Snow cover dataset based on optical instrument remote sensing with 1km spatial resolution on the Qinghai-Tibet Plateau (1989-2018)

Snow cover dataset based on optical instrument remote sensing with 1km spatial resolution on the Qinghai-Tibet Plateau (1989-2018)


Snow cover dataset is produced by snow and cloud identification method based on optical instrument observation data, covering the time from 1989 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 under clear sky or transparent thin cloud is covered by snow. The input data sources include AVHRR L1 data of NOAA and MetOp serials of satellites, and L1 data corresponding to AVHRR channels taken from TERRA/MODIS. Decision Tree algorithm (DT) with dynamic thresholds is employed independent of cloud mask and its cloud detection emphasizes on reserving snow, particularly under transparency cirrus. It considers a variety of methods for different situations, such as ice-cloud over the water-cloud, snow in forest and sand, thin snow or melting snow, etc. Besides those, setting dynamic threshold based on land-surface type, DEM and season variation, deleting false snow in low latitude forest covered by heavy aerosol or soot, referring to maximum monthly snowlines and minimum snow surface brightness temperature, and optimizing discrimination program, these techniques all contribute to DT. DT discriminates most snow and cloud under normal circumstances, but underestimates snow on the Qinghai-Tibet Plateau in October. Daily product achieves about 95% 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 five fields: space based optical instrument and snow cover product code, satellite name, product time, coverage area, version number, etc., with“hdf”data format suffix, such as the form of AVH10A1_SATENM_ 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), 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., Chu, D. (2019). Snow cover dataset based on optical instrument remote sensing with 1km spatial resolution on the Qinghai-Tibet Plateau (1989-2018). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Snow.tpdc.270465. CSTR: 18406.11.Snow.tpdc.270465. (Download the reference: RIS | Bibtex )

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Support Program

Construction of Snow Remote Sensing Dataset for Climate in the Qinghai-Tibet Plateau (No:GYHY201206040)

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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: 6,739 MB
  • Views: 8083
  • Downloads: 248
  • Access: Open Access
  • Temporal coverage: 1989-01-17 To 2019-01-16
  • Updated time: 2021-04-19
Contacts
: ZHENG Zhaojun   CHU Duo  

Distributor: A Big Earth Data Platform for Three Poles

Email: poles@itpcas.ac.cn

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