President of the International Society for Photogrammetry and Remote Sensing, National Geomatics Centre of China

Dr Chen Jun

Chen Jun received his education on photogrammetry and remote sensing in both China and France. He became an associate professor in 1987 and full professor in 1992 in Wuhan University. In 1995, he joined National Geomatics Center of China (NGCC), and served as the NGCC president from 2000 to 2009. He is now chief scientist of NGCC. He has led a number of key research and operational projects in the field of geo-information, including global land cover mapping at 30 meter resolution, updating of national databases at 1:50,000 scales, mapping Ming Great Wall with remote sensing, dynamic and multi-dimensional data modeling, and service-oriented dynamic geo-computing. He has developed Voronoi-based 9-intersection model, spectral gradient-based change detection algorithm,, and published more than 100 journal papers. Since 1993, he has supervised more than 40 PhD students. Chen Jun has been active in both national and international societies. He was the president of China Association of GIS from 1999-2011. He has served the International Society of Photogrammetry and Remote Sensing ISPRS since 1996 and is now ISPRS president (2012-2016). He is also a member of the editorial board of International Journal of Geographic Information Sciences (IJGIS) and ISPRS Journal of Geo-information Sciences .


30-m Global Land Cover Mapping: Methodology and Data Products

Recently, China has completed a four year’s operational Global land cover (GLC) mapping project, and produced a comprehensive 30-m resolution GLC data product, named Globalland30. It contains two data sets for the year 2000 and 2010 respectively, and each has ten land cover classes, i.e., water, wetland, artificial cover, cropland, ice/snow, forest, shrub-land, grassland, barren land and tundra. As the first 30-m GLC data product, Globalland30 has a finer spatial resolution and a better temporal consistency between two baseline years. It provides both more detailed land cover and change information between the ten years.

The Globalland30 was developed using the Landsat-like 30-m remotely sensed imagery. A Pixel-Object-Knowledge (POK) integrated mapping methodology was built by combining automatic classifiers, human domain knowledge about land cover and change, and web service technology. The mapping of complex land cover types was decomposed into a series of simpler single class classification, and each single class was mapped by combining pixel-based classification, object-based identification and knowledge-based verification. A web-based information system was set up for supporting the interactive quality controlling.

Globalland30 provides change are essential information for the environmental change analysis, earth system simulation, global understanding and sustainable development.The geographic distribution of global land cover and its ten year’s change has been analyzed, and some interesting findings have been achieved. Some examples from the Africa area will be demonstrated in this presentation.

The Globalland30 will be available on the website for free access and non-commercial utilization. This will promote the data sharing in the field of geo-sciences and earth observation, and stimulate the collaborative land cover information services in the world.

View This Paper