Lyndon Estes, Ph.D.
Associate Professor
Graduate School of Geography
Clark University
Worcester, MA 01610-1477
Office: Room 201, Jefferson Academic Center
Email: lestes@clarku.edu
Phone: (508)-793-7531
Lyndon Estes is an environmental scientist who investigates the drivers and impacts of agricultural change, with a particular focus on Africa. He conducts his research using new Earth Observation technologies and a range of modeling techniques, and works within inter-disciplinary projects that involve economists, agronomists, human geographers, decision scientists, hydrologists, climatologists, and computer scientists. Lyndon holds a BA in English from Georgetown University, an MPhil in Conservation Biology from the University of Cape Town, and a PhD in Environmental Science from the University of Virginia. Since receiving his PhD degree in 2008, Lyndon has worked as a research scientist in Princeton University's School of Public and International Affairs and Department of Civil and Environmental Engineering. Prior to his academic career, Lyndon spent nearly 9 years working in protected area management and environmental consulting in Southern Africa.
Courses Offered
GEOG 110-311: Introduction to Quantitative Methods
GEOG 246-346: Geospatial Analysis with R
GEOG 287-387: New Methods in Earth Observation
GEOG 315: Applying Deep Learning to Earth Observation
Selected Publications
Song, L., Estes, A. B., & Estes, L. D. (2023). A super-ensemble approach to map land cover types with high resolution over data-sparse african savanna landscapes. International Journal of Applied Earth Observation and Geoinformation, 116 doi:10.1016/j.jag.2022.103152
Xiong, S., Baltezar, P., Crowley, M. A., Cecil, M., Crema, S. C., Baldwin, E., . . . Estes, L. (2022). Probabilistic tracking of annual cropland changes over large, complex agricultural landscapes using google earth engine. Remote Sensing, 14(19) doi:10.3390/rs14194896
Estes, L. D., Ye, S., Song, L., Luo, B., Eastman, J. R., Meng, Z., . . . Caylor, K. K. (2022). High resolution, annual maps of field boundaries for smallholder-dominated croplands at national scales. Frontiers in Artificial Intelligence, 4 doi:10.3389/frai.2021.744863