Displaying 1 - 7 of 7
Operations
Yao, Jiaxiong. 2021. Electricity Consumption and Temperature: Evidence from Satellite Data. [IMF Working Paper No. 2021/022] pp: 38
Related URL(s): https://www.imf.org/en/Publications/WP/Issues/2021/02/05/Electricity-Consumption…
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v4
(Report)
export
Armand, Alex; Gomes, Joseph Flavian; Taveras, Ivan Kim. 2019. Managing Agricultural Risk in Mozambique. International Growth Centre. F-36421-MOZ-1: 28
Related URL(s): https://www.theigc.org/project/managing-agricultural-risk-in-mozambique/
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v4
(Report)
export
Graff, Tilman. 2019. Spatial Inefficiencies in Africa's Trade Network. [National Bureau of Economic Research Working Paper Series] National Bureau of Economic Research. No. 25951: 54 DOI: https://doi.org/10.3386/w25951
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v4
(Report)
export
Khandelwal, Ankush; Ghosh, Rahul; Wei, Zhihao; Kuang, Huangying; Kumar, Vipin; Dugan, Hilary; Hanson, Paul; Karpatne, Anuj. 2019. GLADD-R: A new Global Lake Dynamics Database for Reservoirs. University of Minnesota. TR 19-004: 7
Related URL(s): https://www.cs.umn.edu/research/technical_reports/view/19-004
Uses Remote Sensing: yes
SEDAC Data Collection(s):
grand-v1
(Report)
export
Dalgaard, Carl-Johan; Kaarsen, Nicolai; Olsson, Ola; Selaya, Pablo. 2018. Roman Roads to Prosperity: Persistence and Non-Persistence of Public Goods Provision. [CEPR Discussion Paper No. DP12745] Centre for Economic Policy Research (CEPR). pp: 49
Related URL(s): http://www.cepr.org/active/publications/discussion_papers/dp.php
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v4
(Report)
export
Graff, Tilman. 2018. Spatial Inefficiencies in Africa’s Trade Network. Centre for the Study of African Economies, University of Oxford. WPS/2018-17: 58
Related URL(s): https://www.csae.ox.ac.uk/papers/wps-2018-17
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v4
(Report)
export
Jackson, Benjamin. 2018. The GREAT-ER Model as a Tool for Chemical Risk Assessment and Management for Chinese River Catchments. [Faculty of Science and Technology, Lancaster Environment Centre] Ph.D.(126264): 299
Related URL(s): http://eprints.lancs.ac.uk/126264/
Uses Remote Sensing: yes
SEDAC Data Collection(s):
gpw-v4
(Thesis)
export
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