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The dataset contains phenological camera observation data collected at the Arou Superstation in the midstream of the Heihe integrated observatory network from June 13 to November 16, 2018. The instrument was developed with data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures high-quality data with a resolution of 1280×720 by looking-downward. The calculation of the greenness index and phenology are following 3 steps: (1) calculate the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) according to the region of interest, (2) perform gap-filling for the invalid values, filtering and smoothing, and (3) determine the key phenological parameters according to the growth curve fitting (such as the growth season start date, Peak, growth season end, etc.) There are also 3 steps for coverage data processing: (1) select images with less intense illumination, (2) divide the image into vegetation and soil, and (3) calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (Gcc).

Please refer to Liu et al. (2018) for sites information in the Citation section.

Data file naming and use method

Picture from phenology camera: Station+yyyy+mm+dd+hhmm, for example, Sidaoqiao201806230800.jpg
Post processing data: Year+** observatory network+ site no + Phenology camera.

Required Data Citation View Data Cite Help About Data Citation

1. Liu, J. G., & Pattey, E. (2010). Retrieval of leaf area index from top-of-canopy digital photography over agricultural crops. Agricultural and Forest Meteorology, 150(11), 1485-1490.( View Details | Bibtex)

2. Liu, Y. K., Mu, X. H., Wang, H. X., & Yan, G. J. (2012). A novel method for extracting green fractional vegetation cover from digital images. Journal of Vegetation Science, 23, 406–418.( View Details | Download | Bibtex)

3. Song, W. J., Mu, X. H., Yan, G. J., & Huang, S. (2015). Extracting the Green Fractional Vegetation Cover from Digital Images Using a Shadow-Resistant Algorithm (SHAR-LABFVC). Remote Sensing, 7, 10425-10443.( View Details | Download | Bibtex)

LIU Shaomin, QU Yonghua, XU Ziwei. Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (phenology camera observation data set of mixed forest superstation, 2018). National Tibetan Plateau Data Center, 2019. doi: 10.11888/Geogra.tpdc.270149. (Download the reference： RIS | Bibtex )

Using this data, you must reference article references listed in the Required Data Citation and reference data

Support Program

Pan-Third Pole Environment Study for a Green Silk Road-A CAS Strategic Priority A Program (No:XDA20000000)

User Limit

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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