TitleAssistant Professor of GIS
Office BuildingWecota Hall
Mailing AddressWecota Hall 115D
Brookings, SD 57007
BiographyI am an Assistant Professor of GIS in the Department of Geography & Geospatial Sciences at South Dakota State University. As a well-trained GIScientist and a certified GISP, I am teaching introductory and upper-level GIS courses to train the next generation of GIS professionals at SDSU.
I am currently working with my students on the following research projects:
1) Using computer models, big data, and GIS to improve wildfire evacuation modeling/planning; (required skills: Java (or C/C++), Python, R, & GIS)
3) Using big data and GIS to map wildland-urban interface. (Required skills: Python, R, & GIS)
Meanwhile, I also start to work with my students on other topics in hazards, public health, transportation, sustainability, and precision agriculture.
Education2016 Ph.D. in Geography (GIS), University of Utah
2011 M.S. in Cartography & GIS, Peking University
2008 B.S. in GIS, China University of Geosciences (Beijing)
Academic ResponsibilitiesI teach the following GIS courses at SDSU. We have been using ArcGIS Pro in our GIS courses at SDSU since fall 2020 (ArcMap is phased out at SDSU). Those who are interested in our GIS programs or hiring our GIS graduates could refer to the syllabi on my personal website for more details on these courses.
1. GEOG 372: Introduction to Geographic Information Systems (spring semester, annual)
2. GEOG 471/571: Introduction to GIS Programming (spring semester, TBD, might be offered in spring 2023) (students can take INFO 101 to learn Python grammar at SDSU)
3. GEOG 473/573: GIS Data Creation and Integration (fall semester, annual, will be offered in fall 2021)
4. GEOG 474/574 GIS: Vector and Raster Modeling (spring semester, TBD, will be offered in spring 2022)
5. GEOG 476/576: Web GIS (fall semester, annual, will be offered in fall 2021)
6. GEOG 477/577: Spatial Databases (PostgreSQL/PostGIS) (spring semester, annual/biennial, will not be offered in spring 2022, might be offered in spring 2023) (The GIS students who want to learn spatial databases could take CSC 484 - Database Management Systems (COM) to learn relational databases and take https://www.udemy.com/course/spatialsqlpostgis/ to learn PostGIS)
7. GEOG 786: Geographic Information Systems (Topics: Advanced Python Programming (open-source GIS)) (spring semester, biennial, will be offered in spring 2023)
8. GEOG 790 Seminar: GIS Programming or other topics (spring semester, biennial, will be offered in spring 2022)
9. GEOG 791 Independent Study (spring/fall semester, TBD, depends on my schedule)
Note: GEOG 477/577 and GEOG 786 are based on open source GIS tools. GEOG 476/576 focuses on the use of Web GIS (ArcGIS). I do not have any plans to teach ArcPy programming in my courses in the next two academic years (2021-2022 & 2022-2023). My graduate-level Python courses do not cover Python grammar, and graduate students need to take an introductory-level Python programming course (e.g., INFO 101) before they take my advanced Python programming courses. All undergraduate courses are fully covered by the TAship/RAship at SDSU.
I strongly encourage our GIS students to get a GISP certification (https://www.gisci.org/) in their future careers. Below are the courses you could take at SDSU to prepare for the GISP Certification exam in the future:
1. Conceptual Foundations – 10% (GEOG 372)
2. Cartography and Visualization – 10% (GEOG 383 Cartography)
3. Data Acquisition – 11% (GEOG 473/573)
4. Database Design and Management – 10% (GEOG 477/577 or CSC 484)
5. Analytical Methods – 11% (GEOG 474/574 and/or GEOG 743)
6. Data Manipulation – 11% (GEOG 372 and GEOG 473/573)
7. Geospatial Data Fundamentals – 15% (GEOG 372 and GEOG 473/573)
8. Application Development – 7% (GEOG 471/571 or INFO 101)
9. System Design & Management – 7% (GEOG 476/576 and SE 305)
10. Professional Practice – 8%
- Methods: GIS, Systems Modeling & Integration, Spatial Analysis, Big Data, Open Science
- Fields: Hazards, Public Health, Transportation, Sustainability
Extension ResponsibilitiesPotential Collaborators:
I have been doing research and development in GIS and its applications for over fifteen years. I specialize in using open-source tools or ArcGIS products to design and implement GIS-based solutions for different applications. I enjoy working with scholars, stakeholders, and businesses and using my expertise to help them succeed. Please feel free to contact me (dapeng.li [at] sdstate.edu) if you need technical support in your research or project.
Potential Graduate Students:
I am interested in working with motivated students to study GIS and its applications in hazards, public health, transportation, sustainability, and agriculture. As funded Research Assistant positions become available, I will post the information here and on other job boards (e.g., AAG website). The Department of Geography and Geospatial Sciences will have 4~6 Teaching Assistant positions available every year. Our department will have five tenured/tenure-track faculty members in geospatial sciences/technologies (GIS and remote sensing) in fall 2021. The instructors in our online GIS courses are experienced working GIS professionals in the U.S. The Master's and Ph.D. programs are both STEM programs. In addition, we have advanced computing resources in the department. Lastly, the assistantship (TAship or RAships) can cover the tuition for any course in the SDBOR system. I strongly encourage those who want to pursue a career in GIS to reach out to me and send me a copy of your CV and a summary of your expertise and research interests.
I enjoy involving motivated undergraduate students in my research. I also have a close relationship with many local companies. I encourage those who want to develop strong GIS skills (especially those who want to be GIS developers) to contact me. I will figure out how to help you fit into my research group and develop a career plan.
1. Li, D. (PI). Using computer models, big data, and GIS to improve community wildfire evacuation planning. South Dakota State University, $15,000. (2020-2021)
3. Li, D. (PI). "Using traffic simulation, GIS, and big data for wildfire evacuation modeling in Truckee, California". The Town of Truckee, $30,000. (2019-2020)
2. Groeneveld, D. (PI) & Li, D. (Co-PI). “Using GIS to process and manage spatial information for crop insurance purposes”. South Dakota Governor's Office of Economic Development, $25,000. (2019)
1. Li, D. (PI). Open wildfire evacuation trigger modeling. South Dakota State University, $10,000. (2017-2018)
Professional Memberships2015- Association for Computing Machinery (ACM) (SIGSPATIAL)
2015- International Network of Research on Coupled Human and Natural Systems
2015- Urban and Regional Information Systems Association (URISA)
2014- Association for Fire Ecology (AFE)
2014- International Association of Wildland Fire (IAWF)
2013- Association of American Geographers (AAG) (GIS, Hazards, Health, Transportation)
2013- Cartography and Geographic Information Society (CaGIS)
Work Experience2017-present Assistant Professor, Department of Geography and Geospatial Sciences, South Dakota State University
2016-2017 Research Associate, Department of Fisheries & Wildlife, Michigan State University
2015-2016 Research Assistant, Department of Health Promotion & Education, University of Utah
2011-2015 Research Assistant, Department of Geography, University of Utah
2008-2011 Research Assistant, Institute of Remote Sensing & GIS, Peking University, China
15. Li, D., Li, Y., Nguyen, Q.C., & Siebeneck, L.K. (2020). “A study on the GIS Professional (GISP) certification program in the U.S.”. ISPRS International Journal of Geo-Information, 9(9), 523.
14. Li, D., Cova, T.J., Dennison, P.E., Wan, N., Nguyen, Q.C., & Siebeneck, L.K. (2019). “Why do we need a national address point database to improve wildfire public safety in the U.S.?”. International Journal of Disaster Risk Reduction, 39, 101237.
13. Li, D., Cova, T.J., & Dennison, P.E. (2019). “Setting wildfire evacuation triggers by coupling fire and traffic simulation models: A spatiotemporal GIS approach”. Fire Technology, 55(2), 617–642.
12. Xu, Z., Chau, S., Ruzzenenti, F., Connor, T., Li, Y., Tang, Y., Li, D., Gong, M., & Liu, J. (2019). Evolution of multiple global virtual material flows. Science of the Total Environment, 658, 659-668.
11. Meng, H., Kath, S., Li, D., & Nguyen, Q. (2017). “National substance use patterns on Twitter”. PLOS ONE, 12(11), e0187691.
10. Nguyen, Q. C., McCullough, M., Meng, H. W., Paul, D., Li, D., Kath, S., ... & Li, F. (2017). Geotagged US Tweets as Predictors of County-Level Health Outcomes, 2015–2016. American Journal of Public Health, (0), e1-e7.
9. Li, D., Cova, T.J., & Dennison, P.E. (2017). “Using reverse geocoding to identify prominent wildfire evacuation trigger points”. Applied Geography, 87, 14-27.
8. Xu, Z., Tang, Y., Connor, T., Li., D., Li., Y., & Liu, J. (2017). “Climate variability and trends at a national scale”. Scientific Reports, 7, Article number: 3258.
7. Nguyen, Q., Meng, H., Li, D., Kath, S., et al. (2017). “Social media indicators of the food environment and state health outcomes”. Public Health, 148, 120-128.
6. Cova, T.J., Dennison, P.E., Li, D., Siebeneck, L.K., Drews, F.A., & Lindell, M.K. (2017). “Warning triggers in environmental hazards: who should be warned to do what and when?” Risk Analysis, 37(4), 601-611.
5. Nguyen, Q., Li, D., Meng, H., Kath, S., Nsoesie, E., Wen, M., & Li, F. (2016). “Building a national neighborhood dataset from geotagged Twitter data for indicators of happiness, diet, and physical activity”. JMIR Public Health & Surveillance, 2(2):e158.
4. Nguyen, Q., Kath, S., Meng, H., Li, D., Smith, K., VanDerslice, J.A., Wen, M., & Li, F. (2016). “Leveraging geotagged Twitter data to examine neighborhood happiness, diet, and physical activity”. Applied Geography, 73, 77-88.
3. Li, D., Cova, T.J., & Dennison, P.E. (2015). “A household-level approach to staging wildfire evacuation warnings using trigger modeling”. Computers, Environment, and Urban Systems, 54, 56–67.
2. Guo, X., Cheng, C., Tan, Y., & Li, D. (2013). “Study on unified encoding method for topographic map based on subdivision framework”. Periodical of Ocean University of China, 44(3). (in Chinese)
1. Geng, X., Cheng, C., Song, S., & Li, D. (2010). “Global subdivision systems based on map kilo-grids”. Geography and Geo-Information Science, 2(3). (in Chinese)
Please check my personal website (https://lidapeng.github.io) for more information. If you would like my CV (this website does not allow users to upload CVs), please feel free to contact me at my sdstate email. Thank you!