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

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.

scholarly journals Are Karst Rocky Desertification Areas Affected by Increasing Human Activity in Southern China? An Empirical Analysis from Nighttime Light Data

2019 ◽  
Vol 16 (21) ◽  
pp. 4175
Author(s):  
Shi ◽  
Yang ◽  
Li
Keyword(s):  
Human Activities ◽  
Socioeconomic Development ◽  
Infrared Imaging ◽  
Southern China ◽  
Annual Growth Rate ◽  
Karst Rocky Desertification ◽  
Rocky Desertification ◽  
Nighttime Lights ◽  
Nighttime Light ◽  
Night Lights

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 Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) nighttime light composite 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 was 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.

scholarly journals Are Karst Rocky Desertification Areas Affected by Increasing Human Activity in Southern China? An Empirical Analysis from Nighttime Light Data

2019 ◽  
Author(s):  
Kaifang Shi ◽  
Qingyuan Yang ◽  
Yuanqing Li
Keyword(s):  
Human Activities ◽  
Socioeconomic Development ◽  
Southern China ◽  
Annual Growth Rate ◽  
Karst Rocky Desertification ◽  
Rocky Desertification ◽  
Nighttime Lights ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Night Lights

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.

scholarly journals Assessing the Ability of Luojia 1-01 Imagery to Detect Feeble Nighttime Lights

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3708 ◽  
Author(s):  
Li ◽  
Liu ◽  
Chen ◽  
Sun
Keyword(s):  
Infrared Imaging ◽  
Detection Accuracy ◽  
Application Research ◽  
Threshold Method ◽  
Minimum Area ◽  
Nighttime Lights ◽  
Nighttime Light ◽  
Data Source ◽  
Meteorological Satellite ◽  
Cutoff Threshold

The Luojia1-01 (LJ1-01) satellite launched on June 2, 2018 provides a new option for nighttime light (NTL) application research. In this paper, four types of human settlements, such as cities, counties, towns and villages, are sampled to evaluate the potential of LJ1-01 to detect feeble NTL by comparing with the NTL images from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-Orbiting Partnership Satellite. First, the landscape indices and cutoff threshold method are applied to enhance signal-noise ratio (SNR). Then, the detection accuracy of samples is evaluated to determine the optimal cutoff threshold for each NTL data source. After that, the spatial correspondence of different NTL images and the area consistency between the samples and NTL footprints are compared. Finally, after the discussion of feeble NTL detection and the influence of clouds, moonlight and image composites, it can be concluded that LJ1-01 is more suitable for detection feeble NTL objects, while great importance should be attached to the measures to eliminate the noise in LJ1-01 image and make LJ1-01 more widely used: (1) In the study area, a suitable cutoff threshold of LJ1-01 image can be set to 0.1 nano-Wcm−2sr−1, which is lower than that of VIIRS image (0.3 nano-Wcm−2sr−1), and this enables LJ1-01 to reserve more information of NTL, especially the feeble NTL. Moreover, the minimum area that can be identified by NTL footprints from LJ1-01 is 0.02 km2, while that of VIIRS and DMSP are 0.3 km2 and 4.5 km2, respectively. (2) The cutoff threshold method can identify the range of NTL with more noise, but cannot eliminate the noise separately. The filtering method and the image composition method may play more important role in the applications of LJ1-01 data.

scholarly journals Identification of Shrinkage and Growth Patterns of a Shrinking City in China Based on Nighttime Light Data: A Case Study of Yichun

2019 ◽  
Vol 11 (24) ◽  
pp. 6906 ◽  
Author(s):  
Ying Zhou ◽  
Chenggu Li ◽  
Zuopeng Ma ◽  
Shuju Hu ◽  
Jing Zhang ◽  
...  
Keyword(s):  
Satellite Images ◽  
Infrared Imaging ◽  
Demographic Data ◽  
Growth Patterns ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Urban Science ◽  
New Perspective ◽  
Shrinking City

Urban shrinkage has become a topic of major concern to scholars of geography and urban science. However, the methods of identifying urban shrinkage and growth have mostly focused on traditional statistical methods, and studies based on nighttime light (NTL) data are rare. Here, we use the NTL data for 56 months from 2012 to 2019 obtained by the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar Orbiting Partnership (NPP) to identify the shrinkage and growth patterns of Yichun in China, by calculating the slope of the NTL radiance value after denoising. At the same time, by combining high-resolution Google satellite images and traditional demographic data, we analyzed the shrinkage characteristics of Yichun. The results of the study confirmed the characteristics of partial shrinkage in China’s shrinking cities. In addition, the use of NPP-VIIRS NTL data was able to more accurately identify the urban shrinkage and growth patterns, and may also be seen to present a more objective picture of reality, thus providing a new perspective for studies of urban shrinkage.

scholarly journals Does China’s Urban Development Satisfy Zipf’s Law? A Multiscale Perspective from the NPP-VIIRS Nighttime Light Data

2020 ◽  
Vol 17 (4) ◽  
pp. 1460 ◽  
Author(s):  
Yizhen Wu ◽  
Mingyue Jiang ◽  
Zhijian Chang ◽  
Yuanqing Li ◽  
Kaifang Shi
Keyword(s):  
Urban Development ◽  
Infrared Imaging ◽  
Multiple Scales ◽  
Decision Makers ◽  
Zipf’S Law ◽  
Zipf's Law ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Zipf Law ◽  
The Ideal

Currently, whether the urban development in China satisfies Zipf’s law across different scales is still unclear. Thus, this study attempted to explore whether China’s urban development satisfies Zipf’s law across different scales from the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data. First, the NPP-VIIRS data were corrected. Then, based on the Zipf law model, the corrected NPP-VIIRS data were used to evaluate China’s urban development at multiple scales. The results showed that the corrected NPP-VIIRS data could effectively reflect the state of urban development in China. Additionally, the Zipf index (q) values, which could express the degree of urban development, decreased from 2012 to 2018 overall in all provinces, prefectures, and counties. Since the value of q was relatively close to 1 with an R2 value > 0.70, the development of the provinces and prefectures was close to the ideal Zipf’s law state. In all counties, q > 1 with an R2 value > 0.70, which showed that the primate county had a relatively stronger monopoly capacity. When the value of q < 1 with a continuous declination in the top 2000 counties, the top 250 prefectures, and the top 20 provinces in equilibrium, there was little difference in the scale of development at the multiscale level with an R2 > 0.90. The results enriched our understanding of urban development in terms of Zipf’s law and had valuable implications for relevant decision-makers and stakeholders.

scholarly journals Spatiotemporal Variations of City-Level Carbon Emissions in China during 2000–2017 Using Nighttime Light Data

2020 ◽  
Vol 12 (18) ◽  
pp. 2916
Author(s):  
Yu Sun ◽  
Sheng Zheng ◽  
Yuzhe Wu ◽  
Uwe Schlink ◽  
Ramesh P. Singh
Keyword(s):  
Carbon Emissions ◽  
Infrared Imaging ◽  
Yangtze River Delta ◽  
Chinese Government ◽  
Low Carbon ◽  
Spatiotemporal Variations ◽  
Nighttime Light Data ◽  
Low Emission ◽  
High Emission ◽  
Nighttime Light

China is one of the largest carbon emitting countries in the world. Numerous strategies have been considered by the Chinese government to mitigate carbon emissions in recent years. Accurate and timely estimation of spatiotemporal variations of city-level carbon emissions is of vital importance for planning of low-carbon strategies. For an assessment of the spatiotemporal variations of city-level carbon emissions in China during the periods 2000–2017, we used nighttime light data as a proxy from two sources: Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data and the Suomi National Polar-orbiting Partnership satellite’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The results show that cities with low carbon emissions are located in the western and central parts of China. In contrast, cities with high carbon emissions are mainly located in the Beijing-Tianjin-Hebei region (BTH) and Yangtze River Delta (YRD). Half of the cities of China have been making efforts to reduce carbon emissions since 2012, and regional disparities among cities are steadily decreasing. Two clusters of high-emission cities located in the BTH and YRD followed two different paths of carbon emissions owing to the diverse political status and pillar industries. We conclude that carbon emissions in China have undergone a transformation to decline, but a very slow balancing between the spatial pattern of high-emission versus low-emission regions in China can be presumed.

scholarly journals China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jiandong Chen ◽  
Ming Gao ◽  
Shulei Cheng ◽  
Xin Liu ◽  
Wenxuan Hou ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Infrared Imaging ◽  
Carbon Intensity ◽  
Nighttime Light Data ◽  
Reduction Strategies ◽  
Nighttime Light ◽  
Novel Method ◽  
Data Source ◽  
Emission Reduction Strategies

AbstractAccurate, long-term, full-coverage carbon dioxide (CO2) data in units of prefecture-level cities are necessary for evaluations of CO2 emission reductions in China, which has become one of the world’s largest carbon-emitting countries. This study develops a novel method to match satellite-based Defense Meteorological Satellite Program’s Operational Landscan System (DMSP/OLS) and Suomi National Polar-orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light data, and estimates the CO2 emissions of 334 prefecture-level cities in China from 1992 to 2017. Results indicated that the eastern and coastal regions had higher carbon emissions, but their carbon intensity decreased more rapidly than other regions. Compared to previous studies, we provide the most extensive and long-term CO2 dataset to date, and these data will be of great value for further socioeconomic research. Specifically, this dataset provides a foundational data source for China’s future CO2 research and emission reduction strategies. Additionally, the methodology can be applied to other regions around the world.

scholarly journals Evaluating the Potential of LJ1-01 Nighttime Light Data for Modeling Socio-Economic Parameters

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1465 ◽  
Author(s):  
Guo Zhang ◽  
Xueyao Guo ◽  
Deren Li ◽  
Boyang Jiang
Keyword(s):  
Infrared Imaging ◽  
Electricity Consumption ◽  
The United States ◽  
Gross Regional Product ◽  
Linear Regression Models ◽  
Nighttime Light Data ◽  
Economic Parameters ◽  
Nighttime Light ◽  
Positive Correlations ◽  
Regional Product

The LJ1-01 satellite is the first dedicated nighttime light remote sensing satellite in the world and offers a higher spatial resolution than the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) satellites of the United States. This study compared the LJ1-01 nighttime light data with NPP/VIIRS data in the context of modeling socio-economic parameters. In the eastern and central regions of China, 10 parameters from the four aspects of gross regional product (annual average population, electricity consumption, and area of land in use) were selected to build linear regression models. The results showed that the LJ1-01 nighttime light data offered better potential for modeling socio-economic parameters than the equivalent NPP/VIIRS data; the former can be an effective tool for establishing models for socio-economic parameters. There were significant positive correlations between the two types of nighttime light data and the 10 socio-economic parameters; that for the gross regional product was the highest.

Sign in / Sign up

Export Citation Format

Share Document