High altitude Asia is a high altitude region with the Qinghai Tibet Plateau as the main region. It is an important distribution area of alpine snow in middle and low latitudes. The dynamic change of snow cover has an important impact on water and energy balance and regional climate. Due to the short occurrence time and thin snow layer of the seasonal snow cover in the Qinghai Tibet Plateau, the dynamic monitoring data of snow cover in daily time scale is urgently needed in the understanding of water cycle and other issues. Based on the MODIS normalized snow cover index data with a spatial resolution of 500m, combined with the advantages of terrain and various snow cover estimation algorithms under cloud cover, this data set realizes the re estimation of snow cover under cloud cover, meets the production requirements of daily less cloud (< 10%) data products in High Asia, and constructs the MODIS daily snow cover degree in High Asia from 2002 to 2018 According to the collection. Based on the comparison of cloud amount distribution and total snow area, the results show that the spatial and temporal characteristics of the product are consistent with the binary product. Taking the winter of 2013 as an example, when the snow cover is more than 50%, the correlation can reach 0.8628. This data set can provide daily snow cover data for snow dynamic monitoring, climate and environment, hydrology and energy balance, disaster assessment and other studies in High Asia. At present, the data has been used by students of Sun Yat sen University, Institute of Qinghai Tibet Plateau, Chinese Academy of Sciences, Institute of remote sensing, Anhui Normal University, Nanjing University, Hehai University, and Henan University of technology for writing master's and doctoral dissertations, and for data accuracy evaluation with other snow products.
Remote sensing inversion.
This dataset is based on MODIS normalized snow cover index data with a spatial resolution of 500 m, and combines the advantages of terrain and snow cover estimation algorithms under various cloud coverages to realize re-estimation of snow cover under cloud coverages.(Including five steps: synthesis of MODIS upper and lower noon satellite data, synthesis for three consecutive days,"minimum" ice and snow coverage in a short period of time, adjacent three-pixel method, and eight-day maximum land range masking), meeting the production requirements of daily low cloud (<10%) data products in the High Asia region, a MODIS daily snow coverage dataset for the High Asia region from 2002 to 2018 was constructed.
Based on the comparison of cloud amount distribution and total snow area, the results show that the spatial and temporal characteristics of the product are consistent with the binary product. Taking the winter of 2013 as an example, when the snow cover is more than 50%, the correlation can reach 0.8628; the final snow cover product still has a small amount of cloud, but the cloud amount is controlled within 10%
| # | number | name | type |
| 1 | GYHY201206040 | other |
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CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.ncdc.nieer.2020.1660
10.11922/sciencedb.457
