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Research

Geographic Information Modeling and Process Simulation

Approval Year: 2015
Leader: A-Xing Zhu
Members: Changqing Zhu, Jian Liu, Zhiyao Song, Min Chen, Linwang Yuan, Shuo Li, Yongning Wen, Liang Ning, Qiang Dai, Junzhi Liu

Introduction

This project team is affiliated with the state key discipline of  Geographic Information Science in Nanjing Normal University, the Key Lab of Virtual Geographic Environment, Ministry of Education, and Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application. Our team has become an important force in the field of geographic information research in China. There have been some well-known but difficult problems in traditional geographic modeling and simulation researches, such as the lack of comprehensive characterization of geographic environment. In order to solve these problems, the department of Geographic Information Science in Nanjing Normal University has gathered a group of experts in related fields and aims to build a  multi-disciplinary, multi-scale and  comprehensive research team that covers the main aspects of geographic information modeling and process simulation based on geographic information science.

Research Content

  • The acquisition and modeling of geographic information: oriented to the requirements of geographic process simulation, study the  acquisition methods of geographic information like spatial location, geological evolution process, spatial-temporal relationship, semantic structure and the physical, chemical and biological properties; study the spatial prediction methods of geographic variables and obtain their spatial patterns; study the  spatial-temporal unified data model to organize and store data for geographic process simulation and analysis efficiently.
  • The construction of geographic process simulation library: study the classification and meta-data standards for geographic process models based on formalized representation of geographic problems; collect geographic process models of different disciplines and study the method of constructing open-standard geographic process model library.
  • The construction of geographic modeling environment: study the service-oriented     encapsulation method for geographical models in order to support the comprehensive and collaborative geographic process simulation among experts of  multiple disciplines; study the parallel  computing methods of geographical process simulation based on new hardware architecture to improve the computing performance of geographic process simulation; study the method of building visual modeling environment driven by knowledge to support graphical and automatic modeling.
  • Typical geographic process simulation and analysis: according to the requirements of regional economic and social development, some typical application cases are selected, such as the simulation of global monsoon and the east Asian monsoon, the  simulation of watershed non-point source pollution process and the simulation of coast estuarine water motion; build application-specific integrated geographical process model based on the geographic process model library and the modeling environment, and conduct typical geographic process simulation, which can provide scientific basis for   regional sustainable development.

Representative Achievements

  • The construction of spatial prediction theoretical and method system for geographic variables at fine scales
    A new theoretical theory based on geographic environmental similarity has been proposed to predict spatial distribution of geographic variables. In this method, the individual representativeness of each sample is measured using environmental similarity and then used in predictive mapping. The main advances of this new approach is that it does not depend on the strict assumptions of traditional statistic-base methods, so it can use a wide range of data sources and is especially suitable for currently ubiquitous big-data.
    The research findings have been listed as one of the new developments in geography by the Research Progress in Natural Geography in British and the   Journal of Geography in American. The related methods and techniques have been adopted by more than 100 departments in more than 40 countries and have great influences over the world. The achievements have been demonstrated to the congress of the United States and gain world-wide reputation.
  • The construction of multidimension-unified geographic data model
    Oriented to the difficulties in spatio-temporal and multidimension-united expression, data modelling and complex computation, a new method for modelling and data organization based on GA (Geometric Algebra) was proposed. In this method, GA was used to support the unity of storage structure, expression structure and computation structure. Based on the Grassmann structure relations and basic multivector structure in GA, the adaptive expression model of geographic object was proposed to contain the multidimension structure relationships, topological structure and measure relations. Thus the GIS data model oriented to geographical scene can be constructed using the united storage, expression and computation structures.
    The Geography Subject Development Report (Cartography and Geographic Information System, 2012-2013) had a special commentary in the methods of spatial-temporal and multidimension united modelling. This research is also regarded as the main developments in geography among the 29 Subject Development Report in the China Association.
  • Modeling and simulation of Global Monsoon and East Asian monsoon on decadal-centennial time scale
    Our approach relies on millennial simulations with ECHO-G, an atmosphere-ocean coupled climate model. The results show that both the natural forcing (Total solar irradiation and volcanic eruptions, SV) and the anthropogenic forcing (the greenhouse gases, GHGs) can lead to increased global mean precipitation, but the increased magnitudes are significantly different. The SV forcing results show that when the global mean temperature increase 1 ℃, the global mean precipitation increased 2.1%, while 1.2% under the GHGs forcing. In the two cases, the increase of average precipitation in the tropical land area is more significant (5.5% versus 2.4%). This is determined by the energy balance of the troposphere (the balance between the latent heat of precipitation and the divergence of radiation flux). Increased greenhouse gases will reduce the divergence of radiation flux, which leads to the reduction of global precipitation increment. The study also found that the spatial distribution pattern of global precipitation and sea surface temperature is significantly different on the warming of SV and GHGs forcing. This is determined by different mechanism (Mechanisms of ocean dynamical thermostat and atmospheric static stability). The study also illustrates the different influences and mechanisms of two types of warming on global precipitation. Resolve the academic dispute on ancient climate reconstruction and IPCC climate prediction about whether warming will lead to the increase or decrease of the SST gradient in the tropical Pacific (La Niña versus El Niño). Which has important guiding significance on the planning and implementation of the earth engineering.
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