15 citations as recorded by crossref.

1. Impact of a Surface Ice Lid on the Optical Properties of Melt Ponds P. Lu et al. 10.1029/2018JC014161
2. Snow Depth Retrieval on Arctic Sea Ice Using Under-Ice Hyperspectral Radiation Measurements P. Anhaus et al. 10.3389/feart.2021.711306
3. Comparison of Passive Microwave Data with Shipborne Photographic Observations of Summer Sea Ice Concentration along an Arctic Cruise Path Q. Wang et al. 10.3390/rs11172009
4. Retrieval of snow layer and melt pond properties on Arctic sea ice from airborne imaging spectrometer observations S. Rosenburg et al. 10.5194/amt-16-3915-2023
5. Overview: Recent advances in the understanding of the northern Eurasian environments and of the urban air quality in China – a Pan-Eurasian Experiment (PEEX) programme perspective H. Lappalainen et al. 10.5194/acp-22-4413-2022
6. A New Algorithm for Sea Ice Melt Pond Fraction Estimation From High‐Resolution Optical Satellite Imagery M. Wang et al. 10.1029/2019JC015716
7. The internal melting of landfast sea ice in Prydz Bay, East Antarctica J. Zhao et al. 10.1088/1748-9326/ac76d9
8. Arctic summer sea ice phenology including ponding from 1982 to 2017 X. Chen et al. 10.1007/s13131-022-1993-5
9. A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data M. König & N. Oppelt 10.5194/tc-14-2567-2020
10. Evaporation over a glacial lake in Antarctica E. Shevnina et al. 10.5194/tc-16-3101-2022
11. Multi-Scale Polar Object Detection Based on Computer Vision S. Ding et al. 10.3390/w15193431
12. Mapping the Bathymetry of Melt Ponds on Arctic Sea Ice Using Hyperspectral Imagery M. König et al. 10.3390/rs12162623
13. Monitoring evolution of melt ponds on first-year and multiyear sea ice in the Canadian Arctic Archipelago with optical satellite data Q. Li et al. 10.1017/aog.2020.24
14. Comparison of Pond Depth and Ice Thickness Retrieval Algorithms for Summer Arctic Sea Ice H. Zhang et al. 10.3390/rs14122831
15. Ice floe segmentation and floe size distribution in airborne and high-resolution optical satellite images: towards an automated labelling deep learning approach Q. Zhang & N. Hughes 10.5194/tc-17-5519-2023