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Author (down) Wang, X.; Cheng, H.
Title Study on the Temporal and Spatial Pattern Differences of Chinese Light Curl Based on DMSP/OLS Type Journal Article
Year 2019 Publication IOP Conference Series: Earth and Environmental Science Abbreviated Journal IOP Conf. Ser.: Earth Environ. Sci.
Volume 310 Issue Pages 032072
Keywords Remote Sensing
Abstract Nighttime light data can detect surface gleams that can intuitively reflect human socioeconomic activity.This paper uses the DMSP/OLS nighttime lighting data from 2001 to 2007 to analyze the coupling relationship between regional economic development and nighttime light intensity in China using regression model.The results show that the brightest areas of nighttime light are mainly concentrated in the Beijing-Tianjin-Hebei region, the Yangtze River Delta region, and the Pearl River Delta region. With the change of theyear, the brightness of the three regions is brighter year by year, indicating that the economy is more and more developed.The linear regression model of total brightness and GDP of regional light: Y=792.218+0.024X, linear slope is 0.024, indicating a positive correlation trend.The provinces and cities with the highest total brightness of the provinces and cities are Guangdong Province, Shandong Province, and Jiangsu Province, and the lowest provinces and cities are Qinghai Province and Tibet Autonomous Region.The total brightness of regional lights in China's provinces and cities is well coupled with GDP. The total brightness of regional lights in all provinces and cities is weakened from east to west. The brightness of the 11 provinces in the eastern region is the strongest, including Beijing, Tianjin, Hebei, Liaoning, Shanghai, and Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Hainan Province.The second most powerful lighting is the eight provinces in the central region including Shanxi, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, and Hunan.The weakest lighting is in the western regions of Sichuan, Chongqing, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang, Guangxi, Inner Mongolia and other provinces (cities).In the east of the Hu Huanyong line, the nighttime lighting is higher than the west of the Hu Huanyong line.The eastern part of China's seven geographical divisions (Shanghai, Jiangsu, Zhejiang, Anhui, Jiangxi, Shandong, Fujian, and Taiwan) has the brightest night lights.The northwestern region (Shaanxi, Gansu, Qinghai, Ningxia Hui Autonomous Region, Xinjiang Uygur Autonomous Region, and Inner Mongolia Autonomous Region) has a weak night light.The brightness information of nighttime remote sensing data selected in this study can reflect the level of regional economic development.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1755-1315 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2670
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Author (down) Wang, W.; Cheng, H.; Zhang, L.
Title Poverty assessment using DMSP/OLS night-time light satellite imagery at a provincial scale in China Type Journal Article
Year 2012 Publication Advances in Space Research Abbreviated Journal Advances in Space Research
Volume 49 Issue 8 Pages 1253-1264
Keywords DMSP/OLS night-time light; Provincial scale; Socio-economic development; Principal component analysis; Poverty index; DMSP-OLS; remote sensing
Abstract All countries around the world and many international bodies, including the United Nations Development Program (UNDP), United Nations Food and Agricultural Organization (FAO), the International Fund for Agricultural Development (IFAD) and the International Labor Organization (ILO), have to eliminate rural poverty. Estimation of regional poverty level is a key issue for making strategies to eradicate poverty. Most of previous studies on regional poverty evaluations are based on statistics collected typically in administrative units. This paper has discussed the deficiencies of traditional studies, and attempted to research regional poverty evaluation issues using 3-year DMSP/OLS night-time light satellite imagery. In this study, we adopted 17 socio-economic indexes to establish an integrated poverty index (IPI) using principal component analysis (PCA), which was proven to provide a good descriptor of poverty levels in 31 regions at a provincial scale in China. We also explored the relationship between DMSP/OLS night-time average light index and the poverty index using regression analysis in SPSS and a good positive linear correlation was modelled, with R2 equal to 0.854. We then looked at provincial poverty problems in China based on this correlation. The research results indicated that the DMSP/OLS night-time light data can assist analysing provincial poverty evaluation issues.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0273-1177 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ john @ Serial 206
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Author (down) Wang, W.; Cao, C.; Bai, Y.; Blonski, S.; Schull, M.
Title Assessment of the NOAA S-NPP VIIRS Geolocation Reprocessing Improvements Type Journal Article
Year 2017 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 9 Issue 10 Pages 974
Keywords Remote Sensing
Abstract Long-term time series analysis requires consistent data records from satellites. The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar orbiting Partner (S-NPP) satellite launched in 2011 requires a major effort to produce consistently calibrated sensor data records (SDR). Accurate VIIRS geolocation products are critical to other VIIRS products and products from other instruments on the S-NPP satellite. This paper presents methods for assessing major improvements to the VIIRS geolocation products in the ongoing National Oceanic and Atmospheric Administration (NOAA)/Center for Satellite Applications and Research (STAR) reprocessing that incorporates all corrections in calibration parameters and SDR algorithms since launch to present. In this study, we analyzed the history of VIIRS geometric calibration parameter updates to identify optimal parameters to account for geolocation errors in the early days of the mission. A sample area located in North Western Africa was selected for validation purposes after analyzing global VIIRS and Landsat control point matching results. Geolocation products over the study region were reprocessed and I-bands/M-bands geolocation improvements were characterized by comparing geolocation errors before and after the reprocessing. Our results indicate that all short-term geolocation anomalies before the latest operational geometric calibration parameter update on 22 August 2013 were effectively minimized after reprocessing, with geolocation errors reduced from −47.1 ± 83.8 m to −23.3 ± 51.1 m (along scan) and from −15.6 ± 43.6 m to −5.9 ± 37.7 m (along track). Terrain correction for the VIIRS Day-Night-Band (DNB) was not implemented in the NOAA operational processing until 22 May 2015. In the reprocessing, it will be implemented to the entire DNB geolocation data record. DNB reprocessing improvement due to this implementation was evaluated using nighttime observations over point sources at sea level and over high altitude. Our results show that the implementation of terrain correction will reduce DNB geolocation errors at off-nadir high elevation locations from up to 9 km to ~0.5 pixel (0.375 km), comparable to those at sea level site. The reprocessed geolocation dataset will be distributed online for end-users to access.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1737
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Author (down) Wang, W., & Cao, C.
Title NOAA-20 VIIRS DNB Aggregation Mode Change: Prelaunch Efforts and On-Orbit Verification/Validation Results Type Journal Article
Year 2019 Publication IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Abbreviated Journal
Volume 12 Issue 7 Pages
Keywords Remote Sensing; Radiometry; Earth; Satellite broadcasting; US Government agencies; Geology; Detectors; VIIRS-DNB
Abstract The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the National Oceanic and Atmospheric Administration-20 (NOAA-20, previously named Joint Polar Satellite System-1 or J1) satellite was successfully launched in late 2017, following six years of a successful operation by its predecessor on the Suomi National Polar-Orbiting Partnership (S-NPP) satellite. NOAA-20 VIIRS day/night band (DNB) adopts a new on-board aggregation option (Op21), which is different from S-NPP DNB (using Op32), to mitigate high non-linearity at high scan angles, observed in its radiometric response during prelaunch test. As a result, NOAA-20 VIIRS DNB has a larger scan angle at the end of scan (∼60.5°) and exhibits a unique feature, i.e., ∼600 km extended Earth view (EV) samples, compared to S-NPP DNB and other VIIRS bands. VIIRS geolocation (GEO) algorithm and geometric calibration parameters were analyzed in-depth and subsequently modified to accommodate the NOAA-20 VIIRS DNB aggregation mode change. The GEO code change was tested using S-NPP data; S-NPP DNB simulated J1 DNB radiance and limited J1 prelaunch test data. After the launch, it was further verified using NOAA-20 VIIRS on-orbit observations. Our results show that the prelaunch VIIRS GEO code change performs well. GEO validation results using nighttime point sources show that NOAA-20 DNB GEO errors are comparable to those for S-NPP DNB over the nominal EV range, with averaged nadir equivalent GEO errors less than 200 m after on-bit updates. Over the extended EV samples (scan angle > 56.06°), the averaged GEO errors are less than 500 m. Moreover, NOAA-20 VIIRS DNB radiometric calibration performance is comparable to S-NPP.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ intern @ Serial 2350
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Author (down) Wang, R.; Wan, B.; Guo, Q.; Hu, M.; Zhou, S.
Title Mapping Regional Urban Extent Using NPP-VIIRS DNB and MODIS NDVI Data Type Journal Article
Year 2017 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 9 Issue 8 Pages 862
Keywords Remote Sensing
Abstract The accurate and timely monitoring of regional urban extent is helpful for analyzing urban sprawl and studying environmental issues related to urbanization. This paper proposes a classification scheme for large-scale urban extent mapping by combining the Day/Night Band of the Visible Infrared Imaging Radiometer Suite on the Suomi National Polar-orbiting Partnership Satellite (NPP-VIIRS DNB) and the Normalized Difference Vegetation Index from the Moderate Resolution Imaging Spectroradiometer products (MODIS NDVI). A Back Propagation (BP) neural network based one-class classification method, the Present-Unlabeled Learning (PUL) algorithm, is employed to classify images into urban and non-urban areas. Experiments are conducted in mainland China (excluding surrounding islands) to detect urban areas in 2012. Results show that the proposed model can successfully map urban area with a kappa of 0.842 on the pixel level. Most of the urban areas are identified with a producer’s accuracy of 79.63%, and only 10.42% the generated urban areas are misclassified with a user’s accuracy of 89.58%. At the city level, among 647 cities, only four county-level cities are omitted. To evaluate the effectiveness of the proposed scheme, three contrastive analyses are conducted: (1) comparing the urban map obtained in this paper with that generated by the Defense Meteorological Satellite Program/Operational Linescan System Nighttime Light Data (DMSP/OLS NLD) and MODIS NDVI and with that extracted from MCD12Q1 in MODIS products; (2) comparing the performance of the integration of NPP-VIIRS DNB and MODIS NDVI with single input data; and (3) comparing the classification method used in this paper (PUL) with a linear method (Large-scale Impervious Surface Index (LISI)). According to our analyses, the proposed classification scheme shows great potential to map regional urban extents in an effective and efficient manner.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1703
Permanent link to this record