Post Doctoral Scholar
Dr. Min Xu
Min Xu

Education:

2018-2020 — Ph.D. in Geography, University of Alabama, Tuscaloosa, AL, USA.

2015-2018 — Ph.D. student in the Department of Geography and Geographic Information Science, University of Cincinnati, Cincinnati, OH, USA.

2013-2015 — M.A. in Geography, University of Cincinnati, Cincinnati, OH, USA.

2009-2013 — B.S. in Computer Science and Technology, Central South University, Changsha, Hunan, China.

Positions:

07/2020-present — Postdoctoral Scholar, College of Marine Science, University of South Florida, St. Petersburg, FL, USA.

Research Interests:

Environmental Remote Sensing

  • Water quality (chlorophyll-a, cyanobacteria/phycocyanin, turbidity, colored dissolved organic matter, algal blooms, and trophic state), hydrology, water resource
  • Land cover and land use change
  • Multispectral and hyperspectral remote sensing algorithms development

Geographic Information Science

  • Geospatial techniques, spatial statistics
  • Spatiotemporal analytics of geospatial big data

Computer Science

  • Machine learning (ensemble learning, deep learning)
  • Cloud computing (Google Earth Engine)

Publications:

Shu, S., Liu, H., Beck, R.A., Frappart, F., Korhonen, J., Xu, M., Yang, B., Hinkel, K.M., Huang, Y. and Yu, B., 2020. Analysis of Sentinel-3 SAR altimetry waveform retracking algorithms for deriving temporally consistent water levels over ice-covered lakes. Remote Sensing of Environment, 239, p.111643.

Xu, M., Liu, H., Beck, R., Lekki, J., Yang, B., Shu, S., Liu, Y., Benko, T., Anderson, R., Tokars, R., Johansen, R., Emery, E. and Reif, M., 2019. Regionally and locally adaptive models for retrieving chlorophyll-a concentration in inland waters from remotely sensed multispectral and hyperspectral imagery. IEEE Transactions on Geoscience and Remote Sensing, 57(7), pp. 4758-4774.

Xu, M., Liu, H., Beck, R., Reif, M., Emery, E. and Young, J., 2019. Regional analysis of lake and reservoir water quality with multispectral satellite remote sensing images. Technical Report, U.S. Army Corps of Engineers, Engineer Research and Development Center, ERDC/EL TR-19-19. (http://dx.doi.org/10.21079/11681/34933)

Johansen, R., Reif, M., Emery, E., Nowosad, J., Beck, R., Xu, M. and Liu, H., 2019. waterquality: An Open-Source R Package for the Detection and Quantification of Cyanobacterial Harmful Algal Blooms and Water Quality. Technical Report, U.S. Army Corps of Engineers, Engineer Research and Development Center, ERDC/EL TR-19-20. (http://dx.doi.org/10.21079/11681/35053)

Johansen, R.A., Beck, R., Stumpf, R., Lekki, J., Tokars, R., Tolbert, C., McGhan, C., Black, T., Ma, O., Xu, M. and Liu, H., 2019. HABSat-1: Assessing the feasibility of using CubeSats for the detection of cyanobacterial harmful algal blooms in inland lakes and reservoirs. Lake and Reservoir Management, pp.1-15.

Xu, M., Liu, H., Beck, R., Lekki, J., Yang, B., Shu, S., Kang, E.L., Anderson, R., Johansen, R., Emery, E. and Reif, M., 2018. A spectral space partition guided ensemble method for retrieving chlorophyll-a concentration in inland waters from Sentinel-2A satellite imagery. Journal of Great Lakes Research, 45(3), pp.454-465.

Beck, R., Xu, M., Zhan, S., Johansen, R., Liu, H., Tong, S., Yang, B., Shu, S., Wu, Q., Wang, S. and Berling, K., 2018. Comparison of satellite reflectance algorithms for estimating turbidity and cyanobacterial concentrations in productive freshwaters using hyperspectral aircraft imagery and dense coincident surface observations. Journal of Great Lakes Research, 45(3), pp.413-433.

Wang, S., Tedesco, M., Xu, M. and Alexander, P.M., 2018. Mapping ice algal blooms in southwest Greenland from space. Geophysical Research Letters, 45(21), pp.11-779.

Johansen, R., Beck, R., Nowosad, J., Nietch, C., Xu, M., Shu, S., Yang, B., Liu, H., Emery, E., Reif, M. and Harwood, J., 2018. Evaluating the portability of satellite derived chlorophyll-a algorithms for temperate inland lakes using airborne hyperspectral imagery and dense surface observations. Harmful Algae, 76, pp.35-46.

Huang, Y., Liu, H., Yu, B., Wu, J., Kang, E.L., Xu, M., Wang, S., Klein, A. and Chen, Y., 2018. Improving MODIS snow products with a HMRF-based spatio-temporal modeling technique in the Upper Rio Grande Basin. Remote Sensing of Environment, 204, pp.568-582.

Beck, R., Xu, M., Zhan, S., Liu, H., Johansen, R.A., Tong, S., Yang, B., Shu, S., Wu, Q., Wang, S. and Berling, K., 2017. Comparison of satellite reflectance algorithms for estimating phycocyanin values and cyanobacterial total biovolume in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations. Remote Sensing, 9(6), p.538.

Beck, R., Zhan, S., Liu, H., Tong, S., Yang, B., Xu, M., Ye, Z., Huang, Y., Shu, S., Wu, Q. and Wang, S., 2016. Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations. Remote Sensing of Environment, 178, pp.15-30