Data naming format: the data set consists of 37 folders from 1978 to 2015. Each folder includes the daily surface freeze-thaw classification results of the current year. The daily surface freeze-thaw classification results are stored in the format of TXT. The naming rules are "smmr-ftyyyddd. TXT" or "ssmi-ftyyyddd. TXT" or "ssms-ftyyyddd. TXT", where yyyy represents the year and DDD represents the Julian day.
Data reading mode: all ASCII TXT files in this data set can be opened directly with a text program (such as notepad).In addition to the header file, the main content is the numerical representation of the freezing-thawing state of the surface: 1 represents freezing, 2 represents melting, 3 represents desert, and 4 represents precipitation.If the graph is to be displayed, it is recommended to use ArcView + 3D or Spatial Analyst extension module to read. In the process of reading, the grid file will be generated, and the grid file displayed is the graphical expression of the ASCII file.
JIN Rui, LI Xin. Long-term surface soil freeze-thaw states dataset of China using the dual-index algorithm (1978-2015). National Tibetan Plateau Data Center, 2011. doi: 10.11888/Geocry.tpdc.270029. (Download the reference： RIS | Bibtex )Related Literatures:
1. Jin,R, Zhang,T,Y, Li,X, Yang,X,G, Ran,Y,H.(2015). Mapping surface soil freeze-thaw cycles in china based on smmr and ssm/i brightness temperatures from 1978 to 2008. Arctic, Antarctic, and Alpine Research, 47(2), 213-229.( View Details | Bibtex)
2. Xie, Y.M., Jin, R, & Yang, X.G. (2013). Algorithm development of monitoring daily near surface freeze/thaw cycles using amsr-e brightness temperatures. Remote Sensing Technology and Application, 28(2).( View Details | Download | Bibtex)
Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.
To respect the intellectual property rights, protect the rights of data authors,expand servglacials 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the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results).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.
Example of acknowledgement statement is included below: The data set is provided by National Tibetan Plateau Data Center (http://data.tpdc.ac.cn).
License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)
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