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Photo of Galen Maclaurin

Galen Maclaurin

Scientist III

Galen.Maclaurin@nrel.gov | 303-275-3846

Galen Maclaurin is a member of the Geospatial Data Science team within the Systems Modeling & Geospatial Data Science Group in the Strategic Energy Analysis Center.

Areas of Expertise

Spatial and temporal modeling
Remote sensing image analysis
Spatial statistics and machine learning
Scientific programming and high performance computing

Research Interests

Wind and solar resource assessment
Technical potential and supply curve modeling
Information extraction from remote sensing imagery
Small area estimation and spatial aggregation
Geographic patterns of energy consumption

Education

PhD in Geography, University of Colorado, Boulder
M.A. in Geography, University of Colorado, Boulder
B.A. in Geography and Spanish, University of Colorado, Boulder

Prior Work Experience

Lecturer, University of Colorado Denver, Department of Geography and Environmental Sciences, Denver, CO
Research Assistant, National Center for Atmospheric Research (NCAR), Boulder, CO
Graduate Instructor and Research Assistant, University of Colorado, Boulder, Geography Department, Boulder, CO

Featured Publications

Maclaurin, G., & Leyk, S. (2017). Reverse Engineering of Land Cover Data: Machine Learning for Data Replication in the Spatial and Temporal Domains. In M. Behnisch and G. Meinel (Eds.), Trends in Spatial Analysis and Modelling (Vol. 19). Springer.

Hunter, L., Leyk, S., Maclaurin, G., Nawrotzki, R., Twine, W., Erasmus, B., & Collinson, M. (2017). Variation by Geographic Scale in the Migration-Environment Association: Evidence from Rural South Africa. Comparative Population Studies, 42, 117-148.

Maclaurin, G., Sengupta, M., Xie, Y., & Gilroy, N. (2016). Development of a MODIS-Derived Surface Albedo Data Set: An Improved Model Input for Processing the NSRDB (No. NREL/TP-6A20-67306). NREL (National Renewable Energy Laboratory (NREL), Golden, CO).

Maclaurin, G., & Leyk, S. (2016). Temporal replication of the national land cover database using active machine learning. GIScience and Remote Sensing, 53(6), 759-777.

Mooney, M., & Maclaurin, G. (2016). Transportation of Large Wind Components: A Review of Existing Geospatial Data (No. NREL/TP-6A20-67014). NREL (National Renewable Energy Laboratory (NREL), Golden, CO).

Maclaurin, G., & Leyk, S. (2016). Extending the geographic extent of existing land cover data using active machine learning and covariate shift corrective sampling. International Journal of Remote Sensing, 37(21), 5213-5233.

Maclaurin G., Leyk S., & Hunter, L. (2015). Understanding the combined impacts of aggregation and spatial non-stationarity: The case of migration-environment associations in rural South Africa. Transactions in GIS, 19(6), 877-895.

Ruther, M., Maclaurin, G., Leyk, S., Buttenfield, B., & Nagle, N. (2013). Validation of spatially allocated small area estimates for 1880 Census demography. Demographic Research, 29.

Hunter, L., Nawrotzki, R., Leyk, S., Maclaurin, G., Twine, W., Collinson, M., & Erasmus, B. (2013). Rural Outmigration, Natural Capital, and Livelihoods in South Africa. Population, Space and Place.

Leyk S., Maclaurin G., Hunter L., Nawrotzki R., Twine W., Collinson M. and Erasmus B. (2012). Spatially and Temporally Varying Associations between Temporary Outmigration and Natural Resource Availability in Resource-Dependent Rural Communities in South Africa: A Modeling Framework. Applied Geography 34: 559-568.

Full list of Galen Maclaurin publications (NREL).