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Temporal variations of artificial nighttime lights and their implications for urbanization in the conterminous United States, 2013–2017
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/2014ef000285openalex-snapshot
Holidays in lights: Tracking cultural patterns in demand for energy services
inferredcites →https://doi.org/10.1016/j.cageo.2004.05.006openalex-snapshot
TIMESAT—a program for analyzing time-series of satellite sensor data
inferredcites →https://doi.org/10.1016/j.cageo.2009.01.009openalex-snapshot
A global poverty map derived from satellite data
inferredcites →https://doi.org/10.1016/j.energy.2016.01.058openalex-snapshot
Detecting urban-scale dynamics of electricity consumption at Chinese cities using time-series DMSP-OLS (Defense Meteorological Satellite Program-Operational Linescan System) nighttime light imageries
inferredcites →https://doi.org/10.1016/j.isprsjprs.2017.03.003openalex-snapshot
Spatiotemporally enhancing time-series DMSP/OLS nighttime light imagery for assessing large-scale urban dynamics
inferredcites →https://doi.org/10.1016/j.jshs.2016.07.007openalex-snapshot
The impact of weather on summer and winter exercise behaviors
inferredcites →https://doi.org/10.1016/j.landurbplan.2012.02.013openalex-snapshot
Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008
inferredcites →https://doi.org/10.1016/j.landurbplan.2015.02.017openalex-snapshot
Urban land density function: A new method to characterize urban expansion
inferredcites →https://doi.org/10.1016/j.puhe.2007.04.009openalex-snapshot
The effect of season and weather on physical activity: A systematic review
inferredcites →https://doi.org/10.1016/j.rse.2004.03.014openalex-snapshot
A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter
inferredcites →https://doi.org/10.1016/j.rse.2009.02.004openalex-snapshot
Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods
inferredcites →https://doi.org/10.1016/j.rse.2009.08.014openalex-snapshot
Detecting trend and seasonal changes in satellite image time series
inferredcites →https://doi.org/10.1016/j.rse.2010.02.018openalex-snapshot
Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat Imagery Change Detection Methods
inferredcites →https://doi.org/10.1016/j.rse.2010.03.003openalex-snapshot
Mapping global urban areas using MODIS 500-m data: New methods and datasets based on ‘urban ecoregions’
inferredcites →https://doi.org/10.1016/j.rse.2010.07.008openalex-snapshot
Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms
inferredcites →https://doi.org/10.1016/j.rse.2011.04.032openalex-snapshot
Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data
inferredcites →https://doi.org/10.1016/j.rse.2012.04.018openalex-snapshot
Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: A comparative case study from China's cities
inferredcites →https://doi.org/10.1016/j.rse.2012.06.006openalex-snapshot
Monitoring land cover change in urban and peri-urban areas using dense time stacks of Landsat satellite data and a data mining approach
inferredcites →https://doi.org/10.1016/j.rse.2012.10.022openalex-snapshot
The Vegetation Adjusted NTL Urban Index: A new approach to reduce saturation and increase variation in nighttime luminosity
inferredcites →https://doi.org/10.1016/j.rse.2014.01.011openalex-snapshot
Continuous change detection and classification of land cover using all available Landsat data
inferredcites →https://doi.org/10.1016/j.rse.2014.02.015openalex-snapshot
Good practices for estimating area and assessing accuracy of land change
inferredcites →https://doi.org/10.1016/j.rse.2014.03.004openalex-snapshot
A cluster-based method to map urban area from DMSP/OLS nightlights
inferredcites →https://doi.org/10.1016/j.rse.2014.09.023openalex-snapshot
Detecting change in urban areas at continental scales with MODIS data
inferredcites →https://doi.org/10.1016/j.rse.2014.11.022openalex-snapshot
Night-time light derived estimation of spatio-temporal characteristics of urbanization dynamics using DMSP/OLS satellite data
inferredcites →https://doi.org/10.1016/j.rse.2015.12.027openalex-snapshot
Characterizing the magnitude, timing and duration of urban growth from time series of Landsat-based estimates of impervious cover
inferredcites →https://doi.org/10.1016/j.rse.2015.12.042openalex-snapshot
Mapping sub-pixel urban expansion in China using MODIS and DMSP/OLS nighttime lights
inferredcites →https://doi.org/10.1016/j.rse.2016.10.002openalex-snapshot
Updating urban extents with nighttime light imagery by using an object-based thresholding method
inferredcites →https://doi.org/10.1016/j.rse.2016.12.026openalex-snapshot
Thematic accuracy assessment of the 2011 National Land Cover Database (NLCD)
inferredcites →https://doi.org/10.1016/j.rse.2017.01.006openalex-snapshot
A global analysis of factors controlling VIIRS nighttime light levels from densely populated areas
inferredcites →https://doi.org/10.1016/j.rse.2017.03.003openalex-snapshot
The impact of seasonal changes on observed nighttime brightness from 2014 to 2015 monthly VIIRS DNB composites
inferredcites →https://doi.org/10.1016/j.rse.2018.03.017openalex-snapshot
NASA's Black Marble nighttime lights product suite
inferredcites →https://doi.org/10.1016/j.rse.2018.07.030openalex-snapshot
Mapping annual urban dynamics (1985–2015) using time series of Landsat data
inferredcites →https://doi.org/10.1016/j.rse.2018.10.015openalex-snapshot
A global record of annual urban dynamics (1992–2013) from nighttime lights
inferredcites →https://doi.org/10.1016/s0099-1112(15)30100-2openalex-snapshot
Completion of the 2011 National Land Cover Database for the Conterminous United States – Representing a Decade of Land Cover Change Information
inferredcites →https://doi.org/10.1016/s0924-2716(01)00040-5openalex-snapshot
Night-time lights of the world: 1994–1995
inferredcites →https://doi.org/10.1021/ac60214a047openalex-snapshot
Smoothing and Differentiation of Data by Simplified Least Squares Procedures.
inferredcites →https://doi.org/10.1021/acs.est.5b02471openalex-snapshot
Generating the Nighttime Light of the Human Settlements by Identifying Periodic Components from DMSP/OLS Satellite Imagery
inferredcites →https://doi.org/10.1038/srep03789openalex-snapshot
Contrasting trends in light pollution across Europe based on satellite observed night time lights
inferredcites →https://doi.org/10.1080/01431160304982openalex-snapshot
Validation of urban boundaries derived from global night-time satellite imagery
inferredcites →https://doi.org/10.1080/01431161.2013.820365openalex-snapshot
Intercalibration of DMSP-OLS night-time light data by the invariant region method
inferredcites →https://doi.org/10.1080/01431161.2014.971469openalex-snapshot
Can night-time light images play a role in evaluating the Syrian Crisis?
inferredcites →https://doi.org/10.1080/01431161.2015.1059968openalex-snapshot
Detecting 2014 Northern Iraq Insurgency using night-time light imagery
inferredcites →https://doi.org/10.1080/01431161.2015.1073861openalex-snapshot
An improved method of night-time light saturation reduction based on EVI
inferredcites →https://doi.org/10.1080/01431161.2017.1342050openalex-snapshot
VIIRS night-time lights
inferredcites →https://doi.org/10.1080/014311697218485openalex-snapshot
Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption
inferredcites →https://doi.org/10.1109/tgrs.2011.2178031openalex-snapshot
A Saturated Light Correction Method for DMSP/OLS Nighttime Satellite Imagery
inferredcites →https://doi.org/10.1109/tgrs.2016.2572724openalex-snapshot
A Robust Method to Generate a Consistent Time Series From DMSP/OLS Nighttime Light Data
inferredcites →https://doi.org/10.14358/pers.69.12.1377openalex-snapshot
Mapping Urban Areas by Fusing Multiple Sources of Coarse Resolution Remotely Sensed Data
inferredcites →https://doi.org/10.2747/1548-1603.45.2.131openalex-snapshot
Population Estimation Using Geographically Weighted Regression
inferredcites →https://doi.org/10.30536/j.ijreses.2004.v1.a1326openalex-snapshot
PROGRESS FOR STABLE ARTIFICIAL LIGHTS DISTRIBUTION EXTRVCTION ACCURACY AND ESTIMATION OF ELECTRIC] POWER CONSUMPTION BY MEANS OF DMSP/OLS NIGHTTIME IMAGERY
inferredcites →https://doi.org/10.3390/en20300595openalex-snapshot
A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Monitoring Turkey’s nighttime light and environmental change
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Measuring Dhaka’s Urban Transformation Using Nighttime Light Data
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Monitoring the Trend of Nighttime Light Pollution (NLP) in the Chattogram District, Bangladesh, Using DMSP/OLS and VIIRS Data
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New nighttime light landscape metrics for analyzing urban-rural differentiation in economic development at township: A case study of Fujian province, China
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Quantifying spatiotemporal patterns of shrinking cities in urbanizing China: A novel approach based on time-series nighttime light data
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Developing a new cross-sensor calibration model for DMSP-OLS and Suomi-NPP VIIRS night-light imageries
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Characterizing urban land changes of 30 global megacities using nighttime light time series stacks
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2023.05.028openalex-snapshot
Nighttime light remote sensing for urban applications: Progress, challenges, and prospects
inferred← citeshttps://doi.org/10.1016/j.jag.2021.102339openalex-snapshot
Estimation of pixel-level seismic vulnerability of the building environment based on mid-resolution optical remote sensing images
inferred← citeshttps://doi.org/10.1016/j.jag.2023.103484openalex-snapshot
Spatial heterogeneity of uncertainties in daily satellite nighttime light time series
inferred← citeshttps://doi.org/10.1016/j.jclepro.2022.135608openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jqsrt.2019.106648openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.rse.2020.111739openalex-snapshot
A systematic review and assessment of algorithms to detect, characterize, and monitor urban land change
inferred← citeshttps://doi.org/10.1016/j.rse.2020.111980openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.rse.2022.113016openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.rse.2022.113269openalex-snapshot
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Urban Spatial Development Based on Multisource Data Analysis: A Case Study of Xianyang City’s Integration into Xi’an International Metropolis
inferred← citeshttps://doi.org/10.3390/su14127236openalex-snapshot
Spatiotemporal Evolution and Coupling Pattern Analysis of Urbanization and Ecological Environmental Quality of the Chinese Loess Plateau
inferred← citeshttps://doi.org/10.5194/essd-13-5689-2021openalex-snapshot
Landsat-based Irrigation Dataset (LANID): 30 m resolution maps of irrigation distribution, frequency, and change for the US, 1997–2017
inferred← citeshttps://doi.org/10.62320/jfbr.v2i1.18openalex-snapshot
What do people think about the environmental, social, and economic impacts of the wood pellet industry? An exploratory study of residents living near pellet plants vs. urban residents in states with pellet manufacturers
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.