More than half of the humanity now live in urban areas and the numbers are only expected to grow over next half a century. The ever increasing surge in urban population causes key challenges in terms of sustainability, provision of food, access to energy and other resources, calling for monitoring and studies of their various aspects. Unfortunately, survey data on related key socio-economic parameters are often scarce or non-existent at desired spatial and temporal granularity, causing severe hindrance to studies aimed at addressing key urbanization issues. Remote sensing methodologies provide an efficient way to estimate these parameters either directly, such as identification and mapping of land use and land cover, urban sprawl; or through indirect measures, which include estimation of population, economic conditions through nighttime lights observations. Though past studies have suffered from lack of high spatial and radiometric data capable of detecting minute details in urban fabric, they provided directions for future research and proved the potential of remote sensing data driven approaches. Recent developments in data quality as well as computational capabilities offer exciting prospects in accurate identification and estimation of urban phenomena, for example enabling more accurate measurement of lights emitted from urban core areas using the VIIRS nighttime lights data, or detection of urban sprawl, informal settlements and pockets of poverty using machine learning and high resolution optical data. The information and insight gathered from these applications help in identification of patterns, underlying causes and predict future trends, ultimately helping the decision makes and planners to decide course for a sustainable future.
In this session, we invite abstracts related to methodology, analysis and learned insights from remote sensing and geospatial data driven applications related, but not limited to the following areas:
1. Electricity consumption and access.
2. Urban poverty identification and mapping.
3. Health conditions and accessibility.
4. Estimation of socio-economic conditions.
5. Sustainable urban development
|Presenter||Deborah Milam*, San Diego State University, Use of data with fine spatiotemporal resolution to improve understanding of land use in San Diego||20||8:00 AM|
|Presenter||Naizhuo Zhao*, Texas Tech University, Seasonality and decomposition of monthly VIIRS-DNB image composites||20||8:20 AM|
|Presenter||Yun Zhao*, Oklahoma State University, Peter kedron, Department of Geography, Oklahoma State University, Amy Frazier, Department of Gepgraphy, Oklahoma State University, Identifying urban development patterns by integrating 2D and 3D landscape models||20||8:40 AM|
|Presenter||Pranab K. Roy Chowdhury*, University of Tennessee, Christa M. Brelsford, Oak Ridge National Laboratory, Budhendra L. Bhaduri, Oak Ridge National Laboratory, Measuring electricity consumption at urban scale using VIIRS nighttime lights composite.||20||9:00 AM|
|Presenter||Paul Sutton*, University of Denver, Xuantong Wang, Department of Geography & the Environment, University of Denver, Denver, CO 80208 USA, Mickey Rafa, Pardee Center for International Futures, Josef Korbel School of International Studies, University of Denver, Denver, CO 80208 USA, Jonathan Moyer, Pardee Center for International Futures, Josef Korbel School of International Studies, University of Denver, Denver CO 80208, Using nighttime imagery to estimate Gross Domestic Product at sub-national levels in Africa||20||9:20 AM|
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