My research focuses on validation and comparison of Global land cover datasets. Global land cover datasets (GLC) are used in many models as land cover is an essential variable in human and nature interactions. They also provide important information for actions in the climate change mitigation and adaptation such as UNFCCC and Kyoto protocol. Thanks to developments in remote sensing technologies, several GLC maps have been produced by different agencies. These maps have been assessed in terms of their quality, compatibility and comparability to indicate their uncertainty and limitations in different applications. However, due to imperfect ground truth data and inconsistency between the GLC datasets, such assessment is a challenge.
The issues such as improving the quality of GLC maps and their validation datasets, their efficient use for different applications and user-oriented assessments are addressed in my research. Firstly, I evaluate the re-usability of different validation datasets for GLC maps according to the requirements of different user groups of GLC datasets. Secondly, I conduct comparative accuracy assessments of the recent GLC maps based on the existing reference datasets and specific user requirements. I also conduct wall-to-wall comparison of GLC maps against higher quality regional land cover products. Based on these, the possibility of creating an improved GLC map which meets the requirements of certain user groups will be explored. Lastly, the possibility of monitoring land and forest change using GLC datasets will be considered.
- Tsendbazar, N., de Bruin, S., Herold, M. (2014), Assessing global land cover reference datasets for different user communities, ISPRS Journal of Photogrammetry and Remote Sensing.
- Mora, B., Tsendbazar, N.-E., Herold, M., Arino, O. (2014), Global Land Cover Mapping: Current Status and Future Trends, Land Use and Land Cover Mapping in Europe, Springer Netherlands, pp. 11-30.
- CCI-LC Product Validation and Inter-comparison Report (2014), UCL-Geomatics 2013, p 148-165
- Tsendbazar, N.E. (2011). Object based image analysis of geo - eye VHR data to model above ground carbon stock in Himalayan mid - hill forests, Nepal, University of Twente Faculty of Geo-Information. MSc thesis.
- Keshkamat, S., Tsendbazar, N., Zuidgeest, M.H., van der Veen, A., de Leeuw, J., 2012. The environmental impact of not having paved roads in arid regions: an example from Mongolia, AMBIO: A Journal of the Human Environment 41, 202-205.
- Keshkamat, S., Tsendbazar, N., Zuidgeest, M., Shiirev-Adiya, S., van der Veen, A., van Maarseveen, M., 2013. Understanding transportation-caused rangeland damage in Mongolia, Journal of Environmental Management 114, 433-444.
- Hussin, Y.A., Gilani, H., van Leeuwen, L., Murthy, M., Shah, R., Baral, S., Tsendbazar, N.-E., Shrestha, S., Shah, S.K., Qamer, F.M., 2014. Evaluation of object-based image analysis techniques on very high-resolution satellite image for biomass estimation in a watershed of hilly forest of Nepal, Applied Geomatics 6, 59-68.