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Adaptive Non-Negative Geographically Weighted Regression for Population Density Estimation Based on Nighttime Light

Hone-Jay Chu, Chen-Han Yang, Chelsea Chou
2019 ISPRS International Journal of Geo-Information  
In this study, geographically weighted regression (GWR) identifies the spatially varying relationships between population density and nighttime lights in mainland China.  ...  The model offers a robust and effective approach for estimating the spatial patterns of regional population density solely on the basis of nighttime light imagery.  ...  Acknowledgments: The authors thank Teng for his valuable comments and suggestions. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijgi8010026 fatcat:jo2etnaq75erhe62gfwttirvfq

An Assessment of Electric Power Consumption Using Random Forest and Transferable Deep Model with Multi-Source Data

Luxiao Cheng, Ruyi Feng, Lizhe Wang, Jining Yan, Dong Liang
2022 Remote Sensing  
Many studies estimate fine-resolution EPC based on the positive correction between stable nighttime light and EPC distribution.  ...  However, EPC is related to various factors other than nighttime light and is spatially non-stationary. Yet this has been ignored in current research.  ...  Similarly, negative outliers processing was conducted on the nighttime light composites data for 2013-2019.  ... 
doi:10.3390/rs14061469 fatcat:fkhewuarovh45p2ipore5esspa

Developing Non-Negative Spatial Autoregressive Models for Better Exploring Relation Between Nighttime Light Images and Land Use Types

Honghan Zheng, Zhipeng Gui, Huayi Wu, Aihong Song
2020 Remote Sensing  
Furthermore, the proposed model and the obtained relationship between nighttime light and land use types can be utilized for other applications of nighttime light images in the population, GDP and carbon  ...  autocorrelation effect of light in adjacent pixels on the central pixel.  ...  For the proposed two non-negative spatial autoregressive models, NSEM and NSLM, the non-negative spatial linear regression model NSL without considering spatial autocorrelation was selected as the baseline  ... 
doi:10.3390/rs12050798 fatcat:cl3izpfrzfhf7k5bd534uneqqy

SUMMER LAND SURFACE TEMPERATURE SMALL-LOCAL VARIATION IN INTRO-URBAN ENVIRONMENT IN EL PASO, TX.pdf

MacTar Mohamed
2020 figshare.com  
this dissertation casts light on an important issue in understanding the effect of built environment, biophysical and demographical factors on the local LST.  ...  The outcomes and methods used in this dissertation will be a beneficial reference for close investigation of local climate in the El Paso urban area in future work.  ...  Geographically Weighted Regression (Gwr) As a modification of traditional regression, Geographically Weighted Regression (GWR) was developed to reach accurate conclusions in local spatial variation which  ... 
doi:10.6084/m9.figshare.13077857.v1 fatcat:w6g4ly2ud5aivakw5quncgtad4

Spatially non-stationary effect of underlying driving factors on surface urban heat islands in global major cities

Long Li, Yong Zha, Jiahua Zhang
2020 International Journal of Applied Earth Observation and Geoinformation  
A R T I C L E I N F O Keywords: surface urban heat island spatial non-stationarity driving factors geographically weighted regression A B S T R A C T Urban heat island (UHI) effect is among the most typical  ...  A geographically weighted regression (GWR) was established to assess the relationships between SUHII and several driving factors, and it further was compared to the ordinary least square (OLS) and stepwise  ...  The weighted regressions were applied to local estimates, and the weights of explanatory variables are the function of the distance from i th pixel.  ... 
doi:10.1016/j.jag.2020.102131 fatcat:aus2fxlrlvduzgymgknsgnsuwm

Rapid Assessment of a Typhoon Disaster Based on NPP-VIIRS DNB Daily Data: The Case of an Urban Agglomeration along Western Taiwan Straits, China

Yuanmao Zheng, Guofan Shao, Lina Tang, Yuanrong He, Xiaorong Wang, Yening Wang, Haowei Wang
2019 Remote Sensing  
The strong correlations were found between NTL image light density and population density (R2 = 0.83) and between the total nighttime light intensity and GDP (R2 = 0.96) at the prefecture level.  ...  Our research explored the methods of rapid identification and extraction of the areas based on changes in nighttime light (NTL) after the typhoon disaster by using a statistical radiation-normalization  ...  Regression model between weighted NTL intensity and population or GDP: (a) Weighted light density versus population density (PD), (b) total weighted light versus total population (TP), (c) total weighted  ... 
doi:10.3390/rs11141709 fatcat:mvyxidgygbg6dpnullkmngjise

Using Nighttime Satellite Imagery as a Proxy Measure of Human Well-Being

Tilottama Ghosh, Sharolyn Anderson, Christopher Elvidge, Paul Sutton
2013 Sustainability  
Estimates of different aspects of human well-being, such as Gross Domestic Product, or percentage of population with access to electric power, or measuring the distribution of income in society are often  ...  Improving human well-being is increasingly recognized as essential for movement toward a sustainable and desirable future.  ...  For estimating the population in poverty, a calibration was developed based on the poverty line data available from the World Development Indicators (WDI) 2006 national level estimates.  ... 
doi:10.3390/su5124988 fatcat:n6iha5y7ejfmniptn57fn4wmpy

Modeling Population Density using a New Index Derived from Multi-Sensor Image Data

Luo, Zhang, Cheng, Sun
2019 Remote Sensing  
Using the nighttime light (NTL) imagery for population estimation has been a topic of interest in recent decades.  ...  A statistical model is developed to predict 250m grid-level population density based on the proposed VTLPI and the least square regression approach.  ...  Modeling of Population Density based on VTLPI Based on the proposed VTLPI index, two least square regression (LSR) models for estimating county-level population density at region A and region B are created  ... 
doi:10.3390/rs11222620 fatcat:imihzc6565afhoxjkp5nqxy6n4

Regional inequality, convergence, and its determinants – A view from outer space

Christian Lessmann, André Seidel
2017 European Economic Review  
Abstract This paper provides a new data set of regional income inequalities within countries based on satellite nighttime light data.  ...  We subsequently use our estimation results for an out-ofsample prediction of regional incomes based on the luminosity data, which allows us to investigate regional income differentials in developing countries  ...  The key innovation of our study is the prediction of regional inequality based on satellite nighttime light data.  ... 
doi:10.1016/j.euroecorev.2016.11.009 fatcat:tcivb5mu2fczdjertj4bukfpxy

A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery [article]

Esther Rolf, Jonathan Proctor, Tamma Carleton, Ian Bolliger, Vaishaal Shankar, Miyabi Ishihara, Benjamin Recht, Solomon Hsiang
2020 arXiv   pre-print
Combining satellite imagery with machine learning (SIML) has the potential to address global challenges by remotely estimating socioeconomic and environmental conditions in data-poor regions, yet the resource  ...  Since image encodings are shared across tasks, they can be centrally computed and distributed to unlimited researchers, who need only fit a linear regression to their own ground truth data in order to  ...  All scatterplots indicate regression weights for forest cover, elevation and/or population density.  ... 
arXiv:2010.08168v1 fatcat:pdxqlxejabdabbqozgdrcjwt7e

Predictive Risk Mapping of Schistosomiasis in Madagascar Using Ecological Niche Modeling and Precision Mapping

Mark A. Deka
2022 Tropical Medicine and Infectious Disease  
The results show that suitability for schistosomiasis is widespread and covers 264,781 sq kilometers (102,232 sq miles).  ...  This study provides valuable insight into the geography of schistosomiasis in Madagascar and its potential risk to human populations.  ...  The estimated weighted sum of predictions (weighted mean) (B). Model uncertainty based on the coefficient of variation (CV).  ... 
doi:10.3390/tropicalmed7020015 pmid:35202211 pmcid:PMC8876685 fatcat:kxri6xcgvzhvdbactbuigdxy4a

Spatiotemporal Distribution of U5MR and Their Relationship with Geographic and Socioeconomic Factors in China

Zeng Li, Jingying Fu, Dong Jiang, Gang Lin, Donglin Dong, Xiaoxi Yan
2017 International Journal of Environmental Research and Public Health  
geographically weighted regression (GWR) model.  ...  Nighttime lights (NL) and the digital elevation model (DEM) both have obvious influences on the U5MR, with the NL having a negative impact and DEM having a positive impact.  ...  The estimated U5MR data, gridded nighttime lights (NL) data and gridded digital elevation model (DEM) for the period from 2001 to 2010 were used in the analysis.  ... 
doi:10.3390/ijerph14111428 pmid:29160829 pmcid:PMC5708067 fatcat:rrvevtiqzrbufppt6mntoo34sq

Urban warming inverse contribution on risk of dengue transmission in the southeastern North America [article]

Lorena M. Simon, Jesus N. Pinto-Ledezma, Robert R. Dunn, Thiago F. Rangel
2020 bioRxiv   pre-print
Instead, non-urban areas would be a better focus for dengue hazards into the southern United States.  ...  Instead, the surrounding non-urban temperature was rather suitable for the expected mosquitos' transmission potential.  ...  Figure 4 4 Aedes albopictus (a) and Aedes aegypti (b) spatial density estimation based on Kernel smooth approach of available occurrence records.  ... 
doi:10.1101/2020.01.15.908020 fatcat:mzr5gsiaofb2bdjjqpomqgbuna

Assessment and Improvement of Urban Resilience to Flooding at a Subdistrict Level Using Multi-Source Geospatial Data: Jakarta as a Case Study

Hui Zhang, Xiaoqian Liu, Yingkai Xie, Qiang Gou, Rongrong Li, Yanqing Qiu, Yueming Hu, Bo Huang
2022 Remote Sensing  
Topographic factors, such as elevation (coefficient = 0.3784) and slope (coefficient = 0.1079), were found to have the strongest positive influence on flood recovery, whereas population density (coefficient  ...  The resilience of 42 subdistricts in Jakarta, with their gross domestic product data super-resolved using nighttime-light satellite images, was assessed.  ...  would like to thank Baidu Maps, Badan Penanggulangan Bencana Daerah Provinsi DKI Jakarta, Google Earth Engine, Tsinghua University, the National Oceanic and Atmospheric Administration, and OpenStreetMap for  ... 
doi:10.3390/rs14092010 fatcat:a4vt3b2wwvcv5e5tebubfl74yy

Seasonal and Diurnal Variations in the Relationships between Urban Form and the Urban Heat Island Effect

Ze Liang, Yueyao Wang, Jiao Huang, Feili Wei, Shuyao Wu, Jiashu Shen, Fuyue Sun, Shuangcheng Li
2020 Energies  
The impacts of urban geometric factors and population density in summer, particularly those during the daytime, are significantly larger than those in winter.  ...  To address this deficiency, we conducted an empirical study based on data from 150 cities in the Jing-Jin-Ji region of China from 2000 to 2015.  ...  For instance, based on the use of LCZ, Yang et al.  ... 
doi:10.3390/en13225909 fatcat:kwikqz7ltfgmhnivfgfu4jculi
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