Articles | Volume 18, issue 7
https://doi.org/10.5194/essd-18-4563-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-4563-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| Highlight paper
| 
03 Jul 2026
Data description article | Highlight paper |
| 03 Jul 2026
| 03 Jul 2026
NZ-BeachTopo30: a national-scale and full-coverage 30 m beach topography dataset for New Zealand reconstructed by fusing ICESat-2 and Sentinel-2
Yuhao Wang
School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China
Hao Xu
School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China
Nan Xu
CORRESPONDING AUTHOR
Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Ministry of Natural Resources, Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Service, Shenzhen University, Shenzhen 518060, China
School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
Edward Park
National Institute of Education, Earth Observatory of Singapore and Asian School of the Environment, Nanyang Technological University, Singapore
Xuejiao Hou
School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou, China
Jiayi Fang
Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou, 311121, China
Zhen Zhang
Department of Earth and Environmental Sciences, Tulane University, New Orleans, LA, 70118, USA
Yongjing Mao
Water Research Laboratory, School of Civil and Environmental Engineering, UNSW Sydney, Australia
Huichao Xin
School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China
Chunpeng Chen
State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China
Yinxia Cao
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Yifu Ou
School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Edinburgh, UK
Xinyue Gu
Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hung Hom, Hong Kong, China
Wenyu Li
Department of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, Canada
Xiaojuan Liu
Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Ministry of Natural Resources, Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Service, Shenzhen University, Shenzhen 518060, China
School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
Conghong Huang
College of Land Management, Nanjing Agricultural University, Nanjing, 210095, China
Qingquan Li
Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Ministry of Natural Resources, Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Service, Shenzhen University, Shenzhen 518060, China
School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518107, China
Data sets
New Zealand National-Scale Beach Topography Dataset (30 m): A Fusion of ICESat-2 and Sentinel-2 Yuhao Wang et al. https://doi.org/10.5281/zenodo.17785546
Editorial statement
Although the study has a narrow focus on New Zealand's shores, it stands as an exemplary paper in identifying a clear research gap and motivating the need for this data set. It effectively demonstrates how applying a rigorous methodology can corroborate physical realism while utilizing indirect observations with remote sensing and machine learning. This, coupled with the discussion on strengths and weaknesses, underscores the relevance of the data set for the target community and a potential broader audience.
Although the study has a narrow focus on New Zealand's shores, it stands as an exemplary paper...
Short summary
We developed NZ-BeachTopo30, a full-coverage 30 m beach topography dataset for New Zealand, by integrating Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) and Sentinel-2 data with extreme gradient boosting (XGBoost). It expands valid intertidal coverage by 145.8 % and achieves a 0.94 m root mean square error against airborne light detection and ranging (airborne LiDAR) data, supporting sea-level rise and coastal erosion planning.
We developed NZ-BeachTopo30, a full-coverage 30 m beach topography dataset for New Zealand, by...
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