Daily cloud-free MODIS NDSI and snow phenology dataset over High Mountain Asia (2000-2021)

Daily cloud-free MODIS NDSI and snow phenology dataset over High Mountain Asia (2000-2021)


Snow cover is an important component of the cryosphere and an indispensable variable in the scientific research of global change and Earth system. The distribution range and phenological information of snow cover are important indicators to measure the variation characteristics of snow cover, and also important parameters for snow melting runoff simulation in the hydrological model of cold regions. The High Mountain Asia is the source of many international rivers, and also the hot spot of global climate change research; The ecological and environmental problems caused by the change of ice and snow in the region, such as the reduction of water resources, the increase of extreme weather events, and the frequent occurrence of disasters, have attracted extensive attention from all countries. Therefore, it is very important for climate change research, water resources management, disaster early warning and prevention to accurately obtain long-term snow distribution and snow phenology data in High Mountain Asia .

The daily cloudless MODIS normalized snow cover index (NDSI) product (2000-2021500 m) in the High Mountain Asia is based on the MODIS daily snow cover product (including Terra Morning Star data product MOD10A1 and Aqua Afternoon Star data product MYD10A1, C6 versions), and is processed by the same day afternoon star data fusion and cubic spline interpolation cloud removal algorithm; Among them, when there was only Morningstar data product MOD10A1 from 2000 to 2002, the cubic spline interpolation algorithm was directly used for cloud removal. The snow cover phenological data set for hydrological years 2002-2020 is prepared based on cloudless MODIS NDSI products in hydrological years, including three parameters: snow onset date (SOD), snow end date (SED) and snow duration days (SDD). This data set has reliable accuracy.


File naming and required software

MODIS NDSI data name: YYYYddd_ HMA_ MODIS_ NDSI_ 0.5km.img, where YYYY represents the year and ddd represents Julian day (001-365/366); Example: 2021009_ HMA_ MODIS_ NDSI_ 0.5km.img refers to MODIS NDSI products with a spatial resolution of 0.5km in the High Mountain Asia on January 9, 2021.
Name of snow cover phenological data: YYYY_ HMA_ MODIS_ SOD/SED/SDD_ 0.5km. Tif, where YYYY represents the year, SOD is the snow onset date, SED is the snow end date, and SDD is the snow duration days ; For example: 2020_ HMA_ MODIS_ SOD_ 0.5km.tif refers to the MODIS snow onset date of the Asian alpine region in 2020 hydrological year (2020/9/1 to 2021/8/31) with a spatial resolution of 0.5km.
The file can be opened and viewed by ENVI or ARCGIS and other software.


Data Citations Data citation guideline What's data citation?
Cite as:

Tang, Z., Deng, G. (2022). Daily cloud-free MODIS NDSI and snow phenology dataset over High Mountain Asia (2000-2021). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Cryos.tpdc.272836. CSTR: 18406.11.Cryos.tpdc.272836. (Download the reference: RIS | Bibtex )

Related Literatures:

1. Tang, Z., Deng, G., Hu, G., Zhang, H., Pan, H., & Sang, G. (2022). Satellite observed spatiotemporal variability of snow cover and snow phenology over High Mountain Asia from 2002 to 2021. Journal of Hydrology, 613, 128438.( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.


Support Program

the State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy Sciences (No. SKLCS-OP-2020-08)

National Natural Science Foundation of China (No. 41871058),

Copyright & License

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.


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


Related Resources
Comments

Current page automatically show English comments Show comments in all languages

Download Follow
Keywords
Geographic coverage
East: 107.00 West: 64.00
South: 23.00 North: 57.00
Details
  • Temporal resolution: Daily
  • Spatial resolution: 100m - 1km
  • File size: 75,468 MB
  • Views: 2444
  • Downloads: 147
  • Access: Open Access
  • Temporal coverage: 2000-02-24 To 2021-12-31
  • Updated time: 2022-09-29
Contacts
: TANG Zhiguang    DENG Gang   

Distributor: A Big Earth Data Platform for Three Poles

Email: poles@itpcas.ac.cn

Attachments
Export metadata