Human Activities Along Southwest Border of China: Findings Based on DMSP/OLS Nighttime Light Data

Due to remarkable socioeconomic development, an increasing number of karst rocky desertification areas have been severely affected by human activities in southern China. Effectively analyzing human activities in karst rocky desertification areas is a critical prerequisite for managing and restoring areas with tremendous negative impacts from desertification. At present, a timely and accurate way of quantifying the spatiotemporal variations of human activities in karst rocky desertification areas is still lacking. In this communication, we attempted to quantify human activities from the corrected NPP-VIIRS nighttime light data from 2012 to 2018 based on statistical analysis. The results show that a significant increase of night lights could be clearly identified during the study period. The total nighttime lights (TL) related to severe karst rocky desertification (S) were particularly concentrated in Guizhou and Yunnan. The nighttime light intensity (LI) related to the S areas in Chongqing were the strongest due to its rapid socioeconomic development. The annual growth rate of nighttime lights (GL) has been slow or even negative in Guangdong because of its various karst rocky desertification restoration programs. This communication could provide an effective approach for quantifying human activities and provide useful information about where prompt attention is required for policy-making on the restoration of the karst rocky desertification areas.

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Filtering the NPP-VIIRS Nighttime Light Data for Improved Detection of Settlements in Africa

Remote Sensing ◽

10.3390/rs11243002 ◽

2019 ◽

Vol 11 (24) ◽

pp. 3002

Author(s):

Xiaotian Yuan ◽

Li Jia ◽

Massimo Menenti ◽

Jie Zhou ◽

Qiting Chen

Keyword(s):

Biomass Burning ◽

Human Activities ◽

Infrared Imaging ◽

Recognition Rate ◽

European Space Agency ◽

Environmental Research ◽

Equatorial Africa ◽

Nighttime Lights ◽

Nighttime Light Data ◽

Nighttime Light

Observing and understanding changes in Africa is a hotspot in global ecological environmental research since the early 1970s. As possible causes of environmental degradation, frequent droughts and human activities attracted wide attention. Remote sensing of nighttime light provides an effective way to map human activities and assess their intensity. To identify settlements more effectively, this study focused on nighttime light in the northern Equatorial Africa and Sahel settlements to propose a new method, namely, the patches filtering method (PFM) to identify nighttime lights related to settlements from the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) monthly nighttime light data by separating signal components induced by biomass burning, thereby generating a new annual image in 2016. The results show that PFM is useful for improving the quality of NPP-VIIRS monthly nighttime light data. Settlement lights were effectively separated from biomass burning lights, in addition to capturing the seasonality of biomass burning. We show that the new 2016 nighttime light image can very effectively identify even small settlements, notwithstanding their fragmentation and unstable power supply. We compared the image with earlier NPP-VIIRS annual nighttime light data from the National Oceanic and Atmospheric Administration (NOAA) National Center for Environmental Information (NCEI) for 2016 and the Sentinel-2 prototype Land Cover 20 m 2016 map of Africa released by the European Space Agency (ESA-S2-AFRICA-LC20). We found that the new annual nighttime light data performed best among the three datasets in capturing settlements, with a high recognition rate of 61.8%, and absolute superiority for settlements of 2.5 square kilometers or less. This shows that the method separates biomass burning signals very effectively, while retaining the relatively stable, although dim, lights of small settlements. The new 2016 annual image demonstrates good performance in identifying human settlements in sparsely populated areas toward a better understanding of human activities.

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Applications of Satellite Remote Sensing of Nighttime Light Observations: Advances, Challenges, and Perspectives

Remote Sensing ◽

10.3390/rs11171971 ◽

2019 ◽

Vol 11 (17) ◽

pp. 1971 ◽

Cited By ~ 28

Author(s):

Zhao ◽

Zhou ◽

Li ◽

Cao ◽

He ◽

...

Keyword(s):

Remote Sensing ◽

Human Activities ◽

Energy Use ◽

Environmental Changes ◽

Deep Understanding ◽

Historical Review ◽

Ancillary Data ◽

Nighttime Light Data ◽

Nighttime Light ◽

Changing World

Nighttime light observations from remote sensing provide us with a timely and spatially explicit measure of human activities, and therefore enable a host of applications such as tracking urbanization and socioeconomic dynamics, evaluating armed conflicts and disasters, investigating fisheries, assessing greenhouse gas emissions and energy use, and analyzing light pollution and health effects. The new and improved sensors, algorithms, and products for nighttime lights, in association with other Earth observations and ancillary data (e.g., geo-located big data), together offer great potential for a deep understanding of human activities and related environmental consequences in a changing world. This paper reviews the advances of nighttime light sensors and products and examines the contributions of nighttime light remote sensing to perceiving the changing world from two aspects (i.e., human activities and environmental changes). Based on the historical review of the advances in nighttime light remote sensing, we summarize the challenges in current nighttime light remote sensing research and propose four strategic directions, including: Improving nighttime light data; developing a long time series of consistent nighttime light data; integrating nighttime light observations with other data and knowledge; and promoting multidisciplinary and interdisciplinary analyses of nighttime light observations.

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Correlation Analysis between NPP-VIIRS Nighttime Light Data and POIs Data —a Comparison Study in Different Districts and Counties of Nanchang

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/693/1/012103 ◽

2021 ◽

Vol 693 (1) ◽

pp. 012103

Author(s):

Yuqian Wang ◽

Yue Li ◽

Xuepeng Song ◽

Xin Zou ◽

Jiajun Xiao

Keyword(s):

Correlation Analysis ◽

Comparison Study ◽

Nighttime Light Data ◽

Nighttime Light

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How does the urbanization level change in the Yangtze River economic belt, China? A multi-scale evaluation using DMSP/OLS nighttime light data

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/675/1/012112 ◽

2021 ◽

Vol 675 (1) ◽

pp. 012112

Author(s):

Zhiyu Xu ◽

Xiujuan He ◽

Lin Chen ◽

Xunxun Hu ◽

Weiming Tang ◽

...

Keyword(s):

Yangtze River ◽

The Yangtze River ◽

Urbanization Level ◽

Scale Evaluation ◽

Multi Scale ◽

Level Change ◽

Nighttime Light Data ◽

Nighttime Light

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Delineating the Urban Areas of a Cross-Boundary City with Open-Access Data: Guangzhou–Foshan, South China

Sustainability ◽

10.3390/su13052930 ◽

2021 ◽

Vol 13 (5) ◽

pp. 2930

Author(s):

Pengfei Ban ◽

Wei Zhan ◽

Qifeng Yuan ◽

Xiaojian Li

Keyword(s):

Urban Area ◽

Urban Areas ◽

City Size ◽

Border City ◽

Point Of Interest ◽

Nighttime Light Data ◽

Profile Line ◽

Point Analysis ◽

Nighttime Light ◽

Single Data

Cities defined mainly from the administrative aspect can create impact and problems especially in the case of China. However, only a few researchers from China have attempted to identify urban areas from the morphology dimension. In addition, previous studies have been mostly based on the national and regional scales or a single prefecture city and have completely ignored cross-boundary cities. Defining urban areas on the basis of a single data type also has limitations. To address these problems, this study integrates point of interest and nighttime light data, applies the breaking point analysis method to determine the physical geographic scope of the Guangzhou–Foshan cross-border city, and then compares this city with Beijing and Shanghai. Results show that Guangzhou–Foshan comprises one core urban area and six suburban counties, among which the core urban area extends across the administrative boundaries of Guangzhou and Foshan. The urban area and average urban radius of Guangzhou–Foshan are larger than those of Beijing and Shanghai, and this finding contradicts the city size measurements based on the administrative division system of China and those published on traditional official statistical yearbooks. In terms of urban density value, Shanghai has the steepest profile followed by Guangzhou–Foshan and Beijing, and the profile line of Guangzhou–Foshan has a bimodal shape.

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