A Merging Algorithm for Regional Snow Mapping over Eastern Canada from AVHRR and SSM/I Data

We present an algorithm for regional snow mapping that combines snow maps derived from Advanced Very High Resolution Radiometer (AVHRR) and Special Sensor Microwave/Imager (SSM/I) data. This merging algorithm combines AVHRR's moderate spatial resolution with SSM/I's ability to penetrate clouds and, thus, benefits from the advantages of the two sensors while minimizing their limitations. First, each of the two detection algorithms were upgraded before developing the methodology to merge the snow mapping results obtained using both algorithms. The merging methodology is based on a membership function calculated over a temporal running window of ±4 days from the actual date. The studied algorithms were developed and tested over Eastern Canada for the period from 1988 to 1999. The snow mapping algorithm focused on the spring melt season (1 April to 31 May). The snow maps were validated using snow depth observations from meteorological stations. The overall accuracy of the merging algorithm is about 86%, which is between that of the new versions of the two individual algorithms: AVHRR (90%) and SSM/I (83%). Furthermore, the algorithm was able to locate the end date of the snowmelt season with reasonable accuracy (bias = 0 days; SD = 11 days). Comparison of mapping results with high spatial resolution snow cover from Landsat imagery demonstrates the feasibility of clear-sky snow mapping with relatively good accuracy despite some underestimation of snow extent inherited from the AVHRR algorithm. It was found that the detection limit of the algorithm is 80% snow cover within a 1 × 1 km pixel.

[1]  Filipe Aires,et al.  Sensitivity of satellite observations to snow characteristics , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[2]  Claudia Notarnicola,et al.  Remote Sensing Snow Cover Maps from Modis Images at 250 M Resolution, Part 1: Algorithm Description , 2022 .

[3]  Dorothy K. Hall,et al.  A prototype MODIS-SSM/I snow-mapping algorithm , 2001 .

[4]  Stefan Dech,et al.  Remote sensing of snow – a review of available methods , 2012 .

[5]  Karem Chokmani,et al.  VALIDATION OF A METHOD FOR SNOW COVER EXTENT MONITORING OVER QUEBEC (CANADA) USING NOAA-AVHRR DATA , 2005 .

[6]  Rune Solberg,et al.  A new global Snow Extent product based on ATSR-2 and AATSR , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[7]  Dorothy K. Hall,et al.  Snow Mapping with the MODIS Aqua Instrument , 2004 .

[8]  Peter Romanov,et al.  An assessment of the differences between three satellite snow cover mapping techniques , 2002 .

[9]  Alexandre Langlois,et al.  Étude de la variation spatio-temporelle du couvert nival par télédétection micro-ondes passives et validation du Modèle Régional Canadien du Climat (MRCC) , 2003 .

[10]  A. Klein,et al.  Improving snow cover mapping in forests through the use of a canopy reflectance model , 1998 .

[11]  D. Hall,et al.  Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data , 1995 .

[12]  Hongjie Xie,et al.  Toward advanced daily cloud-free snow cover and snow water equivalent products from Terra-Aqua MODIS and Aqua AMSR-E measurements , 2010 .

[13]  A. Staniforth,et al.  The Operational CMC–MRB Global Environmental Multiscale (GEM) Model. Part I: Design Considerations and Formulation , 1998 .

[14]  Arnaud Mialon,et al.  SEASONAL SNOW COVER EXTENT FROM MICROWAVE REMOTE SENSING DATA: COMPARISON WITH EXISTING GROUND AND SATELLITE BASED MEASUREMENTS , 2005 .

[15]  Stefan Voigt,et al.  A multichannel threshold technique for NOAA AVHRR data to monitor the extent of snow cover in the Swiss Alps , 1999 .

[16]  Monique Bernier,et al.  Suivi spatio-temporel du couvert nival du Québec à l’aide des données NOAA-AVHRR , 2006 .

[17]  Martti Hallikainen,et al.  Snow Monitoring Using Radar and Optical Satellite Data , 1999 .

[18]  B. Ramsay,et al.  The interactive multisensor snow and ice mapping system , 1998 .

[19]  Alexandre Langlois,et al.  Evaluation of the snow cover variation in the Canadian Regional Climate Model over eastern Canada using passive microwave satellite data , 2004 .

[20]  N. DiGirolamo,et al.  MODIS snow-cover products , 2002 .

[21]  Christine Chen,et al.  Validation of NOAA-Interactive Multisensor Snow and Ice Mapping System (IMS) by Comparison with Ground-Based Measurements over Continental United States , 2012, Remote. Sens..

[22]  A. Staniforth,et al.  The Operational CMC–MRB Global Environmental Multiscale (GEM) Model. Part II: Results , 1998 .

[23]  Kalifa Goita,et al.  Monitoring Dry, Wet, and No-Snow Conditions From Microwave Satellite Observations , 2010, IEEE Geoscience and Remote Sensing Letters.

[24]  Konstantin V. Khlopenkov,et al.  Generating historical AVHRR 1 km baseline satellite data records over Canada suitable for climate change studies , 2005 .

[25]  A. Frei.  A New Generation of Satellite Snow Observations for Large Scale Earth System Studies , 2009 .

[26]  Richard Fernandes,et al.  Validation of VEGETATION, MODIS, and GOES + SSM/I snow‐cover products over Canada based on surface snow depth observations , 2003 .

[27]  Karem Chokmani,et al.  Adaptation of the SNOWMAP algorithm for snow mapping over eastern Canada using Landsat-TM imagery , 2010 .

[28]  Hongjie Xie,et al.  Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements , 2008 .

[29]  René Laprise,et al.  A Semi-Implicit Semi-Lagrangian Regional Climate Model: The Canadian RCM , 1999 .

[30]  Ivan Csiszar,et al.  Automated Monitoring of Snow Cover over North America with Multispectral Satellite Data , 2000 .