Modeling
Develop Agent-Based Cell Modeling Framework to Simulate Future Changes
Our earth is undergoing consistent changes in both natural and man-made systems. The successful simulation of their future patterns can allow us insights into better adaption strategies. I am interested in modeling the evolution of macroscopic scale phenomena with two particular emphasis: coupling time, space, and variables together, and incorporating the highly dynamic nature.
Citation: Liang L, Li XC, Huang YB, Qin YC, Huang HB. (2017) Integrating remote sensing, GIS and dynamic models for landscape-level simulation of forest insect disturbance. Ecological Modeling. 354:1-10.
Understanding Disease Ecosystem In A Changing Environment
Human is an indispensable part of the earth system. And human health has been one of the biggest concerns that are intricately interplayed with the external environments and socio-economic activities. One of my research interests is to use interdisciplinary approaches and novel geospatial techniques to address the question “how do the changing environments affect human health?”
One of my earlier research tasks was focused on developing a spherical coordinate based spatial-temporal K function to detect spatial and temporal clusters of disease outbreak cases. As previous geospatial techniques are built upon a flat plane, my spherical 3-dimensional function better approximates real-world scenarios. Furthermore, I introduced a novel 3D graphical map overlay algorithm to account for the challenging spherical point patterns from edge effects due to coastal and uninhabitable area boundaries, which had not existed in any previous research software. Utilizing this novel spherical K function on the pathogenic avian influenza H5N1 dataset, I integrated geoinformatics and bioinformatics to determine the genetic linkages among disease epicenters to infer influenza spreading route and the main transmission agent.
Citation: Liang L, Xu B, Chen Y, Liu Y, Cao W, et al. (2010) Combining spatial-temporal and phylogenetic analysis approaches for improved understanding on global H5N1 transmission. PLoS ONE, 5(10): e13575.
I integrated landscape genetics methods, earth observation data, ecological niche modeling, and geospatial analysis to explain the evolutionary process of a water-borne parasitic infectious disease schistosomiasis. I designed new snail bioclimatic variables based upon the life cycle of the intermediate hosts of Schistosoma japonicum for more accurate modeling of schistosomiasis habitat shifting under the changing climate.
Citation: Liang L, Liu Y, Liao JS, Gong P. (2014) Wetlands explain most in the genetic divergence pattern of Oncomelania hupensis. Infection, Genetics and Evolution, 27: 436-444.