Displaying 1 - 3 of 3
Operations
Bajaj, Shaurya; Geraldine Bessie Amali, D. 2019. Species environmental niche distribution modeling for Panthera Tigris Tigris ‘Royal Bengal Tiger’ using machine learning. [Emerging Research in Computing, Information, Communication and Applications] Ed(s): Shetty, N. R.; Patnaik, L. M.; Nagaraj, H. C.; Hamsavath, Prasad Naik; Nalini, N. pp: 251-263 DOI: https://doi.org/10.1007/978-981-13-5953-8_22
Uses Remote Sensing: yes
SEDAC Data Collection(s):
(Conference Proceedings)
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Lin, Li; Di, Liping; Yang, Ruixin; Zhang, Chen; Yu, Eugene; Rahman, Md. Shahinoor; Sun, Ziheng; Tang, Junmei. 2018. Using machine learning approach to evaluate the PM2.5 concentrations in China from 1998 to 2016. [7th International Conference on Agro-geoinformatics] pp: 1-5 DOI: https://doi.org/10.1109/Agro-Geoinformatics.2018.8475987
SEDAC Data Collection(s):
sdei
(Conference Proceedings)
export
Mao, Zhimin. 2016. Turning Policy Promises into Blue Skies: Mixed-Method Assessment of China's Past and Future Air Pollution–Reduction Efforts. [Pardee RAND Graduate School] Knopman, Debra. Ph.D.(RGSD-385): 147 DOI: https://doi.org/10.7249/RGSD385
Uses Remote Sensing: yes
SEDAC Data Collection(s):
sdei
(Thesis)
export
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