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E-grāmata: Remote Sensing of Night-time Light

Edited by (Wuhan University, CHINA), Edited by , Edited by (Iowa State University, USA), Edited by , Edited by
  • Formāts: 310 pages
  • Izdošanas datums: 09-Aug-2021
  • Izdevniecība: Routledge
  • Valoda: eng
  • ISBN-13: 9781000431063
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  • Formāts: 310 pages
  • Izdošanas datums: 09-Aug-2021
  • Izdevniecība: Routledge
  • Valoda: eng
  • ISBN-13: 9781000431063

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Satellite images acquired at night provide a visually arresting perspective of the Earth and the human activities that light up the otherwise mostly dark Earth. These night-time light satellite images can be compiled into a geospatial time series that represent an invaluable source of information for both the natural and social sciences. Night-time light remote sensing has been shown to be particularly useful for a range of natural science and social science applications, including studies relating to urban development, demography, sociology, fishing activity, light pollution and the consequences of civil war. Key sensors for these time-series include the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) and the Suomi National Polar-orbiting Partnership Satellite’s Visible Infrared Imaging Radiometer Suite Day/Night Band (Suomi NPP/VIIRS DNB). An increasing number of alternative sources are also available, including high spatial resolution and multispectral sensors.

This book captures key methodological issues associated with pre-processing night-time light data, documents state of the art analysis methods, and explores a wide range of applications. Major sections focus on NPP/VIIRS DNB processing; inter-calibration between NPP/VIIRS and DMPS/OLS; applications associated with socio-economic activities, applications in monitoring urbanization; and fishing activity monitoring.

The chapters in this book were originally published as a special issue of the International Journal of Remote Sensing.



This book captures key methodological issues associated with pre-processing night-time light data, documents state of the art analysis methods, and explores a wide range of applications.

Preface: Remote sensing of night-time light

Xi Li, Christopher Elvidge, Yuyu Zhou, Changyong Cao and Timothy A. Warner

1. VIIRS nighttime lights

Christopher D Elvidge, Kimberly Baugh, Mikhail Zhizhin, Feng Chi Hsu and
Tilottama Ghosh

2. Assessment of straylight correction performance for the VIIRS day/night
band using Dome-C and Greenland under lunar illumination

Shi Qiu, Xi Shao, Chang Yong Cao, Sirish Uprety and Wen Hui Wang

3. Improving accuracy of economic estimations with VIIRS DNB image products

Naizhuo Zhao, Feng-Chi Hsu, Guofeng Cao and Eric L. Samson

4. A new multichannel threshold algorithm based on radiative transfer
characteristics for detecting fog/ low stratus using night-time NPP/VIIRS
data.

Shensen Hu, Shuo Ma, Wei Yan, Jun Jiang and Yunxian Huang

5. Intercalibration between DMSP/OLS and VIIRS night-time light images to
evaluate city light dynamics of Syrias major human settlement during Syrian
Civil War

Xi Li, Deren Li, Huimin Xu and Chuanqing Wu

6. Outdoor light and breast cancer incidence: a comparative analysis of DMSP
and VIIRS-DNB satellite data

Nataliya A. Rybnikova and Boris A. Portnov

7. Using multitemporal night-time lights data to compare regional development
in Russia and China, 19922012

Mia M. Bennett and Laurence C. Smith

8. The short-term economic impact of tropical Cyclone Pam: an analysis using
VIIRS nightlight satellite imagery

Preeya Mohan and Eric Strobl

9. Port economics comprehensive scores for major cities in the Yangtze
Valley, China using the DMSPOLS night-time light imagery

Chang Li, Guangping Chen, Jing Luo, Shice Li and Jia Ye

10. Urban mapping using DMSP/OLS stable night-time light: a review

Xuecao Li and Yuyu Zhou

11. Analysis of urbanization dynamics in mainland China using pixel-based
night-time light trajectories from 1992 to 2013

Yang Ju, Iryna Dronova, Qin Ma and Xiang Zhang

12. Assessing urban growth dynamics of major Southeast Asian cities using
Night-Time Light data

Shankar Acharya Kamarajugedda, Pradeep V Mandapaka and Edmond Y.M Lo

13. A Novel Method for Urban Area Extraction from VIIRS DNB and MODIS NDVI
Data: A Case Study of Chinese Cities

Qiao Zhang, Ping Wang, Hui Chen, Qinglun Huang, Hongbing Jiang, Zijian Zhang,
Yanmei Zhang, Xiang Luo and Shujuan Sun

14. Monitoring urban expansion using time series of night-time light data: a
case study in Wuhan, China

Xin Xin, Bin Liu, Kaichang Di, Zhe Zhu, Zhongyuan Zhao, Jia Liu, Zongyu Yue
and Guo Zhang

15. Predicting potential fishing zones of Japanese common squid (Todarodes
pacificus) using remotely sensed images in coastal waters of south-western
Hokkaido, Japan

Xun Zhang, Sei-Ichi Saitoh and Toru Hirawake
Christopher D. Elvidge pioneered the development of global satellite derived night-time lights and led the production of a twenty-one year time series of global DMSP night-time lights (19922013). Elvidge was instrumental in establishing the DMSP digital archive at NOAA and led the media migration that rescued the digital records from aging tapes. He developed the VIIRS nightfire (VNF) product, methods for discriminating flaming and smoldering combustion using night-time Landsat data, and developed a night-time boat detection product for VIIRS.

Xi Li is Associate Professor at State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University. He earned a Ph.D. in Photogrammetry and Remote Sensing at Wuhan University in 2009. His research interests include physical modeling of night-time light as well as night-time light remote sensing applications. He serves as an editorial board member of the International Journal of Remote Sensing and an international consultant for Asian Development Bank.

Yuyu Zhou is Associate Professor at the Department of Geological & Atmospheric Sciences, Iowa State University. His research focus has always been in quantifying spatiotemporal patterns of environmental change and developing modeling mechanisms to bridge the driving forces and consequences of environmental change so that the impacts of human activities on the environment can be effectively measured, modeled and evaluated.

Changyong Cao is the Chief for the satellite calibration and data assimilation branch at the NOAA Center for Satellite Applications and Research (STAR). He oversees the calibration and validation of satellite radiometers on NOAA polar- orbiting and geostationary satellites. He is also the science team lead for the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument with a research interest on VIIRS on- orbit performance for a variety of applications including night- time lights.

Timothy A. Warner is Emeritus Professor of Geology and Geography at West Virginia University. He served as editor in chief of the International Journal of Remote Sensing from 2014 to 2020. He is a Fellow of the American Society of Photogrammetry and Remote Sensing.