Understanding the Spatiotemporal Development of Human Settlement in Hurricane-Prone Areas on the Us Atlantic and Gulf Coasts Using Nighttime Remote Sensing

Hurricanes, as one of the most devastating natural hazards, have posed a great threat to people in coastal areas. A better understanding of the spatiotemporal dynamics of human settlement in hurricane-prone areas largely benefits sustainable development. This study uses the nighttime light (NTL) data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) to examine human settlement development in areas with different levels of hurricane proneness from 1992 to 2013. The DMSP/OLS NTL data from six satellites were intercalibrated and desaturated with the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) optical imagery to derive the Vegetation Adjusted NTL Urban Index (VANUI), a popular index that quantifies human settlement intensity. The derived VANUI time series was examined with the Mann– Kendall test and Theil–Sen test to identify significant spatiotemporal trends. To link the VANUI product to hurricane impacts, four hurricane-prone zones were extracted to represent different levels of hurricane proneness. Aside from geographic division, a wind-speed-weighted track density function was developed and applied to historical storm tracks which originated in the North Atlantic Basin to better categorize the four levels of hurricane proneness. Spatiotemporal patterns of human settlement in the four zones were finally analyzed. The results clearly exhibit a north–south and inland–coastal discrepancy of human settlement dynamics. This study also reveals that both the zonal extent and zonal increase rate of human settlement positively correlate with hurricane proneness levels. The intensified human settlement in high hurricane-exposure zones deserves further attention for coastal resilience

Understanding the Spatiotemporal Development of Human Settlement in Hurricane-Prone Areas on the US Atlantic and Gulf Coasts Using Nighttime Remote Sensing

Hurricanes, as one of the most devastating natural hazards, have posed a great threat to people in coastal areas. A better understanding of the spatiotemporal dynamics of human settlement in hurricane-prone areas largely benefits sustainable development. This study uses the nighttime light (NTL) data from the Defense Meteorological Satellite Program\u27s Operational Linescan System (DMSP/OLS) to examine human settlement development in areas with different levels of hurricane proneness from 1992 to 2013. The DMSP/OLS NTL data from six satellites were intercalibrated and desaturated with the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) optical imagery to derive the Vegetation Adjusted NTL Urban Index (VANUI), a popular index that quantifies human settlement intensity. The derived VANUI time series was examined with the Mann–Kendall test and Theil–Sen test to identify significant spatiotemporal trends. To link the VANUI product to hurricane impacts, four hurricane-prone zones were extracted to represent different levels of hurricane proneness. Aside from geographic division, a wind-speed-weighted track density function was developed and applied to historical storm tracks which originated in the North Atlantic Basin to better categorize the four levels of hurricane proneness. Spatiotemporal patterns of human settlement in the four zones were finally analyzed. The results clearly exhibit a north–south and inland–coastal discrepancy of human settlement dynamics. This study also reveals that both the zonal extent and zonal increase rate of human settlement positively correlate with hurricane proneness levels. The intensified human settlement in high hurricane-exposure zones deserves further attention for coastal resilience

Application of DMSP/OLS nighttime light images : a meta-analysis and a systematic literature review

© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 6 (2014): 6844-6866, doi:10.3390/rs6086844.Since the release of the digital archives of Defense Meteorological Satellite Program Operational Line Scanner (DMSP/OLS) nighttime light data in 1992, a variety of datasets based on this database have been produced and applied to monitor and analyze human activities and natural phenomena. However, differences among these datasets and how they have been applied may potentially confuse researchers working with these data. In this paper, we review the ways in which data from DMSP/OLS nighttime light images have been applied over the past two decades, focusing on differences in data processing, research trends, and the methods used among the different application areas. Five main datasets extracted from this database have led to many studies in various research areas over the last 20 years, and each dataset has its own strengths and limitations. The number of publications based on this database and the diversity of authors and institutions involved have shown promising growth. In addition, researchers have accumulated vast experience retrieving data on the spatial and temporal dynamics of settlement, demographics, and socioeconomic parameters, which are “hotspot” applications in this field. Researchers continue to develop novel ways to extract more information from the DMSP/OLS database and apply the data to interdisciplinary research topics. We believe that DMSP/OLS nighttime light data will play an important role in monitoring and analyzing human activities and natural phenomena from space in the future, particularly over the long term. A transparent platform that encourages data sharing, communication, and discussion of extraction methods and synthesis activities will benefit researchers as well as public and political stakeholders.This work is supported by the 111 project “Hazard and Risk Science Base at Beijing Normal University” under Grant B08008 (Ministry of Education and State Administration of Foreign Experts Affairs, PRC), the State Key Laboratory of Earth Surface Processes and Resource Ecology of Beijing Normal University (No. 2013-RC-03), and the Fundamental Research Funds for the Central Universities (Grant No. 201413037)

FORECASTING URBAN EXPANSION BASED ON NIGHT LIGHTS

Forecasting urban expansion models are a very powerful tool in the hands of urban planners in order to anticipate and mitigate future urbanization pressures. In this paper, a linear regression forecasting urban expansion model is implemented based on the annual composite night lights time series available from National Oceanic and Atmospheric Administration (NOAA). The product known as 'stable lights' is used in particular, after it has been corrected with a standard intercalibration process to reduce artificial year-to-year fluctuations as much as possible. Forecasting is done for ten years after the end of the time series. Because the method is spatially explicit the predicted expansion trends are relatively accurately mapped. Two metrics are used to validate the process. The first one is the year-to-year Sum of Lights (SoL) variation. The second is the year-to-year image correlation coefficient. Overall it is evident that the method is able to provide an insight on future urbanization pressures in order to be taken into account in planning. The trends are quantified in a clear spatial manner

The urbanization impact in China: A prospective model (1992-2025)

The gradual spread of urbanization, the phenomenon known under the term urban sprawl, has become one of the paradigms that have characterized the urban development since the second half of the twentieth century and early twenty-first century. The arrival of electrification to nearly every corner of the planet is certainly the first and more meaningful indicator of artificialization of land. In this sense, the paper proposes a new methodology designed to identify the highly impacted landscapes in China based on the analysis of the satellite image of nighttime lights. The night-lights have been used widespread in scientific contributions, from building human development indices, identifying megalopolis or analyzing the phenomenon of urbanization and sprawl, but generally they have not been used to forecast the urbanization in the near future. This paper proposes to study the urbanization impact in China between 1992 and 2013, and models a hypothesis of future scenarios of urbanization (2013-2025). For this purpose, the paper uses DMSP-OLS Nighttime Lights (1992 – 2013). After obtaining a homogeneous series for the whole period 1992- 2013, we proceed to model the spatial dynamics of past urbanization process using thePeer ReviewedPostprint (published version

First Estimation of Global Trends in Nocturnal Power Emissions Reveals Acceleration of Light Pollution

This is the final version. Available on open access from MDPI via the DOI in this recordData Availability Statement: All raw data used (DMSP-OLS and VIIRS) are already in the public domain on several platforms like for example Google Earth Engine (https://earthengine.google.com/). The data presented in this research are openly available in https://doi.org/10.5281/zenodo.5205656.The global spread of artificial light is eroding the natural night-time environment. The estimation of the pattern and rate of growth of light pollution on multi-decadal scales has nonetheless proven challenging. Here we show that the power of global satellite observable light emissions increased from 1992 to 2017 by at least 49%. We estimate the hidden impact of the transition to solid-state light-emitting diode (LED) technology, which increases emissions at visible wavelengths undetectable to existing satellite sensors, suggesting that the true increase in radiance in the visible spectrum may be as high as globally 270% and 400% on specific regions. These dynamics vary by region, but there is limited evidence that advances in lighting technology have led to decreased emissions

Artificially lit surface of Earth at night increasing in radiance and extent

This is the author accepted manuscript. The final version is available from AAAS via the DOI in this record.A central aim of the “lighting revolution” (the transition to solid-state lighting technology) is decreased energy consumption. This could be undermined by a rebound effect of increased use in response to lowered cost of light. We use the first-ever calibrated satellite radiometer designed for night lights to show that from 2012 to 2016, Earth’s artificially lit outdoor area grew by 2.2% per year, with a total radiance growth of 1.8% per year. Continuously lit areas brightened at a rate of 2.2% per year. Large differences in national growth rates were observed, with lighting remaining stable or decreasing in only a few countries. These data are not consistent with global scale energy reductions but rather indicate increased light pollution, with corresponding negative consequences for flora, fauna, and human well-being.This article is based upon work from COST Action ES1204 LoNNe, supported by COST (European Cooperation in Science and Technology). The authors acknowledge the funding received by ERA-PLANET (www.era-planet.eu) funded by the EC as part of H2020 (contract no. 689443). NOAA’s participation was funded by NASA’s VIIRS science program, contract number NNH15AZ01I. ASM’s contribution was funded by ORISON project (H2020-INFRASUPP-2015-2) Cities at Night

The nature of the diffuse light near cities detected in nighttime satellite imagery

Open Access.-- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Diffuse glow has been observed around brightly lit cities in nighttime satellite imagery since at least the first publication of large scale maps in the late 1990s. In the literature, this has often been assumed to be an error related to the sensor, and referred to as "blooming", presumably in relation to the effect that can occur when using a CCD to photograph a bright light source. Here we show that the effect seen on the DMSP/OLS, SNPP/VIIRS-DNB and ISS is not only instrumental, but in fact represents a real detection of light scattered by the atmosphere. Data from the Universidad Complutense Madrid sky brightness survey are compared to nighttime imagery from multiple sensors with differing spatial resolutions, and found to be strongly correlated. These results suggest that it should be possible for a future space-based imaging radiometer to monitor changes in the diffuse artificial skyglow of cities.© 2020, The Author(s).Tis work was supported by the EMISSI@N project (NERC grant NE/P01156X/1), COST (European Cooperation in Science and Technology) Action ES1204 LoNNe (Loss of the Night Network), the ORISON project (H2020- INFRASUPP-2015-2), the Cities at Night project, the European Union’s Horizon 2020 research and innovation programme under grant agreement no 689443 via project GEOEssential, FPU grant from the Ministerio de Ciencia y Tecnologia and F. Sánchez de Miguel. We acknowledge the support of the Spanish Network for Light Pollution Studies (MINECO AYA2011-15808-E) and also from STARS4ALL, a project funded by the European Union H2020-ICT-2015-688135. This work has been partially funded by the Spanish MICINN (AYA2016- 75808-R), and by the Madrid Regional Government through the TEC2SPACE-CM Project (P2018/NMT-4291). Te ISS images are courtesy of the Earth Science and Remote Sensing Unit, NASA Johnson Space Center. CCMK acknowledges the funding received through the European Union’s Horizon 2020 research and innovation programme ERA-PLANET, grant agreement no. 689443, via the GEOEssential project, and funding from the Helmholtz Association Initiative and Networking Fund under grant ERC-RA-0031. We thank J. Coesfeld for producing Fig. 1. We thank the organizers of the LPTMM 2013 conference for providing a stimulating forum in which we discussed the nature of the difuse light around cities in detail. Tanks to Emma R. Howard for her help in the editing of this article.Peer reviewe

SPATIOTEMPORAL EVOLUTION OF THE IMBALANCED REGIONAL DEVELOPMENT IN MAINLAND CHINA USING DMSP-OLS DATA

The Defense Meteorological Satellite Programs Operational Linescan System (DMSP-OLS) nighttime lights imagery has been widely used to monitor economic activities and regional development in recent decades. In this paper, we firstly processed the nighttime light imageries of the Mainland China from 1992 to 2013 due to the radiation or geometric errors. Secondly, by dividing the Mainland China into seven regions, we found high correlation between the sum light values and GDP of each region. Thirdly, we extracted the economic centers of each region based on their nighttime light images. Through the analysis, we found the distribution of these economic centers was relatively concentrated and the migration of these economic centers showed certain directional trend or circuitous changes, which suggested the imbalanced socio-economic development of each region. Then, we calculated the Regional Development Gini of each region using the nighttime light data, which indicated that social-economic development in South China presents great imbalance while it is relatively balanced in Southwest China. This study would benefit the macroeconomic control to regional economic development and the introduction of appropriate economic policies from the national level