land use change, remote sensing, big earth data
- Jinwei Dong, Professor, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China
- Teiji Watanabe, Professor, Graduate School of Environmental Earth Science, Hokkaido University, Japan
- Wenbin Wu, Professor, Chinese Academy of Agricultural Sciences, China
- Xuezhen Zhang, Professor, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China
As a key component of global changes, land cover and land use maps have been increasingly important for improved understanding of global environmental changes and feedbacks between social and environmental systems. With the development of the remote sensing technology as well as the improvement of the mapping algorithms, a set of national and global scale land cover/use products with higher spatial and temporal resolutions have been developed to fill this gap. With the free releases of increasing remote sensing data, we are entering an unprecedented era of remote sensing big data. A lot of new algorithms and approaches using the power of the time series data analyses improved the existing efforts in identifying more specific agricultural, forest land use types, such as rice paddies, soybean, rubber plantation, oil palm, etc. These new progresses provide new and improved data products to support sustainable development goals.
This session expects to provide an opportunity for the community to exchange the new progress in the land use/cover mapping field in the context of the big remotely sensed data. We welcome any studies related to the application of remote sensing for the analysis of land system sciences, including multi-sensor, multi-resolution, multi-temporal remote sensing analysis, and specific case studies in different regions of the world.