Displaying 1 - 5 of 5
Operations
Khandelwal, Ankush; Karpatne, Anuj; Wei, Zhihao; Ghosh, Rahul; Kuang, Huangying; Cutler, Kelly; Dugan, Hilary; Hanson, Paul; Kumar, Vipin. 2020. ReaLSAT-R: A new Reservoir Surface Area Dynamics Database created using Machine Learning and Satellite Imagery.
Related URL(s): https://ai4earthscience.github.io/iclr-2020-workshop/papers/ai4earth28.pdf
Uses Remote Sensing: yes
SEDAC Data Collection(s):
grand-v1
(Conference Paper)
export
Zhang, Ping; Wolfe, Robert; Bounoua, Lahouari. 2020. Comparison of MODIS Land Surface Temperature and Air Temperature Over Global in 2015. [IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium] pp: 4403-4406 DOI: https://doi.org/10.1109/IGARSS39084.2020.9324516
Uses Remote Sensing: yes
SEDAC Data Collection(s):
ulandsat
(Conference Proceedings)
export
Doupe, Patrick; Bruzelius, Emilie; Faghmous, James; Ruchman, Samuel G. 2016. Equitable development through deep learning: The case of sub-national population density estimation. [Proceedings of the 7th Annual Symposium on Computing for Development] pp: 1-10 DOI: https://doi.org/10.1145/3001913.3001921
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v3
grump-v1
(Conference Paper)
export
Pinkovskiy, Maxim; Sala-i-Martin, Xavier. 2016. Lights, Camera,....Income! Estimating Poverty using National Accounts, Survey Means and Lights. [Allied Social Science Associations ] pp: 46
Related URL(s): https://www.aeaweb.org/conference/2016/preliminary.php
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v3
(Conference Paper)
export
Xie, Jibo; Yu, Wenyang; Li, Guoqing. 2016. An inter-agency collaborative computing framework for fast flood mapping using distributed remote sensing data. [2016 Fifth International Conference on Agro-Geoinformatics (Agro-Geoinformatics)] pp: 1-5 DOI: https://doi.org/10.1109/Agro-Geoinformatics.2016.7577603
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v3
(Conference Proceedings)
export
Export results as CSVXML