Lin Yan is an assistant research professor working on continental-scale land-cover and land-use change (LCLUC) monitoring using Landsat data.
Lin Yan received his Ph. D. in Geodetic Science and Surveying Engineering from The Ohio State University (OSU) (2011), and he received his M.S. in Photogrammetry and Remote Sensing (2005) and his B.S in Surveying Engineering (2002) from Tongji University. His Ph.D. research focused on spectral-spatial classification and nonlinear dimensionality reduction of hyperspectral remote sensing images. Lin also served as software engineer in the Mapping and GIS Lab at OSU supporting NASA's Mars Exploration Rover (MER) and Lunar Reconnaissance Orbiter (LRO) missions.
Yan, L. (Principal Investigator) and Roy, D.P., Sentinel-2/Landsat-8 automated registration software tool development to support the terrestrial moderate spatial resolution user community. This proposal seeks to develop open-source software for precise registration of the Landsat-8 and Sentinel-2 Level 1 products. The proposed work will be undertaken over two years with a phased software delivery. The software will be released to the NASA MuSLI Science Team and refined as needed based on their informed feedback. By the end of the second year, the software will also be released to the general public.
• Yan, L., Roy, D.P., Zhang, H.K., Li, J., Huang, H. (2016). An automated approach for sub-pixel registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery. Remote Sensing, 8(6), 520; doi:10.3390/rs8060520, (http://www.mdpi.com/2072-4292/8/6/520). In special issue "First Experiences with European Sentinel-2 Multi-Spectral Imager (MSI)".
• Yan, L. and Roy, D.P. (2016). Conterminous United States crop field size quantification from multi-temporal Landsat data. Remote Sensing of Environment, 172, 67-86. (http://dx.doi.org/10.1016/j.rse.2015.10.034).
Conterminous United States field extraction data download: http://lcluc.umd.edu/content/conterminous-united-states-conus-field-extr...
• Yan, L. and Roy, D.P. (2015). Improved time series land cover classification by missing-observation-adaptive nonlinear dimensionality reduction. Remote Sensing of Environment, 158, 478-491. (http://dx.doi.org/10.1016/j.rse.2014.11.024)
• Yan, L. and Roy, D.P. (2014) Automated crop field extraction from multi-temporal Web Enabled Landsat Data, Remote Sensing of Environment. 144, 42-64. (http://dx.doi.org/10.1016/j.rse.2014.01.006)
• Yan, L. and Niu, X. (2014). Spectral-angle-based Laplacian Eigenmaps for nonlinear dmensionality reduction of hyperspectral imagery. Photogrammetric Engineering & Remote Sensing, 80, 849-861.
• Li, R., Yan, L., Di, K., and Wu, B. (2008). A new ground-based stereo panoramic scanning system. The XXIth ISPRS Congress, Beijing, China, July 3-11, 2008, 6 p.
• Yan, L., Roy, D.P., Conterminous United States crop field extraction from multi-temporal Landsat data. Fall Meeting, AGU, San Francisco, CA, Dec. 14-18, 2015.
• Yan, L., Roy, D.P., Mapping and monitoring field sizes from satellite time series. AAG Annual Meeting, Chicago, IL, April 21-25, 2015.
• Yan, L., Roy, D.P., Automated agricultural field extraction from multi-temporal Web Enabled Landsat Data. Fall Meeting, AGU, San Francisco, CA, Dec. 3-7, 2012.
• Li., R., Yan, L., He, S., Hwangbo, J., Chen, Y., Tang, M., Wang, W., Tang, P., Lawver, J., Thomas, P.C., Robinson, M., Photogrammetric techniques for terrain model generation from LROC NAC images. ASPRS 2010 Fall Conference, Orlando, FL, Nov. 15-19, 2010.
• Li, R., Yan, L., Di, K., A new ground-based stereo panoramic scanning system, the XXIth ISPRS Congress, Beijing, China, July 3-11, 2008.
• Li, R., Yan, L., Di, K., Initial results of a new ground-based stereo panoramic scanning system. ASPRS 2007 Annual Conference, Tampa, FL, May 7-11, 2007.