal 17-22.
Society Open Science, 2021, 8(8): 210838. ZHANG Yue,LI Zhong,QU Chunhong. Agricultural
[9] PAN W B, FU H M, ZHENG P. Regional Pover‑ Modernization in Africa: Status Quo, Challenges and
ty and Inequality in the Xiamen-Zhangzhou-Quan‑ Opportunities[J]. Food and Nutrition in China,
zhou City Cluster in China Based on NPP/VIIRS 2021, 27(6): 17-22.
Night-Time Light Imagery [J]. Sustainability, [20] GIGLIO L, DESCLOITRES J, JUSTICE C O, et
2020, 12(6): 2547. al. An Enhanced Contextual Fire Detection Algo‑
[10] LIANG H D, GUO Z Y, WU J P, et al. GDP Spa‑ rithm for MODIS[J]. Remote Sensing of Environ‑
tialization in Ningbo City Based on NPP/VIIRS ment, 2003, 87(2-3): 273-282.
Night-Time Light and Auxiliary Data Using Ran‑ [21] SCHROEDER W, OLIVA P, GIGLIO L, et al.
dom Forest Regression[J]. Advances in Space Re‑ The New VIIRS 375 m Active Fire Detection Data
search, 2020, 65(1): 481-493. Product: Algorithm Description and Initial Assess‑
[11] IVAN K, HOLOBÂCĂ I H, BENEDEK J, et al. ment[J]. Remote Sensing of Environment, 2014,
Potential of Night-Time Lights to Measure Regional 143: 85-96.
Inequality[J]. Remote Sensing, 2020, 12(1): 33. [22] ELVIDGE C,ZHIZHIN M,HSU F C,et al. VIIRS
[12] 李熙, 巩钰, 邵振峰, 等 . 夜间灯光遥感视角下的 Nightfire: Satellite Pyrometry at Night[J]. Remote
中国对中亚地区援助效果评估[J]. 武汉大学学报 Sensing, 2013, 5(9): 4423-4449.
(信息科学版), 2023, 48(12): 1914-1922. [23] ROMÁN M O, WANG Z S, SUN Q S, et al.
LI Xi, GONG Yu, SHAO Zhenfeng, et al. Evalua‑ NASA’s Black Marble Nighttime Lights Product
tion of China’s Aid to Central Asia from the Perspec‑ Suite[J]. Remote Sensing of Environment, 2018,
tive of Night-Time Light Remote Sensing[J]. Geo‑ 210: 113-143.
matics and Information Science of Wuhan Universi‑ [24] LI X, SHANG X Y, ZHANG Q L, et al. Using
ty, 2023, 48(12): 1914-1922. Radiant Intensity to Characterize the Anisotropy of
[13] STATHAKIS D, BALTAS P. Seasonal Popula‑ Satellite-Derived City Light at Night[J]. Remote
tion Estimates Based on Night-Time Lights[J]. Sensing of Environment, 2022, 271: 112920.
Computers, Environment and Urban Systems, [25] LI X, MA R, ZHANG Q, et al. Anisotropic Charac‑
2018, 68: 133-141. teristic of Artificial Light at Night-Systematic Inves‑
[14] SONG J C, TONG X Y, WANG L Z, et al. Moni‑ tigation with VIIRS DNB Multi-temporal Observa‑
toring Finer-Scale Population Density in Urban tions[J]. Remote Sensing of Environment, 2019,
Functional Zones: A Remote Sensing Data Fusion 233: 111357.
Approach[J]. Landscape and Urban Planning, [26] JUN C, BAN Y F, LI S N. Open Access to Earth
2019, 190: 103580. Land-Cover Map[J]. Nature, 2014, 514: 434.
[15] HE M, XU Y M, LI N. Population Spatialization in [27] BELGIU M, DRĂGUŢ L. Random Forest in Re‑
Beijing City Based on Machine Learning and Multi‑ mote Sensing: A Review of Applications and Future

