Displaying 1 - 9 of 9
Operations
Cámara-Leret, R.; Raes, N.; Roehrdanz, P.; De Fretes, Y.; Heatubun, C. D.; Roeble, L.; Schuiteman, A.; van Welzen, P. C.; Hannah, L. 2019. Climate change threatens New Guinea’s biocultural heritage. [Science Advances] . 5(11): eaaz1455 DOI: https://doi.org/10.1126/sciadv.aaz1455
SEDAC Data Collection(s):
(Journal Article)
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Dong, Xin; Chu, Yuan-meng-ran; Gu, Xiaodong; Huang, Qiongyu; Zhang, Jindong; Bai, Wenke. 2019. Suitable habitat prediction of Sichuan snub-nosed monkeys (Rhinopithecus roxellana) and its implications for conservation in Baihe Nature Reserve, Sichuan, China. [Environmental Science and Pollution Research] . 26(31): 32374-32384 DOI: https://doi.org/10.1007/s11356-019-06369-3
SEDAC Data Collection(s):
(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
Ju, Yang; Lindbergh, Sarah; He, Yiyi; Radke, John D. 2019. Climate-related uncertainties in urban exposure to sea level rise and storm surge flooding: a multi-temporal and multi-scenario analysis. [Cities] . 92: 230-246 DOI: https://doi.org/10.1016/j.cities.2019.04.002
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
Potvin, Corey K.; Broyles, Chris; Skinner, Patrick S.; Brooks, Harold E.; Rasmussen, Erik. 2019. A Bayesian hierarchical modeling framework for correcting reporting bias in the U.S. tornado database. [Weather and Forecasting] . 34(1): 15-30 DOI: https://doi.org/10.1175/waf-d-18-0137.1
SEDAC Data Collection(s):
usgrid
(Journal Article)
export
Sherpa, Stéphanie; Guéguen, Maya; Renaud, Julien; Blum, Michael G. B.; Gaude, Thierry; Laporte, Frédéric; Akiner, Mustafa; Alten, Bulent; Aranda, Carles; Barre-Cardi, Hélène; Bellini, Romeo; Bengoa Paulis, Mikel; Chen, Xiao-Guang; Eritja, Roger; Flacio, Eleonora; Foxi, Cipriano; Ishak, Intan H.; Kalan, Katja; Kasai, Shinji; Montarsi, Fabrizio; Pajović, Igor; Petrić, Dušan; Termine, Rosa; Turić, Nataša; Vazquez-Prokopec, Gonzalo M.; Velo, Enkelejda; Vignjević, Goran; Zhou, Xiaohong; Després, Laurence. 2019. Predicting the success of an invader: Niche shift versus niche conservatism. [Ecology and Evolution] . 9(22): 12658-12675 DOI: https://doi.org/10.1002/ece3.5734
SEDAC Data Collection(s):
(Journal Article)
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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
Dutko, Paul; Ver Ploeg, Michele; Farrigan, Tracey. 2012. Characteristics and influential factors of food deserts. [Economic Research Report] USDA. ERR-140(ERR-140): 30
Related URL(s): http://www.caction.org/CAN-Research/Reports/2012/err140.pdf
SEDAC Data Collection(s):
usgrid
(Report)
export
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