Journal of Jilin University(Earth Science Edition) ›› 2021, Vol. 51 ›› Issue (4): 1284-1294.doi: 10.13278/j.cnki.jjuese.20200151
Wang Boshuai, Pu Dongchuan, Li Tingting, Niu Xuefeng
CLC Number:
| [1] 肖金成,刘保奎.改革开放40年中国城镇化回顾与展望[J].宏观经济研究,2018(12):18-29. Xiao Jincheng, Liu Baokui. Review and Prospect of China's Urbanization in the Past 40 Years of Reform and Opening-Up[J]. Macroeconomic Research, 2018(12):18-29. [2] 尹荣尧,孙翔.中国快速城市化的资源保障隐忧、生态困境与对策[J].现代经济探讨,2014(2):63-65,87. Yin Rongyao, Sun Xiang. Resource Security Concerns, Ecological Dilemma and Countermeasures for China's Rapid Urbanization[J]. Discussion on Modern Economy, 2014(2):63-65,87. [3] Foley J A,Defries R, Asner G P, et al. Global Consequences of Land Use[J]. Science, 2005, 309:570-574. [4] 李德仁,张过,沈欣,等.珞珈一号01星夜光遥感设计与处理[J].遥感学报,2019,23(6):1011-1022. Li Deren, Zhang Guo, Shen Xin, et al.Design and Processing of Luojia 101 Night-Light Remote Sensing[J]. Journal of Remote Sensing, 209, 23(6):1011-1022. [5] Li D, Li X. An Overview on Data Mining of Nighttime Light Remote Sensing[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44:591-601. [6] Li X, Xu H, Chen X, et al. Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China[J]. Remote Sensing, 2013, 5:3057-3081. [7] Yu B, Shu S, Liu H, et al. Object-Based Spatial Cluster Analysis of Urban Landscape Pattern Using Nighttime Light Satellite Images:A Case Study of China[J]. Int J Geogr Inf Sci, 2014, 28:2328-2355. [8] Li X, Zhou Y Y, Cao C Y. Remote Sensing of Night-Time Light[J]. Int J Remote Sensing, 2017, 38:5855-5859. [9] Jing W, Yang Y, Yue X, et al. Mapping Urban Areas with Integration of DMSP/OLS Nighttime Light and MODIS Data Using Machine Learning Techniques[J]. Remote Sensing, 2015, 7:12419-12439. [10] 何春阳,李景刚,陈晋,等.基于夜间灯光数据的环渤海地区城市化过程[J].地理学报,2005,2(3):409-417. He Chunyang, Li Jinggang, Chen Jin, et al. Urbanization Prosess of Bohai Rim Region Based on Night Light Data[J]. Journal of Geography, 2005, 2(3):409-417. [11] Imoffm M, Lawerence W T, Stutzer D C. A Technique for Using Composite DMSP/OLS "City Light" Satellite Data to Map Urban Area[J]. Remote Sensing of Environment, 1997, 61(3):361-370. [12] Zhou Y, Smith S, Elvidge C, et al. Cluster-Based Method to Map Urban Area from DMSP/OLS Nightlight[J]. Remote Sensing of Environment, 2014, 147:173-185. [13] 陈佐旗. 基于多源夜间灯光遥感影像的多尺度城市空间形态结构分析[D].上海:华东师范大学,2017. Chen Zuoqi. Spatial Morphological Structure Analysis of Multi-Scale Cities Based on Remote Sensing Image of Multi-Source Night Lights[D]. Shanghai:East China Normal University, 2017. [14] 王博. 基于NPP-VIIRS夜间灯光遥感影像的杭州城市结构发展变化分析[D].杭州:浙江大学,2019. Wang Bo. Analysis of Urban Structure Development and Change in Hangzhou Based on NPP-VIIRS Night Light Remote Sensing Image[D]. Hangzhou:Zhejiang University, 2019. [15] 刘沁萍,杨永春,付冬暇,等.基于DMSP_OLS灯光数据的1992~2010年中国城市空间扩张研究[J].地理科学,2014,34(2):129-136. Liu Qinping, Yang Yongchun, Fu Dongxia, et al. Urban Spatial Expansion in China from 1992 to 2010 Based on DMSP_OLS Light Data[J]. Geoscience, 2014, 34(2):129-136. [16] 长春市统计局. 2018年长春市国民经济和社会发展统计公报[N]. 长春日报,2019-05-30(6). Changchun Municipal Bureau of Statistics. 2018 Statistical Bulletin on Changchun's National Economic and Social Development[N]. Changchun Daily, 2019-05-30(6). [17] 徐涵秋,唐菲.新一代Landsat系列卫星:Landsat 8遥感影像新增特征及其生态环境意义[J].生态学报,2013,33(11):3249-3257. Xu Hanqiu, Tang Fei. New Generation of Landsat Series Satellites:New Features of Landsat 8 Remote Sensing Image and Its Ecological Environment Significance[J]. Journal of Ecology, 2013, 33(11):3249-3257. [18] Lu D S, Tian H Q, Zhou G M, et al. Regional Mapping of Human Settlements in Southeastern China with Multisensor Remotely Sensed Data[J]. Remote Sensing of Environment, 2008, 112:3668-3679. [19] 唐敏. 基于对数变换的NPP-VIIRS夜间灯光遥感影像在城市建成区提取中的应用[D].上海:华东师范大学,2017. Tang Min. Application of NPP-VIIRS Night Light Remote Sensing Image Based on Logarithmic Transformation in Urban Built-Up Area Extraction[D]. Shanghai:East China Normal University, 2017. [20] Zhang Q, Schaaf C, Seto K C. The Vegetation Adjusted NTL Urban Index:A New Approach to Reduce Saturation and Increase Variation in Nighttime Luminosity[J]. Remote Sensing of Environment, 2013, 129:32-41. [21] 李二珠. 半监督支持向量机高光谱遥感影像分类[D].徐州:中国矿业大学,2014. Li Erzhu. Semi-Supervised Hyperspectral Remote Sensing Image Classification by Support Vector Machines[D]. Xuzhou:China University of Mining and Technology, 2014. [22] 王明常,朱春宇,陈学业,等.基于FPN Res-Unet的高分辨率遥感影像建筑物变化检测[J].吉林大学学报(地球科学版),2021,51(1):296-306. Wang Mingchang, Zhu Chunyu, Chen Xueye, et al. Building Change Detection High Resolution Remote Sensing Images Based on FPN Res-Unet[J]. Journal of Jilin University (Earth Science Edition), 2021, 51(1):296-306. [23] Li Xi, Zhao Lixian, Li Deren. Mapping Urban Extent Using Luojia 1-01 Nighttime Light Imagery[J]. Sensors, 2018, 18(11). doi.org/10.3390/s18113665. [24] 张华. 遥感数据可靠性分类方法研究[D].徐州:中国矿业大学,2012. Zhang Hua. Research on Reliability Classification Method of Remote Sensing Data[D]. Xuzhou:China University of Mining and Technology, 2012. |
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