Displaying 1 - 10 of 29
Operations
Breckner, Miriam. 2019. Climatic and Geographic Determinants of Economic Development. [Economics] Sunde, Uwe. Ph.D.(ediss:23734): 155
Related URL(s): https://edoc.ub.uni-muenchen.de/23734/
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v3
gpw-v4
(Thesis)
export
Cairns, Stephen; Chen, Ting. 2019. Cartographic technique and Artifice: The case of the Chengdu Plain. [Future Cities Laboratory: Indicia 02] Ed(s): Cairns, Stephen; Tunas, Devisari. pp: 191-199 DOI: https://doi.org/10.3929/ethz-b-000353122
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v4
hanpp
povmap
(Book Section)
export
Chen, Siyu; Jiang, Nanxuan; Huang, Jianping; Zang, Zhou; Guan, Xiaodan; Ma, Xiaojun; Luo, Yuan; Li, Jiming; Zhang, Xiaorui; Zhang, Yanting. 2019. Estimations of indirect and direct anthropogenic dust emission at the global scale. [Atmospheric Environment] . 200: 50-60 DOI: https://doi.org/10.1016/j.atmosenv.2018.11.063
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v3
(Journal Article)
export
Geldmann, Jonas; Manica, Andrea; Burgess, Neil D.; Coad, Lauren; Balmford, Andrew. 2019. A global-level assessment of the effectiveness of protected areas at resisting anthropogenic pressures. [Proceedings of the National Academy of Sciences] . 116(46): 23209-23215 DOI: https://doi.org/10.1073/pnas.1908221116
Uses Remote Sensing: yes
SEDAC Data Collection(s):
(Journal Article)
export
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
Lloyd, Christopher T.; Chamberlain, Heather; Kerr, David; Yetman, Greg; Pistolesi, Linda; Stevens, Forrest R.; Gaughan, Andrea E.; Nieves, Jeremiah J.; Hornby, Graeme; MacManus, Kytt; Sinha, Parmanand; Bondarenko, Maksym; Sorichetta, Alessandro; Tatem, Andrew J. 2019. Global spatio-temporally harmonised datasets for producing high-resolution gridded population distribution datasets. [Big Earth Data] . 3(2): 108-139 DOI: https://doi.org/10.1080/20964471.2019.1625151
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v3
gpw-v4
grump-v1
(Journal Article)
export
Magory Cohen, Tali; Dor, Roi. 2019. The effect of local species composition on the distribution of an avian invader. [Scientific Reports] . 9(1): 15861 DOI: https://doi.org/10.1038/s41598-019-52256-9
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v3
(Journal Article)
export
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
Wagner, Paul D.; Fohrer, Nicola. 2019. Gaining prediction accuracy in land use modeling by integrating modeled hydrologic variables. [Environmental Modelling & Software] . 115: 155-163 DOI: https://doi.org/10.1016/j.envsoft.2019.02.011
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v3
(Journal Article)
export
Walker, Robert S.; Hamilton, Marcus J. 2019. Machine learning with remote sensing data to locate uncontacted indigenous villages in Amazonia. [PeerJ Computer Science] . 5: e170 DOI: https://doi.org/10.7717/peerj-cs.170
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v3
(Journal Article)
export

Pages

Export results as CSVXML