Di Zhang

Spatial Planning & Biodiversity Expert – United Nations Development Programme (UNDP)

Di is a Spatial Planning & Biodiversity Expert with the Global Programme on Nature for Development, UNDP. She provides key implementation support to a broad range of spatial activities across the Mapping Nature for People and Planet (ELSA) project and the UN Biodiversity Lab (UNBL), including data management, GIS analysis, stakeholder engagement and capacity building. Di coordinates the ELSA science team work and has worked closely with countries across the globe to locate and curate national-level data on biodiversity, climate, and sustainable livelihoods. She is also responsible for user support of UNBL and coordinates core activities to support national-level achievement of the Kunming-Montreal Global Biodiversity Framework.

Previous experience and expertise

Prior to joining UNDP, Di conducted her PhD study on conservation outcomes of protected areas, and co-designed an evidence-based outcomes evaluation system for China’s nature reserves that embeds long-term monitoring efforts. Di has worked as consultant for a non-profit organization Shanshui, where she implemented the China Forest Watch project, and co-led the conservation outcome assessment of China’s largest Giant Panda nature reserve. Di also has work experience with UNDP China and the Development Research Center of the State Council. Di holds a PhD degree in Conservation Biology from Peking University, and a Bachelor’s degree in Marine Biology. She has large research interests in systematic conservation planning, protected areas effectiveness assessment, and has broad experience in GIS, statistics, wildlife inventory and habitat modeling.

Recent work 

• Integrated Spatial Planning Workbook (UNDP)
• Wang, H., Zhang, D., Lü, Z. (2023) How to Access the Conservation Outcomes of Protected Areas? Peking University Press.
• Zhang, D., Wang, H., Wang, X., & Lü, Z. 2020. Accuracy assessment of the global forest watch tree cover 2000 in China. International Journal of Applied Earth Observation and Geoinformation, 87, 102033. https://doi.org/10.1016/j.jag.2019.102033