Extraction of large-scale urban area information in China using DMSP/OLS nighttime light data

doi:10.6046/gtzyyg.2013.03.26

Abstract
References
Related Articles
Metrics

Download: PDF(2927 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Nighttime light data have been widely used for mapping urban land. Previous application of the TM-assisted thresholding method mainly determined threshold of the nighttime light data in each city, which is not suitable for the study at a large scale due to its low processing efficiency and high data acquisition cost. In this paper, based on the TM-assisted thresholding method, the authors put forward the partition idea to extract the urban area using the DMSP/OLS nighttime light data. China was divided into 7 major regions based on economic partition and then TM-assisted thresholding method was employed to extract urban land areas. Finally, applying real urban land use pixels judgment, the authors obtained China’s urban land information of the years 1992, 1995 and 2000. A comparison with the previous method shows that the performance of the method based on partition idea is more efficient and can ensure overall accuracy.

Keywords logarithmic polar coordinate transformation phase correlation image registration extraction of earthquake damage information

TP 79

Issue Date: 03 July 2013

	Service

	E-mail this article
	E-mail Alert
	RSS
	Articles by authors

	YANG Dehe
	CHEN Yijin
	YANG Xi
	LYU Jingguo
	ZHANG Zixin
	ZHANG Shuai

Cite this article:

YANG Dehe,CHEN Yijin,YANG Xi, et al. Extraction of large-scale urban area information in China using DMSP/OLS nighttime light data[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(3): 159-164.

URL:

https://www.gtzyyg.com/EN/10.6046/gtzyyg.2013.03.26 OR https://www.gtzyyg.com/EN/Y2013/V25/I3/159

[1] Foley J A,DeFries R,Asner G P,et al.Global consequences of land use[J].Science,2005,309(5734):570-574.

[2] Grimm N B,Faeth S H,Golubiewski N E,et al.Global change and theecology of cities[J].Science,2008,319(5864):756-760.

[3] 方创琳.改革开放30年来中国的城市化与城镇发展[J].经济地理,2009,29(1):19-25. Fang C L.The urbanization and urban development in China after the reform and opening-up[J].Economic Geography,2009,29(1):19-25.

[4] Cao X,Chen J,Imura H,et al.A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data[J].Remote Sensing of Environment,2009,113(10):2205-2209.

[5] Croft T A.Night time images of the earth from space[J].Scientific American,1978,239(1):86-89.

[6] Imhoff M L,Lawrence W T,Stutzer D C,et al.A technique for using composite DMSP/OLS city lights satellite data to map urban area[J].Remote Sensing of Environment,1997,61(3):361-370.

[7] Milesi C,Elvidge C D,Nemani R R,et al.Assessing the impact of urban land development on net primary productivity in the southeastern United States[J].Remote Sensing of Environment,2003,86(3):401-410.

[8] Henderson M,Yeh E T,Gong P,et al.Validation of urban boundaries derived from global nighttime satellite imagery[J].International Journal of Remote Sensing,2003,24(3):595-609.

[9] 陈晋,卓莉,史培军,等.基于DMSP/OLS数据的中国城市化过程研究——反映区域城市化水平的灯光指数的构建[J].遥感学报,2003,7(3):168-175. Chen J,Zhuo L,Shi P J,et al.The study on urbanization process in China based on DMSP/OLS data:Development of a light index for urbanization level estimation[J].Journal of Remote Sensing,2003,7(3):168-175.

[10] He C Y,Shi P J,Li J G,et al.Restoring urbanization process in China in the 1990s by using non-radiance-calibrated DMSP/OLS nighttime light imagery and statistical data[J].Chinese Science Bulletin,2006,51(13):1614-1620.

[11] 杨洋,何春阳,赵媛媛,等.利用DMSP/OLS稳定夜间灯光数据提取城镇用地信息的分层阈值法研究[J].中国图象图形报,2011,16(4):666-673. Yang Y,He C Y,Zhao Y Y,et al.Research on the layered threshold method for extracting urban land using the DMSP/OLS stable nighttime light data[J].Journal of Image and Graphics,2011,16(4):666-673.

[12] Wang L,Gong P,Ying Q,et al.Settlement extraction in the North China Plain using Landsat and Beijing-1 multispectral data with an improved watershed segmentation algorithm[J].International Journal of Remote Sening,2010,31(6):1411-1426.

[13] Liu J Y,Liu M L,Tian H Q,et al.Spatial and temporal patterns of China’s cropland during 1990-2000:An analysis based on Landsat TM data[J].Remote Sensing of Environment,2005,98(4):442-456.

[14] 王雷,李丛丛,应清,等.中国1990~2010年城市扩张卫星遥感制图[J].科学通报,2012,57(16):1388-1399. Wang L,Li C C,Ying Q,et al.China’s urban expansion from 1990 to 2010 determined with satellite remote sensing[J].Chinese Science Bulletin,2012,57(16):1388-1399.

[15] 胡序威.论中国经济区的类型与组织[J].地理学报,1993,48(3):193-203. Hu X W.On the typology and organization of economic regions in China[J].Acta Geographica Sinica,1993,48(3):193-203.

[16] 陆大壮.中国行政区、经济区发展的回顾与展望[J].中国人民大学学报,1994(6):1-6. Lu D Z.The retrospect and prospect development of the administrative and economic regions in China[J].Journal of Renmin University of China,1994(6):1-6.

[17] Elvidge C D,Baugh K E,Dietz J B,et al.Radiance calibration of DMSP/OLS low-light imaging data of human settlements[J].Remote Sensing of Environment,1999,68(1):77-88.

[18] 卓莉,李强,史培军,等.基于夜间灯光数据的中国城市用地扩展类型[J].地理学报,2006,61(2):169-178. Zhuo L,Li Q,Shi P J,et al.Identification and characteristics analysis of urban land expansion types in China in the 1990s using DMSP/OLS data[J].Acta Geographica Sinica,2006,61(2):169-178.

[1]	ZANG Liri, YANG Shuwen, SHEN Shunfa, XUE Qing, QIN Xiaowei. A registration algorithm of images with special textures coupling a watershed with mathematical morphology[J]. Remote Sensing for Natural Resources, 2022, 34(1): 76-84.
[2]	ZHANG Mengsheng, YANG Shuwen, JIA Xin, ZANG Liri. An automatic registration algorithm for remote sensing images based on grid index[J]. Remote Sensing for Land & Resources, 2021, 33(1): 123-128.
[3]	Famao YE, Wei LUO, Yanfei SU, Xuqing ZHAO, Hui XIAO, Weidong MIN. Application of convolutional neural network feature to remote sensing image registration[J]. Remote Sensing for Land & Resources, 2019, 31(2): 32-37.
[4]	Li YAN, Xun GONG, Hong XIE. Phase correlation supported feature track- matching algorithm for repeating texture[J]. Remote Sensing for Land & Resources, 2018, 30(1): 1-6.
[5]	PAN Jianping, HAO Jianming, ZHAO Jiping. Improved algorithm based on SURF for image registration[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(1): 110-115.
[6]	LI Fuyu, YE Famao. Summarization of SIFT-based remote sensing image registration techniques[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(2): 14-20.
[7]	SONG Zhili. Automatic approach based on point and curve features for multimodal remote sensing image registration[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(3): 48-54.
[8]	LI Zheng, LI Yongshu, CHU Bin, TANG Min. UAV image registration based on the weighted total-least-squares[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(2): 69-73.
[9]	LI Weifeng, ZHOU Jinqiang, FANG Shenghui. Image registration method based on improved Hausdorff distance[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(2): 93-98.
[10]	ZHANG Yunsheng, ZOU Zhengrong. Automatic registration method for remote sensing images based on improved ORB algorithm[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(3): 20-24.
[11]	YANG Dehe, CHEN Yijin, YANG Xi, LYU Jingguo, ZHANG Zixin, ZHANG Shuai. Automatic registration of multi-source images for extraction of earthquake damage information[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(3): 56-60.
[12]	Gao Feng . AUTOMATIC RELATIVE ORIENTATION OF MULTI-ANGLE REMOTE SENSED IMAGERY CONDUCTED BY GPS[J]. REMOTE SENSING FOR LAND & RESOURCES, 1997, 9(4): 47-53.

Viewed

Full text

Abstract

Cited

Shared

Discussed