Displaying 1 - 4 of 4
Operations
Gao, Jing; O'Neill, Brian. 2019. Data-driven spatial modeling of long-term urban land development potential for global environmental change impact assessment: The SELECT model. [Environmental Modelling & Software] . 119: 458-471 DOI: https://doi.org/10.1016/j.envsoft.2019.06.015
SEDAC Data Collection(s):
(Journal Article)
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Jin, Kai; Wang, Fei; Chen, Deliang; Liu, Huanhuan; Ding, Wenbin; Shi, Shangyu. 2019. A new global gridded anthropogenic heat flux dataset with high spatial resolution and long-term time series. [Scientific Data] . 6(1): 139 DOI: https://doi.org/10.1038/s41597-019-0143-1
Uses Remote Sensing: yes
SEDAC Data Collection(s):
(Journal Article)
export
Meehan, Timothy D.; Michel, Nicole L.; Rue, Håvard. 2019. Spatial modeling of Audubon Christmas Bird Counts reveals fine-scale patterns and drivers of relative abundance trends. [Ecosphere] . 10(4): e02707 DOI: https://doi.org/10.1002/ecs2.2707
SEDAC Data Collection(s):
(Journal Article)
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Meng, Jun; Li, Chi; Martin, Randall V.; van Donkelaar, Aaron; Hystad, Perry; Brauer, Michael. 2019. Estimated long-term (1981-2016) concentrations of ambient fine particulate matter across North America from chemical transport modeling, satellite remote sensing and ground-based measurements. [Environmental Science & Technology] . 53(9): 5071-5079 DOI: https://doi.org/10.1021/acs.est.8b06875
Uses Remote Sensing: yes
SEDAC Data Collection(s):
(Journal Article)
export
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