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dc.contributorPeter Rogersonen_US
dc.contributorThomas J. Baerwald Program Manageren_US
dc.contributor.authorLe Wang Principal Investigatoren_US
dc.datestart 08/01/2008en_US
dc.dateexpiration 01/31/2013en_US
dc.date.accessioned2014-04-02T18:25:17Z
dc.date.available2014-04-02T18:25:17Z
dc.date.issued2014-04-02
dc.identifier0822489en_US
dc.identifier.urihttp://hdl.handle.net/10477/23672
dc.descriptionGrant Amount: $ 154641en_US
dc.description.abstractSmall-area population estimates are essential for understanding and responding to many social, political, economic, and environmental problems. The size and distribution of the population often are key determinants for resource allocation for state and local governments. In the United States, detailed population data are only available for one date per decade through the national census. This frequency often does not meet the needs of rapid growth areas like Austin, Texas where noteworthy local inter-censal population changes occur. The overall objective of this project is to develop a cost-effective method to generate detailed (census block level), timely (inter-census) and accurate population estimates. This will be accomplished by development of an improved estimation of housing units in an automatic fashion from emerging high-spatial resolution remote sensing technologies, such as high spatial resolution satellite imagery and Light Detection And Ranging (LiDAR). A conventional Housing Unit (HU) method will then be employed to calculate population counts at census block level. Two separate validations: including a household special census, and comparisons to 2010 Census, will be performed to evaluate the accuracy of population estimates derived from the developed remote sensing methods. <br/><br/>This project is intended to synergize previous efforts that separately existed in two fields: remote sensing and population geography, in order to seek solutions for providing timely population estimates at census block level. The research will make significant contributions to the technical advancement of the two fields as well as demonstrate a viable scheme for linking the two fields in addressing population estimation. The proposed method will provide a more cost-effective solution for population projections since the method is mainly driven by remote sensing data as compared to the laboriously collected decennial and survey data of the Census Bureau. In addition, the results of the project will be discussed extensively with city planners and officials from Austin and nearby rapidly growing localities.en_US
dc.titleCollaborative Research: Improving Small Area Population Estimation with High-Resolution Remote Sensingen_US
dc.typeNSF Granten_US


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