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International Journal of Remote Sensing Volume 31, 2010 - Issue 21: Population Estimation Using Remote Sensing and GIS Technologies
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Original Articles

Improving the housing-unit method for small-area population estimation using remote-sensing and GIS information

Chengbin Deng Department of Geography, University of Wisconsin-Milwaukee, P.O. Box 413, Milwaukee, WI, 53201, USA
,
Changshan Wu Department of Geography, University of Wisconsin-Milwaukee, P.O. Box 413, Milwaukee, WI, 53201, USACorrespondence[email protected]
&
Le Wang Department of Geography, State University of New York at Buffalo, Buffalo, NY, 14261, USA
Pages 5673-5688 | Published online: 15 Nov 2010

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Nelson Mileu, Margarida Queirós & Paulo Morgado. (2022) Mapping population distribution from open address data: application to mainland Portugal. Journal of Maps 18:3, pages 585-593.
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Shengyuan Zou & Le Wang. (2020) Individual Vacant House Detection in Very-High-Resolution Remote Sensing Images. Annals of the American Association of Geographers 110:2, pages 449-461.
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Mohammed Alahmadi. (2018) Spatial non-stationarity analysis to estimate dwelling units in Riyadh, Saudi Arabia. European Journal of Remote Sensing 51:1, pages 558-571.
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Lívia Tomás, Leila Fonseca, Cláudia Almeida, Fernando Leonardi & Madalena Pereira. (2016) Urban population estimation based on residential buildings volume using IKONOS-2 images and lidar data. International Journal of Remote Sensing 37:sup1, pages 1-28.
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Menale Wondie, Werner Schneider, Klaus Katzensteiner, Reinfried Mansberger & Demel Teketay. (2016) Modelling the dynamics of landscape transformations and population growth in the highlands of Ethiopia using remote-sensing data. International Journal of Remote Sensing 37:23, pages 5647-5667.
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Longwei Li & Dengsheng Lu. (2016) Mapping population density distribution at multiple scales in Zhejiang Province using Landsat Thematic Mapper and census data. International Journal of Remote Sensing 37:18, pages 4243-4260.
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Chengbin Deng & Changshan Wu. (2013) Improving Small-Area Population Estimation: An Integrated Geographic and Demographic Approach. Annals of the Association of American Geographers 103:5, pages 1123-1141.
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Chaogui Kang, Yu Liu, Xiujun Ma & Lun Wu. (2012) Towards Estimating Urban Population Distributions from Mobile Call Data. Journal of Urban Technology 19:4, pages 3-21.
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Andrey Petrov. (2012) One Hundred Years of Dasymetric Mapping: Back to the Origin. The Cartographic Journal 49:3, pages 256-264.
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Le Wang & Changshan Wu. (2010) Population estimation using remote sensing and GIS technologies. International Journal of Remote Sensing 31:21, pages 5569-5570.
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Yunxiao Gao, Zhanqi Wang & Feng Xu. (2023) Geospatial characteristics and the application of land use functions in the Yangtze River Economic Belt, China: Perspectives on provinces and urban agglomerations. Ecological Indicators 155, pages 110969.
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Yanbi Chen, Zilong Zhang, Lixia Lang, Zhi Long, Ningfei Wang, Xingpeng Chen, Bo Wang & Ya Li. (2023) Measuring the Spatial Match between Service Facilities and Population Distribution: Case of Lanzhou. Land 12:8, pages 1549.
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Elaf A. Alyasiri, James L. Wilson & Ryan D. James. (2022) Estimating the Population of a Middle Eastern City Based on a Normalized Difference Built-Up Index and Urban Morphology. International Journal of Applied Geospatial Research 14:1, pages 1-22.
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Yue Li, Chengmeng Zhang, Yan Tong, Yalu Zhang & Gong Chen. (2022) Prediction of the Old-Age Dependency Ratio in Chinese Cities Using DMSP/OLS Nighttime Light Data. International Journal of Environmental Research and Public Health 19:12, pages 7179.
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Yisheng Peng, Jiahui Liu, Tianyao Zhang & Xiangyang Li. (2021) The Relationship between Urban Population Density Distribution and Land Use in Guangzhou, China: A Spatial Spillover Perspective. International Journal of Environmental Research and Public Health 18:22, pages 12160.
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Xingdong Deng, Yang Liu, Feng Gao, Shunyi Liao, Fan Zhou & Guanfang Cai. (2021) Spatial Distribution and Mechanism of Urban Occupation Mixture in Guangzhou: An Optimized GeoDetector-Based Index to Compare Individual and Interactive Effects. ISPRS International Journal of Geo-Information 10:10, pages 659.
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Shengyuan Zou & Le Wang. (2021) Detecting individual abandoned houses from google street view: A hierarchical deep learning approach. ISPRS Journal of Photogrammetry and Remote Sensing 175, pages 298-310.
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Shuoshuo Shang, Shihong Du, Shouji Du & Shoujie Zhu. (2021) Estimating building-scale population using multi-source spatial data. Cities 111, pages 103002.
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Beata Calka & Elzbieta Bielecka. (2020) GHS-POP Accuracy Assessment: Poland and Portugal Case Study. Remote Sensing 12:7, pages 1105.
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Yi Shi, Junyan Yang & Peiyu Shen. (2020) Revealing the Correlation between Population Density and the Spatial Distribution of Urban Public Service Facilities with Mobile Phone Data. ISPRS International Journal of Geo-Information 9:1, pages 38.
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Chengbin Deng, Xiaoyu Dong, Huihai Wang, Weiying Lin, Hao Wen, John Frazier, Hung Chak Ho & Louisa Holmes. (2020) A Data-Driven Framework for Walkability Measurement with Open Data: A Case Study of Triple Cities, New York. ISPRS International Journal of Geo-Information 9:1, pages 36.
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Zhi Zheng & Guangyuan Zhang. (2020) The Prediction of Finely-Grained Spatiotemporal Relative Human Population Density Distributions in China. IEEE Access 8, pages 181534-181546.
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Jian Gao, Yi-Cheng Zhang & Tao Zhou. (2019) Computational socioeconomics. Physics Reports 817, pages 1-104.
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Jingang Li, Jianwei Li, Yangzi Yuan & Guifang Li. (2019) Spatiotemporal distribution characteristics and mechanism analysis of urban population density: A case of Xi'an, Shaanxi, China. Cities 86, pages 62-70.
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Mingzhu Du, Le Wang, Shengyuan Zou & Chen Shi. (2018) Modeling the Census Tract Level Housing Vacancy Rate with the Jilin1-03 Satellite and Other Geospatial Data. Remote Sensing 10:12, pages 1920.
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Sophie Mossoux, Matthieu Kervyn, Hamid Soulé & Frank Canters. (2018) Mapping Population Distribution from High Resolution Remotely Sensed Imagery in a Data Poor Setting. Remote Sensing 10:9, pages 1409.
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Anna Dmowska & Tomasz F. Stepinski. (2017) A high resolution population grid for the conterminous United States: The 2010 edition. Computers, Environment and Urban Systems 61, pages 13-23.
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Filip Biljecki, Ken Arroyo Ohori, Hugo Ledoux, Ravi Peters & Jantien Stoter. (2016) Population Estimation Using a 3D City Model: A Multi-Scale Country-Wide Study in the Netherlands. PLOS ONE 11:6, pages e0156808.
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Mohammed Alahmadi, Peter M. Atkinson & David Martin. (2016) A Comparison of Small-Area Population Estimation Techniques Using Built-Area and Height Data, Riyadh, Saudi Arabia. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9:5, pages 1959-1969.
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Chengbin Deng. (2015) Integrating multi-source remotely sensed datasets to examine the impact of tree height and pattern information on crimes in Milwaukee, Wisconsin. Applied Geography 65, pages 38-48.
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Chengbin Deng & Junjie Ma. (2015) Viewing urban decay from the sky: A multi-scale analysis of residential vacancy in a shrinking U.S. city. Landscape and Urban Planning 141, pages 88-99.
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Kasper Cockx & Frank Canters. (2015) Incorporating spatial non-stationarity to improve dasymetric mapping of population. Applied Geography 63, pages 220-230.
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Stefan Rayer. 2015. International Encyclopedia of the Social & Behavioral Sciences. International Encyclopedia of the Social & Behavioral Sciences 162 169 .
Shiqian Wang, Wei Li & Jonathan Li. (2014) Using high resolution remote sensing image to help population estimation in small cities. Using high resolution remote sensing image to help population estimation in small cities.
Abraham Akkerman & Shinji Shimoura. (2012) Discrete choice in commuter space: Small area analysis of diurnal population change in the Tokyo Metropolitan Region. Computers, Environment and Urban Systems 36:5, pages 386-397.
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Christian G. Daughton. (2012) Real-time estimation of small-area populations with human biomarkers in sewage. Science of The Total Environment 414, pages 6-21.
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David A. Swanson & Jeff TaymanDavid A. Swanson & Jeff Tayman. 2012. Subnational Population Estimates. Subnational Population Estimates 357 368 .

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