This dataset is land surface phenology estimated from 16 days composite MODIS NDVI product (MOD13Q1 collection6) in the Three-River-Source National Park from 2001 to 2020. The spatial resolution is 250m. The variables include Start of Season (SOS) and End of Season (EOS). Two phenology estimating methods were used to MOD13Q1, polynomial fitting based threshold method and double logistic function based inflection method. There are 4 folders in the dataset. CJYYQ_phen is data folder for source region of the Yangtze River in the national park. HHYYQ_phen is data folder for source region of Yellow River in the national park. LCJYYQ_phen is data folder for source region of Lancang River in the national park. SJY_phen is data folder for the whole Three-River-Source region. Data format is geotif. Arcmap or Python+GDAL are recommended to open and process the data.
WANG Xufeng
The data set contains the monthly net primary productivity data of 2012-2015. The data is based on the temperature, precipitation, solar radiation and other climatic elements of the daily value data set of China's surface climate data, as well as the data of evapotranspiration et, potential PET, photosynthetic effective absorption ratio FPAR, NDVI and maximum light utilization rate, which are calculated by CASA model. The calculation results are verified by the data of Sanjiangyuan sampling point, The correlation coefficient is 0.718. The data set can be directly used for the analysis of grassland vegetation change in the Qinghai Tibet Plateau, providing the basis for dynamic monitoring of grassland change, and for the management of Grassland Change in the Qinghai Tibet Plateau.
FAN Jiangwen, XIN Liangjie, ZHANG Haiyan, YUAN Xiu
This data set is the plant collection and distribution site information of Three-River-Source National Park investigated by Northwest Plateau Biology Institute of Chinese Academy of Sciences. The data set covers the period from 2008 to 2017, and the survey covers theThree-River-Source National Park. The survey contents include information such as collection date, number, family, genus, species, survey date, collection place, collector, longitude, latitude, altitude, habitat, appraiser, etc. Three parks of the national park were investigated respectively. 88 species of vegetation belonging to 56 genera and 24 families were investigated in the Yangtze River Source Park, with 116 records in total. Vegetation of 110 species in 64 genera and 26 families was investigated in the Yellow River Source Park, with 159 records in total. The vegetation of 30 species in 22 genera and 12 families was investigated in Lancang River Source Park, with a total of 33 records.
GAO Qingbo
Monthly meteorological data of Sanjiangyuan includes 32 national standard meteorological stations. There are 26 variables: average local pressure, extreme maximum local pressure, date of extreme maximum local pressure, extreme minimum local pressure, date of extreme minimum local pressure, average temperature, extreme maximum temperature, date of extreme maximum temperature, extreme minimum temperature and date of extreme minimum temperature, average temperature anomaly, average maximum temperature, average minimum temperature, sunshine hours, percentage of sunshine, average relative humidity, minimum relative humidity, date of occurrence of minimum relative humidity, precipitation, days of daily precipitation >=0.1mm, maximum daily precipitation, date of maximum daily precipitation, percentage of precipitation anomaly, average wind speed, maximum wind speed, date of maximum wind speed, maximum wind speed, wind direction of maximum wind speed, wind direction of maximum wind speed and occurrence date of maximum wind speed. The data format is txt, named by the site ID, and each file has 26 columns. The names and units of each column are explained in the SURF_CLI_CHN_MUL_MON_readme.txt file. Projection information: Albers isoconic projection Central meridian: 105 degrees First secant: 25 degrees First secant: 47 degrees West deviation of coordinates: 4000000 meters
ZHU Weiwei
Based on the average NDVI (spatial resolution 250m) of MODIS during the growing season from 2000 to 2018, the trend of NDVI was calculated by using Mann-Kendall trend detection method. Three parks of Three River Source National Park are calculated (CJYQ: Yangtze River Park; HHYYQ: Yellow River Park; LCJYQ: Lancang River Park). CJYQ_NDVI_trend_2000_2018_ok.tif: Changjiang Source Park NDVI trend. CJYQ_NDVI_trend_2000_2018_ok_significant.tif: Changjiang Source Park NDVI change trend, excluding the area that is not significant (p > 0.05). CJYYQ_gs_avg_NDVI_2000.tif: The average NDVI of the Yangtze River Source Park in 2000 growing season. Unit NDVI changes every year.
WANG Xufeng
The method of aboveground biomass of grassland is zonal classification model. The data years were 2000, 2010 and 2015, and the fresh vegetation weight was based on the first ten days of August. Above-ground biomass is defined as the total amount of organic matter of vegetation living above the ground in a unit area. Unit: g/m². This data set is calculated from a statistical model based on the MODIS vegetation index by the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences. The spatial resolution is 250 m x 250 m. The data set is an important data source for vegetation monitoring in Three River Source National Park. Projection information: Albers isoconic projection Central meridian: 105 degrees First secant: 25 degrees First secant: 47 degrees West deviation of coordinates: 4000000 meters
ZHU Weiwei
The data set is NDVI data of long time series acquired by NOAA's Advanced Very High Resolution Radiometer (AVHRR) sensor. The time range of the data set is from 1982 to 2015. In order to remove the noise in NDVI data, maximum synthesis and multi-sensor contrast correction are carried out. A NDVI image is synthesized every half month. The data set is widely used in the analysis of long-term vegetation change trend. The data set is cut out from the global data set, so as to carry out the research and analysis of the source areas of the three rivers separately. The data format of this data set is GeoTIFF with spatial resolution of 8 km and temporal resolution of 2 weeks, ranging from 1982 to 2015. Data transfer coefficient is 10000, NDVI = ND/10000.
National Oceanic and Atmospheric Administration
The data set is MODIS vegetation index data (MOD13Q1). The source areas of the three rivers are extracted to carry out the research and analysis of the source areas of the three rivers separately. MOD13Q1 is a 16-day composite vegetation index, including normalized vegetation index (NDVI) and enhanced vegetation index (EVI). The spatial scope of Sanjiang Source covers two MODIS files (h25v05 and h26v05). Data storage format is hdf. Each file contains 12 bands: Normalized Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Data Quality (VI Quality), Red Reflectance, Near Infrared Reflectance (NIR Reflectance), Blue Reflectance, Mid Infrared Reflectance, Observation. Viewzenith angle, sun zenith angle, relative azimuth angle, composite day of the year and pixel reliability. The data format of this data set is hdf, spatial resolution is 250m, temporal resolution is 16 days, time range: February 2000 to October 2018.
Kamel Didan*, Armando Barreto Munoz, Ramon Solano, Alfredo Huete
The data set is extracted from the NDVI data of long time series acquired by VEGETATION sensor on SPOT satellite. The time range of the data set is from May 1998 to 2013. In order to remove the noise in NDVI data, the maximum synthesis is carried out. A NDVI image is synthesized every 10 days. The data set is cut out from the global data set, so as to carry out the research and analysis of the source areas of the three rivers separately. The data format of this data set is geotiff, spatial resolution is 1 km, temporal resolution is 10 days, time range: May 1998 to December 2013.
Image Processing Centre for SPOT-VGT
The data set is NDVI data of long time series acquired by SeaWiFS. The time range of the data set is from September 1997 to 2007. In order to remove the noise in NDVI data, the maximum synthesis is carried out. A NDVI image is synthesized every 15 days. The data set is cut out from the global data set, so as to carry out the research and analysis of the source areas of the three rivers separately. The data format of this data set is geotiff, spatial resolution is 4 km, temporal resolution is 15 days, time range: 256 days in 1997 to 365 days in 2007.
Charles R. Mcclain
The data set includes estimated data on the SOS (start of season) and the EOS (end of season) of vegetation in Sanjiangyuan based on the MODIS 16-day synthetic NDVI product (MOD13A2 collection 6). Two common phenological estimation methods were adopted: the threshold extraction method based on polynomial fitting (the term “poly” was included in the file names) and the inflection point extraction method based on double logistic function fitting (the term “sig” was included in the file names). These data can be used to analyse the relationship between vegetation phenology and climate change. The temporal coverage ranges from 2001 to 2014, and the spatial resolution is 1 km.
WANG Xufeng
The data set includes the estimated data of the SOS (start of season) and the EOS (end of season) of vegetation in Sanjiangyuan based on 10-day synthetic NDVI products from the SPOT satellite. Two common phenological estimation methods were adopted: the threshold extraction method based on polynomial fitting (the term “poly” was included in the file names) and the inflection point extraction method based on double logistic function fitting (the term “sig” was included in the file names). These data can be used to analyse the relationship between vegetation phenology and climate change. The temporal coverage is from 1999 to 2013, and the spatial resolution is 1 km.
WANG Xufeng
The data set includes the estimated data on the SOS (start of season) and the EOS (end of season) of vegetation in Sanjiangyuan based on GIMMS3g version 1.0, the latest version of the GIMMS NDVI data set. Two common phenological estimation methods were adopted: the threshold extraction method based on polynomial fitting (the term “poly” was included in the file names) and the inflection point extraction method based on double logistic function fitting (the term “sig” was included in the file names). These data can be used to analyse the relationship between vegetation phenology and climate change. The temporal coverage ranges from 1982 to 2015, and the spatial resolution is 8 km.
WANG Xufeng
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