Geoanalytics, GIS and Remote Sensing

Overview

In a rapidly changing global world, our geoanalytical methods transform spatial data to information for human well-being. The cluster members are committed to improving the applicability and adaptability of geoanalytical methods including spatial modelling, GIS, and remote sensing to advance our understanding of geographical questions. Our research focuses on digital terrain analysis, hydrological modelling, remote sensing, spatial statistics, and travel behaviour studies. We develop and apply advanced geospatial techniques to provide immediate and efficient actions for our pressing environmental and urban problems.

Featured Research

National Science Foundation of China (PI: Prof Qiming Zhou) Investigation of High-performance Digital Terrain Analysis and Landslide Susceptibility

The research is to investigate multi-scale flow path network model to model and simulate the rainfall-runoff process, to analyze and refine the current hydrological model for landslide analysis, as well as constructing cloud-computation platform for verifying and refining models based on high-performance computing technology, and achieving the real-time dynamic landslide early warning services.

GRF Project (PI: Prof Donggen Wang) Exploring and Modelling the Relationships between Residential Environment, Travel Behavior and Travel-related Subjective Wellbeing in Shanghai, China. 2015-2018

This research project is proposed to examine the influence of individuals’ residential environment on their travel satisfaction and travel affective experience, study the effects of travel wellbeing on short-term activity-travel choices, and explore the possible impacts of travel wellbeing in long-term mobility and residential location decisions.

Transportation research or more specifically travel behavior research is experiencing a paradigm shift from focusing on the instrumental aspect of travel (such as travel time and monetary costs) to also consider the affective experience of and the cognitive satisfaction with travel. Issues related to daily travel–related subjective wellbeing have recently received great research attention. Pleasure seeking is considered in addition to time and/or money cost minimization as important determinants of travel choices and transport decisions. This new development of academic research has the potential to help broaden the objectives of transport policies from focusing on the provision of efficient and effective transport services (i.e., facilitating the fast movements of people and freight between different places) to also provide pleasant experience of travel. Many studies have been conducted to examine the factors determining individuals’ satisfaction (or dissatisfaction) and affective experience with their daily travel and activities. Existing studies have revealed that travel satisfaction varies significantly between transport models and trip characteristics are important determinants of travel satisfaction. However, the contribution of more policy related variables such as the built environment of individuals’ residential place has rarely been studied. More importantly, notwithstanding the many studies of travel satisfaction in North America and Europe, studies in other parts of the world, where mobility, travel behavior and social norms are quite different, are very scarce. This research project is proposed to fill in these gaps. Based on the Principal Investigator’s long term research on built environment and travel behavior and recent research on subjective wellbeing, this research project is proposed to examine the influence of individuals’ residential environment on their travel satisfaction and travel affective experience, study the effects of travel wellbeing on short-term activity-travel choices, and explore the possible impacts of travel wellbeing in long-term mobility and residential location decisions. The case study is proposed to be conducted in Shanghai, China. This research will fill in an important gap in the travel wellbeing literature with empirical evidences from a city of a developing country and establish important linkages between travel satisfaction, travel behavior and residential environment. The outcomes of this research will be highly relevant for developing transport policies acting on the non-instrumental aspect of travel to manage travel demand and spatial policies to improve individuals’ travel satisfaction and quality of life.

GRF Project (PI: Dr Jianfeng Li) Compound Floods from Upstream River Discharge, Localized Rainstorm and Storm Surge across the Pearl River Delta Megacity Region: Risks, Changes and Mechanisms

This study is intended to develop high-quality datasets of river discharge, localized precipitation, and sea level. Joint flood risk analysis will be conducted to estimate the probabilistic behaviors of compound floods, as well as how they have changed in the past several decades over the PRD.

The proposed study will develop high-quality datasets of river discharge, localized precipitation, and sea level. Joint flood risk analysis will be conducted to estimate the probabilistic behaviors of compound floods, as well as how they have changed in the past several decades over the PRD. Synoptic weather conditions during different types of compound floods will be analyzed to understand the mechanisms of these extreme events. Numerical simulations based on physically-based hydrological model and regional weather model will be carried out to evaluate how land use changes influence compound floods by altering land-atmosphere interactions and surface hydrological characteristics. The objectives of the proposed study are: (1) to evaluate risks of compound floods from high river discharge, localized rainstorm and/or storm surge across the PRD; (2) to estimate spatio-temporal changes in compound floods due to climate change and rapid urbanization across the PRD, and; (3) to unravel the mechanisms of compound floods in terms of weather conditions and land use changes. The study outcomes will provide strong scientific support for developing multi-flood management strategies and plans for the PRD and other coastal megacity regions in China.

Featured Publications

Many existing accessibility studies ignore human mobility due to the lack of large-scale human mobility data. This study investigates the impacts of human mobility on accessibility using massive mobile phone tracking data collected in Shenzhen, China. In this study, human mobility information is extracted from mobile phone tracking data using a time-geographic approach. The accessibility of each phone user is evaluated using fine spatial resolution across the entire city. The impacts of human mobility on accessibility are quantified by using relative accessibility ratios between phone users and a virtual stationary user in the same residential location. Results of this study enrich understandings of how land use influences relationships between human mobility and accessibility. For resource-poor regions with sparse service facilities, human mobility can greatly enhance individual accessibility. In contrast, for resource-rich regions with dense service facilities, human mobility can even reduce individual accessibility. Overall, human mobility can reduce spatial inequity of accessibility for people living in different regions of the city. The results of this study also have several important methodological implications for including human mobility and time dimension in accessibility evaluations.

This paper reports an investigation into the generalization of a grid-based digital elevation model (DEM) for the purpose of terrain analysis. The focus is on the method of restructuring the grid-based surface elevation data to form a triangulated irregular network (TIN) that is optimized to keep the important terrain features and slope morphology with the minimum number of sample points. The critical points of the terrain surface are extracted from the DEM based on their significance, measured not only by their local relief, but also by their importance in identifying inherent geomorphological and drainage features in the DEM. A compound method is proposed by integrating the traditional point-additive and feature-point methods to construct a drainage-constrained TIN. The outcome is then compared with those derived from other selected methods including filtering, point-additive or feature-point algorithms. The results show that the compound approach is capable of taking advantage of both point-additive and feature-point algorithms to maximally keep the terrain features and to maintain RMSE at an acceptable level, while reducing the elevation data points by over 99%. The analytical result also shows that the proposed method outperforms the compared methods with better control in retaining drainage features at the same level of RMSE.