Soe Myint




Soe Myint Ph.D
Arizona State University, Tempe, AZ, USA




Myint has a wide range of interests, including land-use and land-cover modeling/mapping, forest type mapping, urban growth prediction and mapping, assessment and monitoring of land degradation and desertification, coastal environment management information system, soil salinization and nutrient depletion modeling, and coastal suspended sediments and suspended solids mapping. His work has involved analysis of remotely sensed data, geographic information system, geostatistical modeling, data mining, pattern recognition, and geospatial analysis techniques. Additionally, Myint’s expertise in geospatial techniques, statistical modeling, and signal processing has led to development of spatial and frequency based algorithms that identify complex spatial features, objects, and classes. Some of the geospatial algorithms that he has been developing and exploring include spatial coccurrence matrix, spatial autocorrelation (Moran,s I and Geary’s C), fractal analysis method (e.g., Isarithm approach, Triangular prism approach, Variogram approach), Lacunarity analysis techniques (e.g, binary approach, differential box counting method, other gray scale methods), G index, and Fourier transform approach. Myint has been examining the effectiveness of the above geospatial approaches in identifying urban land use and land cover classes and mapping coastal features. Myint also explores spatial distribution, dispersion, orientation, pattern, and association of socio-economic functional units using central tendency and dispersion approaches, quadrat method, nearest neighbor method, geographically weighted regression approach, and spatial analysis on a network (SANET, 2001) using network K-function method and network cross K-function method. Most recently, Myint’s research efforts have focused on geospatial and frequency based multi-scale multi-decomposition techniques for spatial data mining and pattern recognition. He has developed a new wavelet-based classification framework and a number of operational algorithms using Haar wavelets, Daubechies wavelets, and Coieflets approaches to identify complex land-use and land-cover classes accurately.

Research Interests/Expertise: remote sensing; GIS; geospatial statistics; land use land cover change and prediction; assessment and monitoring of drought, land degradation, and desertification; landscape fragmentation; urban environmental modeling including urban water use and climate analysis; forest characterization including coastal environments; disaster assessment, recovery, and monitoring; agriculture water use, evapotranspiration, and surface energy analysis; spatial modeling; and classification algorithm development

Selected Publications

Feng, X. & Myint, S.W. (2016). Exploring the effect of neighboring land cover pattern on land surface temperature of central building objects. Building and Environment, 95, pp. 346 – 354. doi: 10.1016/j.buildenv.2015.09.019

Kamal, S., Huang, H.P., & Myint, S.W. (2015). The Influence of Urbanization on the Climate of the Las Vegas Metropolitan Area: A Numerical Study. Journal of Applied Meteorology and Climatology, 54(11), pp. 2157 – 2177. doi: 10.1175/JAMC-D-15-0003.1

Yang, J.C., Wang, Z.H., Chen, F., Miao, S.G., Tewari, M., Voogt, J.A., & Myint, S. (2015). Enhancing Hydrologic Modelling in the Coupled Weather Research and Forecasting-Urban Modelling System. Boundary-Layer Meteorology, 155(2), pp. 87-109. doi: 10.1007/s10546-014-9991-6

Fan, C. & Myint, S. (2014). A comparison of spatial autocorrelation indices and landscape metrics in measuring urban landscape fragmentation. Landscape and Urban Planning, 121, pp. 117 – 128. doi:10.1016/j.landurbplan.2013.10.002

Kaplan, S., Myint, S., Fan, C., & Brazel, A.J. (2014). Quantifying Outdoor Water Consumption of Urban Land Use/Land Cover: Sensitivity to Drought. Environmental Management, 53(4), pp. 855 – 864. doi:10.1007/s00267-014-0245-7