scholarly journals An extended time-series (2000–2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration

2020 ◽  
Author(s):  
Zuoqi Chen ◽  
Bailang Yu ◽  
Chengshu Yang ◽  
Yuyu Zhou ◽  
Xingjian Qian ◽  
...  
Keyword(s):  
Time Series ◽  
Infrared Imaging ◽  
Sensor Calibration ◽  
Temporal Consistency ◽  
Extended Time ◽  
Economic Activities ◽  
Time Period ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
The Difference

Abstract. The nighttime light (NTL) satellite data have been widely used to investigate urbanization process. The Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) stable nighttime light data and Suomi National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data are two widely used NTL datasets. However, the difference of their spatial resolutions and sensor design makes it difficult to directly use these two datasets together for a long-term analysis of urbanization. To solve this issue, an extended time-series (2000–2018) of NPP-VIIRS-like NTL data were proposed in this study through a cross-sensor calibration from DMSP-OLS NTL data (2000–2012) and a composition of monthly NPP-VIIRS NTL data (2013–2018). Compared with the annual composited NPP-VIIRS NTL data in 2012, our product of extended NPP-VIIRS-like NTL data shows a good consistency at the pixel and city levels with R2 of 0.87 and 0.95, respectively. We also found that our product has a good accuracy by comparing with DMSP-OLS radiance calibrated NTL (RNTL) data in 2000, 2004, 2006, and 2010. Generally, our extended NPP-VIIRS-like NTL data (2000–2018) have a good spatial pattern and temporal consistency, which are similar to the composited NPP-VIIRS NTL data. In addition, the resulting product could be easily updated and provide a useful proxy to monitor the dynamics of demographic and socio-economic activities for a longer time period compared to existing products. The extended time-series (2000–2018) of nighttime light data are freely accessible at https://doi.org/10.7910/DVN/YGIVCD (Chen et al., 2020).

scholarly journals An extended time series (2000–2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration

2021 ◽  
Vol 13 (3) ◽  
pp. 889-906
Author(s):  
Zuoqi Chen ◽  
Bailang Yu ◽  
Chengshu Yang ◽  
Yuyu Zhou ◽  
Shenjun Yao ◽  
...  
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Infrared Imaging ◽  
Great Accuracy ◽  
Sensor Calibration ◽  
Temporal Consistency ◽  
Extended Time ◽  
Urbanization Process ◽  
Nighttime Light Data ◽  
Nighttime Light

Abstract. The nighttime light (NTL) satellite data have been widely used to investigate the urbanization process. The Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) stable nighttime light data and Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data are two widely used NTL datasets. However, the difference in their spatial resolutions and sensor design requires a cross-sensor calibration of these two datasets for analyzing a long-term urbanization process. Different from the traditional cross-sensor calibration of NTL data by converting NPP-VIIRS to DMSP-OLS-like NTL data, this study built an extended time series (2000–2018) of NPP-VIIRS-like NTL data through a new cross-sensor calibration from DMSP-OLS NTL data (2000–2012) and a composition of monthly NPP-VIIRS NTL data (2013–2018). The proposed cross-sensor calibration is unique due to the image enhancement by using a vegetation index and an auto-encoder model. Compared with the annual composited NPP-VIIRS NTL data in 2012, our product of extended NPP-VIIRS-like NTL data shows a good consistency at the pixel and city levels with R2 of 0.87 and 0.95, respectively. We also found that our product has great accuracy by comparing it with DMSP-OLS radiance-calibrated NTL (RNTL) data in 2000, 2004, 2006, and 2010. Generally, our extended NPP-VIIRS-like NTL data (2000–2018) have an excellent spatial pattern and temporal consistency which are similar to the composited NPP-VIIRS NTL data. In addition, the resulting product could be easily updated and provide a useful proxy to monitor the dynamics of demographic and socioeconomic activities for a longer time period compared to existing products. The extended time series (2000–2018) of nighttime light data is freely accessible at https://doi.org/10.7910/DVN/YGIVCD (Chen et al., 2020).

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 Response Patterns of Vegetation Phenology along Urban-Rural Gradients in Urban Areas of Different Sizes

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Xue Luo ◽  
Yuqing Zhang ◽  
Dongqi Sun
Keyword(s):  
Urban Areas ◽  
Growing Season ◽  
Liaoning Province ◽  
Vegetation Phenology ◽  
Coastal Cities ◽  
Nighttime Light Data ◽  
Urban Rural ◽  
Nighttime Light ◽  
Urban Size ◽  
The Difference

On the basis of MODIS Enhanced Vegetation Index time series data and multisource data, such as nighttime light data and China City Statistical Yearbook data, we investigated the differences in vegetation phenology along urban-rural gradients in urban areas of different sizes between coastal and inland cities in Liaoning Province, China. The results showed that the following: (1) the iterative extraction of urban built-up areas using the threshold method based on nighttime light data combined with the definition of urban built-up areas had high accuracy. (2) Additionally, we found that the start of the growing season (SOS) in Liaoning Province occurred between day 100 and day 180, while the end of the growing season (EOS) occurred between days 260 and 330. The difference in the SOS between coastal cities (i.e., Dalian, Yingkou, Panjin, Jinzhou, Huludao, and Dandong) and inland cities (i.e., Chaoyang, Fuxin, Tieling, Shenyang, Fushun, Liaoyang, Benxi, and Anshan) was 1.70 days. However, the difference in the EOS was more significant, i.e., the EOS in coastal cities occurred 4.47 days later than that in the inland cities. (3) In urban areas of different sizes, the ∆SOS and ∆EOS of inland cities had negative correlations with urban size. Specifically, when the urban size increased 10-fold, the ∆SOS and ∆EOS advanced by 10.03 and 5.71 days, respectively. In contrast, the ∆SOS and ∆EOS of coastal cities had positive and negative correlations with the urban size, respectively. Specifically, when urban size increased 10-fold, ∆SOS was delayed by 11.29 days while EOS was advanced by 8.83 days.

scholarly journals Anthropogenic Heat Flux Estimation Based on Luojia 1-01 New Nighttime Light Data: A Case Study of Jiangsu Province, China

2020 ◽  
Vol 12 (22) ◽  
pp. 3707
Author(s):  
Zhongli Lin ◽  
Hanqiu Xu
Keyword(s):  
Heat Flux ◽  
Energy Consumption ◽  
Urban Climate ◽  
Power Estimation ◽  
Anthropogenic Heat ◽  
Economic Activities ◽  
Estimation Model ◽  
Nighttime Light Data ◽  
Anthropogenic Heat Flux ◽  
Nighttime Light

With the rapid process of urbanization, anthropogenic heat generated by human activities has become an important factor that drives the changes in urban climate and regional environmental quality. The nighttime light (NTL) data can aptly reflect the spatial distribution of social-economic activities and energy consumption, and quantitatively estimate the anthropogenic heat flux (AHF) distribution. However, the commonly used DMSP/OLS and Suomi-NPP/VIIRS NTL data are restricted by their coarse spatial resolution and, therefore, cannot exhibit the spatial details of AHF at city scale. The 130 m high-resolution NTL data obtained by Luojia 1-01 satellite launched in June 2018 shows a promise to solve this problem. In this paper, the gridded AHF spatial estimation is achieved with a resolution of 130 m using Luojia 1-01 NTL data based on three indexes, NTLnor (Normalized Nighttime Light Data), HSI (Human Settlement Index), and VANUI (Vegetation Adjusted NTL Urban Index). We chose Jiangsu, a fast-developing province in China, as an example to determine the best AHF estimation model among the three indexes. The AHF of 96 county-level cities of the province was first calculated using energy-consumption statistics data and then correlated with the corresponding data of three indexes. The results show that based on a 5-fold cross-validation approach, the VANUI power estimation model achieves the highest R2 of 0.8444 along with the smallest RMSE of 4.8277 W·m−2 and therefore has the highest accuracy among the three indexes. According to the VANUI power estimation model, the annual mean AHF of Jiangsu in 2018 was 2.91 W·m−2. Of the 96 cities, Suzhou has the highest annual mean AHF of 7.41 W·m−2, followed by Wuxi, Nanjing, Changzhou and Zhenjiang, with the annual mean of 3.80–5.97 W·m−2, while the figures of Suqian, Yancheng, Lianyungang, and Huaian, the cities in northern Jiangsu, are relatively low, ranging from 1.41 to 1.59 W·m−2. This study has shown that the AHF estimation model developed by Luojia 1-01 NTL data can achieve higher accuracy at city-scale and discriminate the spatial detail of AHF effectively.

Mapping Global Urban Areas From 2000 to 2012 Using Time-Series Nighttime Light Data and MODIS Products

2019 ◽  
Vol 12 (4) ◽  
pp. 1143-1153 ◽  
Author(s):  
Zuoqi Chen ◽  
Bailang Yu ◽  
Yuyu Zhou ◽  
Hongxing Liu ◽  
Chengshu Yang ◽  
...  
Keyword(s):  
Time Series ◽  
Urban Areas ◽  
Nighttime Light Data ◽  
Nighttime Light

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 Decennal geomorphic transport from archived time series digital elevation models: a cookbook for tropical and alpine environments.

2021 ◽  
Author(s):  
Antoine Lucas ◽  
Eric Gayer
Keyword(s):  
Time Series ◽  
Time Scale ◽  
Aerial Images ◽  
Sensor Calibration ◽  
Dense Matching ◽  
Time Period ◽  
Digital Elevation ◽  
Seasonal Time Scale ◽  
Areas Of Interest ◽  
Alpine Environments

<div> <div> <div> <p>On the seasonal time scale, for accessible locations and when manpower is available, direct observations and field survey are the most useful and standard approaches. However very limited studies have been conducted on direct observation at the decennial to century time-scale due to observational constrains. Here, we present an open and reproducible pipeline based on historical aerial images (up to 70 yrs time span) that includes sensor calibration, dense matching and elevation reconstruction over two areas of interest that represent pristine examples for tropical and alpine environments. The Remparts Canyon and Langevin River in Reunion Island, and the Bossons glacier in the French Alps share a limited accessibility (in time and space) that can be overcome only from remote-sensing. We reach a metric to sub-metric resolution close to the nominal images spatial sampling. This provides elevation time series with a better resolution to most recent satellite images such as Pleiades over decennial time period. </p> </div> </div> </div>

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