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Delineating Spatial Patterns in Human Settlements Using VIIRS Nighttime Light Data: A Watershed-Based Partition Approach
Ma, Ting1,2,3; Yin, Zhan1,2; Zhou, Alicia4
2018-03-01
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume10Issue:3Pages:14
Corresponding AuthorMa, Ting(mting@lreis.ac.cn)
AbstractAs an informative proxy measure for a range of urbanization and socioeconomic variables, satellite-derived nighttime light data have been widely used to investigate diverse anthropogenic activities in human settlements over time and space from the regional to the national scale. With a higher spatial resolution and fewer over-glow and saturation effects, nighttime light data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument with day/night band (DNB), which is on the Suomi National Polar-Orbiting Partnership satellite (Suomi-NPP), may further improve our understanding of spatiotemporal dynamics and socioeconomic activities, particularly at the local scale. Capturing and identifying spatial patterns in human settlements from VIIRS images, however, is still challenging due to the lack of spatially explicit texture characteristics, which are usually crucial for general image classification methods. In this study, we propose a watershed-based partition approach by combining a second order exponential decay model for the spatial delineation of human settlements with VIIRS-derived nighttime light images. Our method spatially partitions the human settlement into five different types of sub-regions: high, medium-high, medium, medium-low and low lighting areas with different degrees of human activity. This is primarily based on the local coverage of locally maximum radiance signals (watershed-based) and the rank and magnitude of the nocturnal radiance signal across the whole region, as well as remotely sensed building density data and social media-derived human activity information. The comparison results for the relationship between sub-regions with various density nighttime brightness levels and human activities, as well as the densities of different types of interest points (POIs), show that our method can distinctly identify various degrees of human activity based on artificial nighttime radiance and ancillary data. Furthermore, the analysis results across 99 cities in 10 urban agglomerations in China reveal inter-regional variations in partition thresholds and human settlement patterns related to the urban size and form. Our partition method and relative results can provide insight into the further application of VIIRS DNB nighttime light data in spatially delineated urbanization processes and socioeconomic activities in human settlements.
Keywordnighttime light Suomi-NPP VIIRS human settlement watershed-based partition second-order exponential decay
DOI10.3390/rs10030465
WOS KeywordMAP URBAN AREA ; SOCIOECONOMIC ACTIVITY ; URBANIZATION DYNAMICS ; SATELLITE IMAGERY ; CITY LIGHTS ; CHINA ; LUMINOSITY ; VEGETATION ; ECOSYSTEM ; MISSION
Indexed BySCI
Language英语
Funding ProjectKey Research Program of Frontier Science, Chinese Academy of Sciences[QYZDY-SSW-DQC007] ; National Natural Science Foundation of China[41771418] ; National Natural Science Foundation of China[41421001] ; National Science and Technology Key Project[2016YFB0502301] ; National Key Basic Research Program of China[2015CB954101]
Funding OrganizationKey Research Program of Frontier Science, Chinese Academy of Sciences ; National Natural Science Foundation of China ; National Science and Technology Key Project ; National Key Basic Research Program of China
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000428280100111
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/54973
Collection中国科学院地理科学与资源研究所
Corresponding AuthorMa, Ting
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
4.Boston Univ, Coll Art & Sci, Dept Math & Stat, Boston, MA 02215 USA
Recommended Citation
GB/T 7714
Ma, Ting,Yin, Zhan,Zhou, Alicia. Delineating Spatial Patterns in Human Settlements Using VIIRS Nighttime Light Data: A Watershed-Based Partition Approach[J]. REMOTE SENSING,2018,10(3):14.
APA Ma, Ting,Yin, Zhan,&Zhou, Alicia.(2018).Delineating Spatial Patterns in Human Settlements Using VIIRS Nighttime Light Data: A Watershed-Based Partition Approach.REMOTE SENSING,10(3),14.
MLA Ma, Ting,et al."Delineating Spatial Patterns in Human Settlements Using VIIRS Nighttime Light Data: A Watershed-Based Partition Approach".REMOTE SENSING 10.3(2018):14.
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