Displaying 1 - 5 of 5
Operations
Lin, Ping; Yang, Lu; Zhao, Shuqing. 2020. Urbanization effects on Chinese mammal and amphibian richness: a multi-scale study using the urban-rural gradient approach. [Environmental Research Communications] . 2(12): 125002 DOI: https://doi.org/10.1088/2515-7620/abd1c5
Uses Remote Sensing: yes
SEDAC Data Collection(s):
species
(Journal Article)
export
Hulley, Glynn; Shivers, Sarah; Wetherley, Erin; Cudd, Robert. 2019. New ECOSTRESS and MODIS land surface temperature data reveal fine-scale heat vulnerability in cities: A case study for Los Angeles County, California. [Remote Sensing] . 11(18): 2136 DOI: https://doi.org/10.3390/rs11182136
Uses Remote Sensing: yes
SEDAC Data Collection(s):
usgrid
(Journal Article)
export
Myer, Mark H.; Johnston, John M. 2019. Spatiotemporal Bayesian modeling of West Nile virus: Identifying risk of infection in mosquitoes with local-scale predictors. [Science of The Total Environment] . 650: 2818-2829 DOI: https://doi.org/10.1016/j.scitotenv.2018.09.397
Uses Remote Sensing: yes
SEDAC Data Collection(s):
usgrid
(Journal Article)
export
Walsh, Michael G; Mor, Siobhan M; Maity, Hindol; Hossain, Shah. 2019. Forest loss shapes the landscape suitability of Kyasanur Forest disease in the biodiversity hotspots of the Western Ghats, India. [International Journal of Epidemiology] . 48(6): 1804-1814 DOI: https://doi.org/10.1093/ije/dyz232
Uses Remote Sensing: yes
SEDAC Data Collection(s):
species
(Journal Article)
export
Zou, Yufei; O’Neill, Susan M.; Larkin, Narasimhan K.; Alvarado, Ernesto C.; Solomon, Robert; Mass, Clifford; Liu, Yang; Odman, M. Talat; Shen, Huizhong. 2019. Machine learning-based integration of high-resolution wildfire smoke simulations and observations for regional health impact assessment. [International Journal of Environmental Research and Public Health] . 16(12): 2137 DOI: https://doi.org/10.3390/ijerph16122137
Uses Remote Sensing: yes
SEDAC Data Collection(s):
usgrid
(Journal Article)
export
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