Zobrazeno 1 - 10 of 129 pro vyhledávání: '"C. Jochem"'
1
Akademický článek
The spatial and social correlates of neighborhood morphology: Evidence from building footprints in five U.S. metropolitan areas.
Autor: Noah J Durst, Esther Sullivan, Warren C Jochem
Publikováno v: PLoS ONE, Vol 19, Iss 4, p e0299713 (2024)
Recent advances in quantitative tools for examining urban morphology enable the development of morphometrics that can characterize the size, shape, and placement of buildings; the relationships between them; and their association with broader pattern
Externí odkaz: https://doaj.org/article/4cdd450e68f1458ab2f1f0a1b0ee4dad
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2
Akademický článek
Mapping the prevalence of severe acute malnutrition in Papua, Indonesia by using geostatistical models
Autor: Paul Jasper, Warren C. Jochem, Emma Lambert-Porter, Umer Naeem, Chigozie Edson Utazi
Publikováno v: BMC Nutrition, Vol 8, Iss 1, Pp 1-10 (2022)
Abstract Background Severe acute malnutrition (SAM) is the most life-threatening form of malnutrition, and in 2019, approximately 14.3 million children under the age of 5 were considered to have SAM. The prevalence of child malnutrition is recorded t
Externí odkaz: https://doaj.org/article/734afa3564dd4d4bb18c3c095f317036
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3
Akademický článek
Tools for mapping multi-scale settlement patterns of building footprints: An introduction to the R package foot.
Autor: Warren C Jochem, Andrew J Tatem
Publikováno v: PLoS ONE, Vol 16, Iss 2, p e0247535 (2021)
Spatial datasets of building footprint polygons are becoming more widely available and accessible for many areas in the world. These datasets are important inputs for a range of different analyses, such as understanding the development of cities, ide
Externí odkaz: https://doaj.org/article/7ccca1d0e7a14037ae4938513d505f75
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4
Akademický článek
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5
Akademický článek
Using GIS and Machine Learning to Classify Residential Status of Urban Buildings in Low and Middle Income Settings
Autor: Christopher T. Lloyd, Hugh J. W. Sturrock, Douglas R. Leasure, Warren C. Jochem, Attila N. Lázár, Andrew J. Tatem
Publikováno v: Remote Sensing, Vol 12, Iss 23, p 3847 (2020)
Utilising satellite images for planning and development is becoming a common practice as computational power and machine learning capabilities expand. In this paper, we explore the use of satellite image derived building footprint data to classify th
Externí odkaz: https://doaj.org/article/be9a828afebb4597ace45ed8cbdb0b69
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10
National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty
Autor: Warren C. Jochem, Eric M. Weber, Andrew J. Tatem, Vincent Seaman, Douglas R. Leasure
Publikováno v: Proceedings of the National Academy of Sciences of the United States of America
Significance High-resolution population estimates are essential for government planning, development projects, and public health campaigns, but countries where this information is most needed are often where recent national census data are least avai
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::22a7535733be38c1f4642ee4e9a8e68c
https://doi.org/10.1073/pnas.1913050117
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