profileimage

Dr. Sun Zhongqiu is a scientist at the Academy of Forest Inventory & Planning, State Forestry Administration, China.
 
Zhongqiu Sun has received her PhD in Cartography and Geographic Information System in Peking University. Her key area of research is spatial data integration and three-dimension GIS. She proposed a new 3D GIS model and developed a prototype system based on it. It is a multi-scale adaptive spatial discrete grid so that the calculation and expression of three-dimension field data are not confined to the surface envelope. Meanwhile, it can supply the spatial-temporal analysis chart, etc. After graduation, she joined in the team of Academy of Forest Inventory & Planning. Now she focuses on the forestry statistics and mapping in the Geographic Information System.
 

Why I am part of The Carbon Institute

In terrestrial carbon accounting, we have to manage data with the characteristics of multiple data scales, differences in time or professional field. As a result, it is very necessary to understand the statistical methods especially the combining estimates of error or uncertainty.
 
In FAMC, I will design the statistical curriculum with the help of Carbon Institute. In TCA, besides the basic idea of a number of combined estimations, and international programs expect the uncertainty (and associated confidence), R language will be introduced to trainees which will help them to calculate the combined error and associated confidence.
 

Selected Publications

  • Zhongqiu Sun, Chengqi Cheng True 3D data expression Based on GeoSOT-3D ellipsoid subdivision [J]. Geomatics world, 2016, 23(3):40-46.
  • Zhongqiu Sun, Shuang Li, Chengqi Cheng Analyzing Regional Economic Disparities Based on ESDA in Yangtze River Delta [J]. Geomatics world, 2016,23(1):71-79.
  • Zhongqiu Sun, Chengqi Cheng 3D integrated representation model and visualization based on the global discrete voxel—GeoSOT3D [C] Geoinformatics 2015.
  • Zhongqiu Sun, Bo Chen, Chengqi Cheng A DMD-based hyperspectral imaging system using compressive sensing method[C] Proc. SPIE 2014.