EGU25-20632, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-20632
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Wednesday, 30 Apr, 14:00–15:45 (CEST), Display time Wednesday, 30 Apr, 08:30–18:00
 
vPoster spot 4, vP4.3
SnowMapPy v1.0: A Python Package for Automated Snow Cover Mapping and Monitoring in Mountain Regions 
Haytam Elyoussfi1, Abdelghani Boudhar4,2,1, Salwa Belaqziz3,1, Mostafa Bousbaa1,5, Hatim Bechri1, Eric A Sproles6,7, and Fatima Benzhair3
Haytam Elyoussfi et al.
  • 1Center for Remote Sensing Applications (CRSA), Mohammed VI Polytechnic University (UM6P), Benguerir 43150, Morocco.
  • 2Data4Earth Laboratory, Faculty of Sciences and Technics, University Sul-tan Moulay Slimane, Beni Mellal 23000, Morocco.
  • 3Laboratory of Computer Systems and Vision (LabSIV), Department of Computer Science, Faculty of Science, Ibn Zohr University, Agadir 80000, Morocco.
  • 4L3G Laboratory, Faculty of Sciences and Techniques, Cadi Ayyad University, Marrakech, Morocco.
  • 5Institute of Methodologies for Environmental Analysis, CNR-IMAA, Tito, 85050, Italy.
  • 6Department ofEarth Sciences, MT State University, Bozeman, Montana.
  • 7Geospatial Core Facility, Montana State University, Bozeman, Montana.

SnowMapPy is a Python-based package developed to streamline the collection, preparation, and analysis of MODIS NDSI data, specifically from the Terra and Aqua satellite products. By automating essential steps (data clipping, reprojection, filtering, and time series generation), SnowMapPy improves the efficiency and precision of snow hydrology research. The protocol allows users to work with both local and Google Earth Engine cloud-based datasets, enabling flexible data acquisition and processing tailored to the needs of snow hydrology, water resource management, and climate change studies. Designed for accessibility and flexibility, SnowMapPy supports large-scale, high-resolution snow cover analysis with minimal configuration. The package facilitates customized workflows through its modular structure, making it a valuable tool for researchers aiming to understand snow dynamics and their impact on seasonal water resources. 

How to cite: Elyoussfi, H., Boudhar, A., Belaqziz, S., Bousbaa, M., Bechri, H., Sproles, E. A., and Benzhair, F.: SnowMapPy v1.0: A Python Package for Automated Snow Cover Mapping and Monitoring in Mountain Regions , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20632, https://doi.org/10.5194/egusphere-egu25-20632, 2025.