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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLIII-B2-2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-605-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-605-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
12 Aug 2020
| 12 Aug 2020
DUAL PYRAMIDS ENCODER-DECODER NETWORK FOR SEMANTIC SEGMENTATION IN GROUND AND AERIAL VIEW IMAGES
S. L. Jiang
Department of Land Surveying and Geo-informatics, The Hongkong Polytechnic University, Hong Kong
College of Information and Communication Engineering, Sungkyunkwan University, Suwon, Korea
G. Li
College of Information and Communication Engineering, Sungkyunkwan University, Suwon, Korea
Department of Land Surveying and Geo-informatics, The Hongkong Polytechnic University, Hong Kong
Research Institute for Sustainable Urban Development, The Hong Kong Polytechnic University, Hong Kong
Z. H. Hong
College of Information Technology, Shanghai Ocean University, Shanghai, China
T. Y. Kuc
College of Information and Communication Engineering, Sungkyunkwan University, Suwon, Korea
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Revised manuscript accepted for ESSD
Short summary
Short summary
We released a dataset (IC2-GDEM) by directly refining the ASTER GDEM elevation with ICESat-2 altimeter data. It presents a superior elevation quality compared to ASTER GDEM at a global scale. It can promote seamless integration with the historical datasets of ASTER GDEM, which is essential for longitudinal studies of long-term environmental changes, etc. impacts. It can be as a new complementary data source to other DEMsfor leading to more reliable and comprehensive scientific discoveries.
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