Snow cover dataset based on multi-source remote sensing products blended with 1km spatial resolution on the Qinghai-Tibet Plateau (1995-2018)

Snow cover dataset based on multi-source remote sensing products blended with 1km spatial resolution on the Qinghai-Tibet Plateau (1995-2018)


This dataset is blended by two other sets of data, snow cover dataset based on optical instrument remote sensing with 1km spatial resolution on the Qinghai-Tibet Plateau (1989-2018) produced by National Satellite Meteorological Center, and near-real-time SSM/I-SSMIS 25km EASE-grid daily global ice concentration and snow extent (NISE, 1995-2018) provided by National Snow and Ice Data Center (NSIDC, U.S.A). It covers the time from 1995 to 2018 (two periods, from January to April and from October to December) and the region of Qinghai-Tibet Plateau (17°N-41°N, 65°E-106°E) with daily product, which takes equal latitude and longitude projection with 0.01°×0.01° spatial resolution, and characterizes whether the ground is covered by snow. The input data sources include daily snow cover products generated by NOAA/AVHRR, MetOp/AVHRR, and alternative to AVHRR taken from TERRA/MODIS corresponding observation, and snow extent information of NISE derived from observation by SSM/I or SSMIS of DMSP satellites. The processing method of data collection is as following: first, taking 1km snow cover product from optical instruments as initial value, and fully trusting its snow and clear sky without snow information; then, under the aid of sea-land template with relatively high resolution, replacing the pixels or grids where is cloud coverage, no decision, or lack of satellite observation, by NISE's effective terrestrial identification results. For some water and land boundaries, there still may be a small amount of cloud coverage or no observation data area that can’t be replaced due to the low spatial resolution of NISE product. Blended daily snow cover product achieves about 91% average coincidence rate of snow and non-snow identification compared to ground-based snow depth observation in years. The dataset is stored in the standard HDF4 files each having two SDSs of snow cover and quality code with the dimensions of 4100-column and 2400-line. Complete attribute descriptions is written in them.


File naming and required software

The data file is named by six fields: space based optical instrument and snow cover product code, satellite name, NISE product code, product time, coverage area, version number, etc., with“hdf”data format suffix, such as the form of AVH10A1_SATENM_ NISE_ yyyymmdd_QTP_V01.hdf, where AVH10A1 indicates daily snow cover product generated based on AVHRR or corresponding instrument channel observation data, SATENM is the satellite name (values are NOAA11, NOAA14, NOAA16, NOAA17, EOSMLT and MetOpA), NISE is product code of “Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration and Snow Extent”, yyyymmdd indicates the date, QTP indicates the Qinghai-Tibet Plateau, and V01 indicates the version number. The data is stored in the standard HDF4 format and can be viewed by ENVI, ARCGIS, HDFView, Hdfexp and other software. Users can also write programs to process and use it.


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Cite as:

Zheng, Z., Cao, G. (2019). Snow cover dataset based on multi-source remote sensing products blended with 1km spatial resolution on the Qinghai-Tibet Plateau (1995-2018). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Snow.tpdc.270102. CSTR: 18406.11.Snow.tpdc.270102. (Download the reference: RIS | Bibtex )

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Database construction of climate and ecological environment parameters on the Qinghai-Tibet Plateau (No:GYHY201306017)

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License: This work is licensed under an Attribution 4.0 International (CC BY 4.0)


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Keywords
Geographic coverage
East: 106.00 West: 65.00
South: 17.00 North: 41.00
Details
  • Temporal resolution: Daily
  • Spatial resolution: km
  • File size: 4,079 MB
  • Views: 8932
  • Downloads: 360
  • Access: Open Access
  • Temporal coverage: 1995-10-18 To 2019-01-17
  • Updated time: 2021-04-19
Contacts
: ZHENG Zhaojun   CAO Guangzhen  

Distributor: A Big Earth Data Platform for Three Poles

Email: poles@itpcas.ac.cn

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