Abstract
As 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.
Highlights
As a human-dominated landscape, human settlements ranging in size from hamlets and villages to towns and cities play a crucial role in environmental and ecological changes [1,2,3]
A reduction in texture information regarding artificial objects in nighttime light images is still a major challenge when delineating the spatial patterns in human settlements using nocturnal luminosity data, even for Visible Infrared Imaging Radiometer Suite (VIIRS) images with markedly enhanced spatial resolutions and less over-glow effects than those of traditional Defense Meteorological Satellite Program (DMSP) images [34]
Based on the local hotspots of lighting signals and the spatial fluctuations in nighttime brightness, we developed a watershed-based partition approach for VIIRS images
Summary
As a human-dominated landscape, human settlements ranging in size from hamlets and villages to towns and cities play a crucial role in environmental and ecological changes [1,2,3]. Based on the statistically significant relationship between nocturnal artificial lighting signals and several urbanization and socioeconomic variables over time and space [7,8], satellite-derived nighttime light data, which were previously provided by the Defense Meteorological Satellite Program (DMSP), have been widely applied when investigating socioeconomic dynamics and mapping urbanization at various spatial and temporal scales [9,10,11,12]. DMSP nighttime light datasets have several considerable drawbacks due to factors such as a relatively coarse spatial resolution, saturated lighting signals due to the limited capability of the six-bit quantization sensors and over-glow effects caused by light diffusion from adjacent areas, which can visibly affect the quantitative measurement of human activities, at a fine scale [14,15]. Most previous studies based on DMSP nighttime light data have generally been limited to regional or sub-regional level surveys of urbanization dynamics and socioeconomic development, even though several efforts have been made to calibrate radiance values and reduce saturation effects in DMSP images [16,17,18]
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