The Interannual Calibration and Global Nighttime Light Fluctuation Assessment Based on Pixel-Level Linear Regression Analysis

Zheng, Zihao; Yang, Rong-Jia; Chen, Guihai; Wu, Kan; Marinello, Francesco

doi:10.3390/rs11182185

Cited by 17 publications

(10 citation statements)

References 55 publications

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“…To overcome the shortcomings of existing methods, the STAPIP method performs consistency calibration for both unsaturated and saturated pixels. We applied the proposed scheme to China and compared the results with four calibration methods proposed by Liu et al [55], Wu et al [24], Elvidge et al [47], and Zheng et al [48], respectively.…”

Section: Discussionmentioning

confidence: 99%

“…The calibration results of the proposed TAPIP method were compared with those of four representative calibration methods proposed by Wu et al [24], Elvidge et al [47], Zhang et al [26], and Zheng et al [48], respectively. As shown in Fig.…”

Section: A Consistency Calibration Analysis Of the Nsl Images Acquire...mentioning

confidence: 99%

“…A stable PIP set is a basis for the consistency calibration of the NSL images. In this study, we use the mean DN value, interquartile range (IQR) and RMSD [54] to assess the stability of the PIP set selected by the proposed TAPIP method, in comparison with the methods proposed by Liu et al [55], Wu et al [24], Elvidge et al [47], and Zheng et al [48], respectively…”

Section: A Stability Analysis Of Pseudo-invariant Pixelmentioning

confidence: 99%

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A Novel Consistency Calibration Method for DMSP-OLS Nighttime Stable Light Time-Series Images

Yang

Cao

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The Defense Meteorological Satellite Program-Operational Line-Scan System (DMSP-OLS) nighttime stable light (NSL) products have been widely employed for studying human activities and urbanization. However, due to the lack of on-board calibration of the OLS sensors, narrow radiation range, and different satellite platforms, the NSL products suffer from several limitations such as saturation effect and inconsistency problem. To solve these issues, this study proposed a spatio-temporal adaptive pseudoinvariant pixel (STAPIP) scheme for NSL time-series consistency calibration based on eight-year DMSP-OLS radiance calibrated (RC) products. The unsaturated pixels were calibrated with the temporal adaptive pseudo-invariant pixel (TAPIP) method, while the saturated pixels were calibrated with the spatial adaptive PIP (SAPIP) method. To verify the proposed method's effectiveness, we applied it in China and compared its results with the results of several existing NSL calibration methods. Then we further analyzed the correlations between the calibrated NSL time-series images and several important socio-economic indicators, such as population, gross domestic product (GDP), and electricity consumption (EC). Results showed that the NSL time-series images calibrated by the STAPIP method have the best consistency and highest correlation with socio-economic indicators at both provincial and city levels. Thus, this study can provide an accurate and stable NSL time-series product for research on human activities and the urbanization process.

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Section: Discussionmentioning

confidence: 99%

Section: A Consistency Calibration Analysis Of the Nsl Images Acquire...mentioning

confidence: 99%

Section: A Stability Analysis Of Pseudo-invariant Pixelmentioning

confidence: 99%

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A Novel Consistency Calibration Method for DMSP-OLS Nighttime Stable Light Time-Series Images

Yang

Cao

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…There are a few approaches to improve a number of parameters of high-resolution DMSP data on nighttime lights, including geolocation error [31][32][33]. In this paper, it is presented an original approach to estimating and compensating for geolocation error of ODIAC data on CO 2 emissions (the error inherited from DMSP data), which is based on data on city boundaries and water bodies.…”

Section: Methodsmentioning

confidence: 99%

Mitigating geolocation errors in nighttime light satellite data and global CO2 emission gridded data

Kinakh¹,

Oda²,

Bun³

et al. 2021

Math. Model. Comput.

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Accurate geospatial modeling of greenhouse gas (GHG) emissions is an essential part of the future of global GHG monitoring systems. Our previous work found a systematic displacement in the high-resolution carbon dioxide (CO2) emission raster data of the Open-source Data Inventory for Anthropogenic CO2 (ODIAC) emission product. It turns out this displacement is due to geolocation bias in the Defense Meteorological Satellite Program (DMSP) nighttime lights (NTL) data products, which are used as a spatial emission proxy for estimating non-point source emissions distributions in ODIAC. Mitigating such geolocation error (~1.7 km), which is on the same order of the size of the carbon observing satellites field of view, is especially critical for the spatial analysis of emissions from cities. In this paper, there is proposed a method to mitigate the geolocation bias in DMSP NTL data that can be applied to DMSP NTL-based geospatial products, such as ODIAC. To identify and characterize the geolocation bias, we used the OpenStreetMap repository to define city boundaries for a large number of global cities. Assumption is that the total emissions within the city boundaries are at the maximum if there is no displacement (geolocation bias) in NTL data. Therefore, it is necessary to find an optimal vector (distance and angle) that maximizes the ODIAC total emissions within cities by shifting the emission fields. In the process of preparing annual composites of the nighttime stable lights data, some pixels of the DMSP data corresponding to water bodies were zeroed, which due to the geolocation bias unreasonably distorted the ODIAC emission fields. Hence, an original approach for restoring data in such pixels is considered using elimination of the factor that distorted the ODIAC emission fields. It is also proposed a bias correction method for shifted high-resolution emission fields in ODIAC. The bias correction was applied to multiple cities from the different continents. It is shown that the bias correction to the emission data (elimination of geolocation error in non-point emission source fields) increases the total CO2 emissions within city boundaries by 4.76% on average, due to reduced emissions from non-urban areas to which these emissions were likely to be erroneously attributed.

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“…This study selected five years of nighttime light data in 2000, 2005, 2010, 2015 and 2020, respectively, to analyze the coupling effect of urbanization and EEQ, of which the nighttime light data in 2000, 2005, and 2010 were from DMSP/OLS Stable Light (STL), with a spatial resolution of about 1 km (the original resolution of DMSP/OLS sensor was 2.8 km, with product resampling of 1 km), where the pixel gray value (DN value) represented the average light intensity, with a range of 0–63. Since there was a light saturation phenomenon with DMSP/OLS data drifting with images from different satellite sensors, this paper adopted a Pixel-Based Pseudo-Invariant Features (PBPIF) based on the fluctuation characteristics of pixels [ 43 ] to obtain the calibration light data of 2000, 2005 and 2010 of the study area. The nighttime light remote sensing data in 2015 and 2020 were from NPP/VIIRS Cloud Mask Straight Light (VCMSL).…”

Section: Study Area and Datamentioning

confidence: 99%

Analysis of Spatiotemporal Changes of Ecological Environment Quality and Its Coupling Coordination with Urbanization in the Yangtze River Delta Urban Agglomeration, China

Shi

Wang

Zhao

2023

IJERPH

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It is inevitable that urban agglomeration will have a coercive impact on the regional Ecological Environment Quality (EEQ) as a consequence of high-speed urbanization. Balancing the EEQ and urbanization development has become a problem worthy of attention. In order to objectively evaluate the EEQ of the Yangtze River Delta Urban Agglomeration (YRDUA) and explore the impact of the urbanization process on it, this paper is based on the Modified Remote Sensing Ecological Index (MRSEI) and the Comprehensive Night Light Index (CNLI), respectively, and conducts a quantitative assessment of the YRDUA in China from 2000 to 2020. The results show that: (1) From 2000 to 2020, the MRSEI of the YRDUA first decreased and then increased, and the ecological environment quality degraded first and then improved; however, there were significant differences between regions. The ecological environment quality in the south is obviously better than that in the north, and the ecological environment quality in the north changes more drastically, and the low value area of MRSEI will gradually move downstream as time changes; (2) During the study period, the YRDUA formed a hierarchical and progressive urbanization pattern. The inland urbanization process expanded from east to west along the Yangtze River, and the urbanization process of coastal cities expanded from Shanghai as the center to the north and south with high-intensity urbanization cities concentrated in Shanghai and its surrounding cities and low-intensity urbanization cities distributed in the western part of the urban agglomeration; (3) The Coupling Coordination Degree (CCD) between urbanization and EEQ in the YRDUA has continuously improved with an increase of 28.57% in the past 21 years, and the number of cities with high level coupling continues to rise, while the number of medium level coupling cities and low level coupling cities has declined. As a large-scale and long-term analysis of changes in the EEQ and the urbanization process, this study can provide theoretical support for policymakers to formulate mesoscale development planning, EEQ monitoring, and environmental protection policies.

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The Interannual Calibration and Global Nighttime Light Fluctuation Assessment Based on Pixel-Level Linear Regression Analysis

Cited by 17 publications

References 55 publications

A Novel Consistency Calibration Method for DMSP-OLS Nighttime Stable Light Time-Series Images

A Novel Consistency Calibration Method for DMSP-OLS Nighttime Stable Light Time-Series Images

Mitigating geolocation errors in nighttime light satellite data and global CO2 emission gridded data

Analysis of Spatiotemporal Changes of Ecological Environment Quality and Its Coupling Coordination with Urbanization in the Yangtze River Delta Urban Agglomeration, China

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