Adaptive clustering-based method for ICESat-2 sea ice retrieval ...
<!--!introduction!--> The great potential of NASA's Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) to retrieve sea ice heights has been proven. However, a large number of noise photons in the ICESat-2 data make it more challenging to accurately monitor sea ice changes. In this paper...
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| Format: | Conference Object |
| Language: | unknown |
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GFZ German Research Centre for Geosciences
2023
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| Online Access: | https://dx.doi.org/10.57757/iugg23-3449 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5019503 |
| Summary: | <!--!introduction!--> The great potential of NASA's Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) to retrieve sea ice heights has been proven. However, a large number of noise photons in the ICESat-2 data make it more challenging to accurately monitor sea ice changes. In this paper, an adaptive clustering and kernel density estimate-based method (AC-KDE) to estimate sea ice heights in ICESat-2 photon clouds is proposed. First, sea ice signal photons are effectively detected by the adaptive clustering method. The input parameters of the method are determined by ATLAS parameters and the LiDAR transmission equation. Then, the adaptive-count signal photon aggregates are used to estimate sea ice heights and obtain variable along-track resolution by kernel density estimate method. By applying the AC-KDE method to the MABEL and ICESat-2 data, we compare it with other denoising algorithms, including the HBM, the DBSCAN, and the OPTICS algorithms. The results show that the proposed method is better in ... : The 28th IUGG General Assembly (IUGG2023) (Berlin 2023) ... |
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