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 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 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 Explore the application of high-resolution nighttime light remote sensing images in nighttime marine ship detection: A case study of LJ1-01 data

2020 ◽  
Vol 12 (1) ◽  
pp. 1169-1184
Author(s):  
Liang Zhong ◽  
Xiaosheng Liu ◽  
Peng Yang ◽  
Rizhi Lin
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Infrared Imaging ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Constant False Alarm Rate ◽  
Remote Sensing Images ◽  
Ship Detection ◽  
Application Potential ◽  
Nighttime Light

AbstractNighttime light remote sensing images show significant application potential in marine ship monitoring, but in areas where ships are densely distributed, the detection accuracy of the current methods is still limited. This article considered the LJ1-01 data as an example, compared with the National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) data, and explored the application of high-resolution nighttime light images in marine ship detection. The radiation values of the aforementioned two images were corrected to achieve consistency, and the interference light sources of the ship light were filtered. Then, when the threshold segmentation and two-parameter constant false alarm rate methods are combined, the ships’ location information was with obtained, and the reliability of the results was analyzed. The results show that the LJ1-01 data can not only record more potential ship light but also distinguish the ship light and background noise in the data. The detection accuracy of the LJ1-01 data in both ship detection methods is significantly higher than that of the NPP/VIIRS data. This study analyzes the characteristics, performance, and application potential of the high-resolution nighttime light data in the detection of marine vessels. The relevant results can provide a reference for the high-precision monitoring of nighttime marine ships.

Measuring the regional non-observed economy in China with nighttime lights

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Menggen Chen ◽  
Shuai Zhang
Keyword(s):  
Design Methodology ◽  
Eastern Region ◽  
Middle Region ◽  
Content Type ◽  
Nighttime Lights ◽  
Defense Meteorological Satellite Program ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Average Size ◽  
Meteorological Satellite

PurposeThe non-observed economy (NOE) is a pervasive phenomenon worldwide, especially in developing countries, but the size of the NOE and its contributions to the overall economy are usually unknown. This paper presents an estimation of the average size of the NOE for the 31 provincial regions in China between 1992 and 2013.Design/methodology/approachThis study uses the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data combined with 11 existing surveys on or measurements of NOE for 191 countries or regions throughout the world, to measure the size of the NOE.FindingsThe results show that the NOE share is unevenly distributed among China's provincial regions, with the smallest being 3.19% for Beijing and the largest being 69.71% for Ningxia. The national average is 43.11%, while the figures for the eastern region, middle region, northeastern region and western region are 39.3%, 47.6%, 44.7% and 43.6%, respectively. The NOE estimates are negatively correlated with the measured gross domestic product (GDP) and GDP per capita, which suggests that developed regions tend to have less NOE.Originality/valueThe nighttime lights are used to measure the NOE for China's provincial regions. Compared with traditional databases, one of the prominent features of nighttime lights is its objectivity, as there is little human interference; therefore, it can be used to achieve more accurate results.

scholarly journals Extending the DMSP Nighttime Lights Time Series beyond 2013

2021 ◽  
Vol 13 (24) ◽  
pp. 5004
Author(s):  
Tilottama Ghosh ◽  
Kimberly E. Baugh ◽  
Christopher D. Elvidge ◽  
Mikhail Zhizhin ◽  
Alexey Poyda ◽  
...  
Keyword(s):  
Time Series ◽  
Infrared Imaging ◽  
Earth Observation ◽  
Observation Group ◽  
Diurnal Pattern ◽  
High Brightness ◽  
The Earth ◽  
Early Evening ◽  
Nighttime Lights ◽  
Meteorological Satellite

Data collected by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) sensors have been archived and processed by the Earth Observation Group (EOG) at the National Oceanic and Atmospheric Administration (NOAA) to make global maps of nighttime images since 1994. Over the years, the EOG has developed automatic algorithms to make Stable Lights composites from the OLS visible band data by removing the transient lights from fires and fishing boats. The ephemeral lights are removed based on their high brightness and short duration. However, the six original satellites collecting DMSP data gradually shifted from day/night orbit to dawn/dusk orbit, which is to an earlier overpass time. At the beginning of 2014, the F18 satellite was no longer collecting usable nighttime data, and the focus had shifted to processing global nighttime images from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) data. Nevertheless, it was soon discovered that the F15 and F16 satellites had started collecting pre-dawn nighttime data from 2012 onwards. Therefore, the established algorithms of the previous years were extended to process OLS data from 2013 onwards. Moreover, the existence of nighttime data from three overpass times for the year 2013–DMSP satellites F18 and F15 from early evening and pre-dawn, respectively, and the VIIRS from after midnight, made it possible to intercalibrate the images of three different overpass times and study the diurnal pattern of nighttime lights.

Assessing nighttime lights for mapping the urban areas of 50 cities across the globe

2018 ◽  
Vol 46 (6) ◽  
pp. 1097-1114
Author(s):  
Hasi Bagan ◽  
Habura Borjigin ◽  
Yoshiki Yamagata
Keyword(s):  
Urban Areas ◽  
Comprehensive Evaluation ◽  
Grid Cell ◽  
Small Cities ◽  
Large Cities ◽  
Nighttime Lights ◽  
Defense Meteorological Satellite Program ◽  
Nighttime Light ◽  
The Relationship ◽  
Meteorological Satellite

Nighttime data from the Defense Meteorological Satellite Program Operational Linescan System have been widely used to map urban/built-up areas (hereafter referred to as “built-up area”), but to date there has not been a geographically comprehensive evaluation of the effectiveness of using nighttime lights data to map urban areas. We created accurate, convenient, and scalable grid cells based on Defense Meteorological Satellite Program/Operational Linescan System nighttime light pixels. We then calculated the density of Landsat-derived built-up areas within each grid cell. We explored the relationship between Defense Meteorological Satellite Program/Operational Linescan System nighttime lights data and the density of built-up areas to assess the utility of nighttime lights for mapping urban areas in 50 cities across the globe. We found that the brightness of nighttime lights was only in moderate agreement with the density of built-up areas; moreover, correlations between nighttime lights and Landsat-derived built-up areas were weak. Even in relatively sparsely populated urban regions (where the density of the built-up area is less than 20%), the highest correlation coefficient ( R2) was only 0.4. Furthermore, nighttime lights showed lighted areas that extended beyond the area of large cities, and nighttime lights reduced the area of small cities. The results suggest that it is difficult to use the regression model to calibrate the Defense Meteorological Satellite Program/Operational Linescan System nighttime lights to fit urban built up areas.

scholarly journals Global Nighttime Light Change from 1992 to 2017: Brighter and More Uniform

2020 ◽  
Vol 12 (12) ◽  
pp. 4905
Author(s):  
Yunfeng Hu ◽  
Yunzhi Zhang
Keyword(s):  
United States ◽  
Infrared Imaging ◽  
Electricity Consumption ◽  
The United States ◽  
Added Value ◽  
Light Change ◽  
Nighttime Lights ◽  
Long Time ◽  
Nighttime Light

Nighttime light images record the brightness of the Earth surface, indicating the scope and intensity of human activities. However, there are few studies on the long-term changes in global nighttime lights. In this paper, the authors constructed a long time series (1992~2017) nighttime light dataset combining the Defense Meteorological Satellites Program/Operational Linescan System (DMSP-OLS) and the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) data sources and observed the following: (1) Global nighttime lights have become brighter. The global nighttime brightness in 2017 was 2.2 times that of 1992. Approximately 40.3% of the lighted area was significantly brightened, and an area of 1.3 × 107 km2 transitioned from an unlighted area to a lighted area. (2) Approximately 85.7% of the nighttime light increase occurred in the low-brightness zone (LBZ). Therefore, global brightness has become more uniform than before. (3) China, India, and the United States have led the global lighting trend. The increase in Chinese nighttime lights is the largest, with an average annual growth of 6.48%, followed by the light growth in India, while the United States has the largest brightened area. (4) The changes in nighttime lights in developing countries (e.g., China and India) are closely and positively related to their electricity consumption, industrial added value and gross domestic product (GDP). The shift of the LBZ center from Asia to Africa indicates the intercontinental transition of poverty.

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 MONITORING DISASTER-RELATED POWER OUTAGES USING NASA BLACK MARBLE NIGHTTIME LIGHT PRODUCT

2018 ◽  
Vol XLII-3 ◽  
pp. 1853-1856 ◽  
Author(s):  
Z. Wang ◽  
M. O. Román ◽  
Q. Sun ◽  
A. L. Molthan ◽  
L. A. Schultz ◽  
...  
Keyword(s):  
Disaster Response ◽  
Situational Awareness ◽  
Infrared Imaging ◽  
Activity Patterns ◽  
Power Outages ◽  
Electricity Grid ◽  
Nighttime Lights ◽  
Standard Product ◽  
Nighttime Light ◽  
Human Activity Patterns

Timely and accurate monitoring of disruptions to the electricity grid, including the magnitude, spatial extent, timing, and duration of net power losses, is needed to improve situational awareness of disaster response and long-term recovery efforts. Satellite-derived Nighttime Lights (NTL) provide an indication of human activity patterns and have been successfully used to monitor disaster-related power outages. The global 500 m spatial resolution National Aeronautics and Space Administration (NASA) Black Marble NTL daily standard product suite (VNP46) is generated from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the NASA/National Oceanic and Atmospheric Administration (NOAA) Suomi National Polar-orbiting Partnership (Suomi- NPP) satellite, which began operations on 19 January 2012. With its improvements in product accuracy (including critical atmospheric and BRDF correction routines), the VIIRS daily Black Mable product enables systematic monitoring of outage conditions across all stages of the disaster management cycle.

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