Large Area Mapping of Urban Deprivation from Sentinel-2 and Google Open Buildings using Deep Learning-Reference-Cited by-同舟云学术

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Large Area Mapping of Urban Deprivation from Sentinel-2 and Google Open Buildings using Deep Learning

Published:2024-07-07 Issue: Volume: Page:1567-1570
ISSN:
Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Engstrom Ryan¹,Owusu Maxwell¹,Hanna Mina²,Jafari Amir²,Thomson Dana R.³,Kuffer Monika⁴

Affiliation:

1. George Washington University,Department of Geography,Washington DC,USA

2. George Washington University,Data Science Program,Washington DC,USA

3. Columbia University,Center for International Earth Science Information Network (CIESIN),New York,USA

4. University of Twente, ITC,Faculty of Geo-Information Science and Earth Observation,Enschede,Netherlands

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10640635.pdf?arnumber=10640635

Reference19 articles.

1. Toward a Collective Agenda on AI for Earth Science Data Analysis

2. Analyzing urban spatial patterns and trend of urban growth using urban sprawl matrix: A study on Kolkata urban agglomeration, India

3. Estimating quality of life dimensions from urban spatial pattern metrics

4. Evaluating the Relationship Between Contextual Features Derived from Very High Spatial Resolution Imagery and Urban Attributes: A Case Study in Sri Lanka

5. Open data for algorithms: mapping poverty in Belize using open satellite derived features and machine learning

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