Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/9224
Title: | Climate-related child undernutrition in the lake Victoria basin: an integrated spatial analysis of health surveys, ndvi, and precipitation data | Authors: | Lopez-Carr, David Lawrence Mwenda, Kevin M. Pricope, Narcisa G. Kyriakidis, Phaedon Jankowska, Marta M. Weeks, John R. Funk, Chris C. Husak, Gregory J. Michaelsen, Joel C. |
metadata.dc.contributor.other: | Κυριακίδης, Φαίδων | Major Field of Science: | Natural Sciences | Field Category: | Earth and Related Environmental Sciences | Keywords: | Climate;Lake Victoria Basin (LVB);Stunting;Undernutrition;NDVI;Vulnerability | Issue Date: | 1-Jun-2016 | Source: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, vol. 9, no. 6, pp. 2830-2835 | Volume: | 9 | Issue: | 6 | Start page: | 2830 | End page: | 2835 | Journal: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Abstract: | Despite growing research into the socio-economic aspects of vulnerability [1]-[4], relatively little work has linked population dynamics with climate change beyond the complex relationship between migration and climate change [5]. It is likely, however, that most people experience climate change in situ, so understanding the role of population dynamics remains critical. How a given number of people, in a given location and with varying population characteristics may exacerbate or mitigate the impacts of climate change or how, conversely, they may be vulnerable to climate change impacts are basic questions that remain largely unresolved [6]. This paper explores where and to what extent population dynamics intersect with high exposure to climate change. Specifically, in Eastern Africa's Lake Victoria Basin (LVB), a climate change/health vulnerability hotspot we have identified in prior research [7], we model child undernutrition vulnerability indices based on climate variables, including proxy measures (NDVI) derived from satellite imagery, at a 5-km spatial resolution. Results suggest that vegetation changes associated with precipitation decline in rural areas of sub-Saharan Africa can help predict deteriorating child health. | URI: | https://hdl.handle.net/20.500.14279/9224 | ISSN: | 21511535 | DOI: | 10.1109/JSTARS.2016.2569411 | Rights: | © IEEE | Type: | Article | Affiliation : | University of California The University of North Carolina Wilmington Cyprus University of Technology |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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