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Training Workshop 1: Methods and Models for Spatial Analysis on Population and C

Training Workshop 1:

Methods and Models for Spatial Analysis on Population and Climate Change

Dates: Oct. 5-9, 2019, Shanghai, China

Host: Asian Demographic Research Institute (ADRI), Shanghai University


The human interventions on the environment and climate systems and the consequences of environmental and climate changes on human societies vary among geographic regions and differ across administrative levels. Climate change impacts and human exposures, vulnerabilities, and risks are generally place-based and require systematic and consistent spatial analysis across multiple geographic scales. While data, methods, and models have been increasingly developed for exploring population and climate change interactions, findings from researches of various regions based on different approaches and datasets are hardly comparable or used to draw general conclusions. To promote comparative studies and foster joint and compatible research, the Asian Demographic Research Institute at Shanghai University, in collaboration with the Population-Environment Research Network (PERN), the Vulnerable Population Initiative of City University of New York (CUNY), is going to hold a training workshop on spatial analysis on population and climate change in Shanghai on October 5-9 of 2019.


Three leading scholars in spatial demographic research Bryan Jones, Guangqing Chi, and Deborah Balk (the latter joining remotely) will serve as the instructors. They are going to introduce various types of spatial data that are used in the analysis of climate-change impacts, and cover emerging methods for combining remotely sensed, satellite-type data with census/survey data to enhance population-environment research applications.  Such analysis is often fraught with technical issues, as such they will introduce solutions to many of the most common problems associated with spatial inquiries.  During the five-day intensive training sessions, the workshop will combine lectures with hands-on labs to cover explanatory spatial data analysis, spatial regression modeling, spatial downscaling models, methods for projecting spatially explicit data, and methods for assessing exposure, vulnerability, and the human response to climate hazards. As one result of the training workshop, joint research projects will be proposed for future collaborations among participants under the framework of the Asian MetaCentre for Population and Sustainable Development Analysis.


The provisional agenda

Saturday, October 5, 2019:

             AM: Review of spatial analysis - data, methods, and models;

              PM: Overview of the fields and planned joint research

Sunday October 6, 2019:

AM: Spatial Interactions modeling for population-environment research

PM: Hands-on exercises

Monday, October 7, 2019

AM: Downscaling modeling for projections of population and climate change impacts

PM: Hands-on exercises

Tuesday, October 8, 2019

AM: Explanatory spatial data analysis - concepts and methods for illustrating and detecting spatial dependence

PM: Hands-on exercises

Wednesday, October 9, 2019:

AM: Spatial regression modeling -spatial lag model and spatial error model

PM: Hands-on lab, applications to climate change and migration


Research scholars and graduate students interested in spatial analysis of population - climate change interactions and collaborative research are welcome to apply. Basic knowledge of geographic information system (GIS) and experiences of using geocoded data for spatial analysis are required. The application should include a letter of intent, CV, and a sample of publications or GIS works. Limited funding is available to support participants from low-income countries. Successful applicants are also encouraged to participate in the 2nd Asian Population Forum in Shanghai on October 11-12 of 2019. 

Deadline of application: July 15, 2019

Please apply through:


Contact: Yu Zhang, zhangyu539@shu.edu.cn

Tel: 00 86 21 6613 2080

Address: No. 99 Shangda Road, Shanghai, China