The dataset of setting of the sampling plots and stripes in the Linze station foci experimental area was as follows: (1) Wulidun farmland quadrates (90m×90m), which was divided into nine subplots (30m×30m). Numbering of Cold and Arid Regions Environmental and Engineering Research Institute was different from that of BNU, in which the former was 1-9 from south to north, and the latter was A-I from north to south. (2) the west-east desert strip, which was composed of 20 neighbouring pairs of subplots (30×30m). They were numbered S0-S20 from the south corner on and N0-N20 from the north corner on; the common corner points in the middle were numbered M0-M20. Corner points were measured during the satellite or airplane overpass. (3) the north-south desert strip, which was composed of nine non-conterminous subplots (40m×40m, numbered from A1-A9) at intervals of 60m. Corner points and center points were measured during the satellite or airplane overpass. (4) three quadrates (30m×30m) of the transit zone, LY06，LY07，LY08 strips. Samples were selected following the zigzag line from the northwest corner and numbered 1-9. (5) the poplar forest (90×90m), which was divided into 9 subplots (30m×30m). (6) 6 desert strips with 17 sample points each. (7) maize plots (3m×3m) inside Linze station. Data including coordinates of each sample point were archived as Excel files.

The dataset of sun photometer observations was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas. 24 times observations were carried out by CE318 from BNU (at 1020nm, 936nm, 870nm, 670nm and 440nm, and column water vapor by 936 nm data) and from Institute of Remote Sensing Applications, CAS (at 1640nm, 1020nm, 936nm, 870nm, 670nm, 550nm, 440nm, 380nm and 340nm, and column water vapor by 936 nm data) on May 20, 23, 25 and 27, Jun. 4, 6, 16, 20, 22, 23, 27 and 29, Jul. 1, 7 and 11, 2008. Those atmospheric measurements synchronized with airborne (i.e. WiDAS, OMIS) and spaceborne sensors (i.e. TM, ASTER,CHRIS and Hyperion) Accuracy of CE318 could be influenced by local air pressure, instrument calibration parameters, and convertion factors. (1) Most air pressure was derived from elevation-related empiricism, which was not reliable. For more accurate result, simultaneous data from the weather station are needed. (2) Errors from instrument calibration parameters. Field calibration based on Langly or interior instrument calibrationcin the standard light is required. (3) Convertion factors for retrieval of aerosol optical depth and the water vapor of the water vapor channel were also from empiricism, and need further checking. Raw data were archived in k7 format and can be opened by ASTPWin. ReadMe.txt is attached for details. Preprocessed data (after retrieval of the raw data) in Excel format are on optical depth, Rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number. Langley was used for the instrument calibration. Two parts are included in CE318 result data (see Geometric Positions and the Total Optical Depth of Each Channel and Rayleigh Scattering and Aerosol Optical Depth of Each Channel).

On August 20, 2018, a DJI Elf 4 UAV camera was used to take aerial photographs of the alpine meadow sample in Qumali County, which is located in the source area of the Yangtze River. A total of 31 routes were set up. The flight altitude was 100 m, and the overlap degree of adjacent photographs was not less than 70%. A total of 664 aerial photographs were obtained and stored in the Drone Photoes of Qumalai (2018) folder.

This data comes from the National Geographic Information Resources Catalogue Service System, which was provided free to the public by the National Basic Geographic Information Center in November 2017. In order to use the data more conveniently, the source of the three rivers is spliced and cut as a whole, so as to facilitate the use of the source area of the three rivers. The data trend is 2017. This data set is composed of 1:1 million residential areas in Sanjiangyuan area, including residential land (RESA) and residential place (RESP) layers, RESP residential area (point) layers, including ordinary houses, grazing areas and so on.

This data comes from the National Geographic Information Resources Catalogue Service System, which was provided free to the public by the National Basic Geographic Information Center in November 2017. We have spliced and cut the source of the three rivers as a whole, so as to facilitate the use of the study of the source area of the three rivers. The data trend is 2015. This data set consists of 1:250,000 residential areas in Sanjiangyuan area, including two layers of residential land (RESA) and residential place (RESP). Resident land (RESA) mainly refers to the outline of surface residential area, and residential place (RESP) includes ordinary houses, shacks, caves, Mongolian yurts, grazing places, etc. Names and definitions of RESA attribute items: Attribute Item Description Fill in Example GB National Standard Classification Code 310200 Name and Definition of Residential Place (RESP) Attribute Item: Attribute Item Description Fill in Example GB National Standard Classification Code 310200 ANGLE Angle 67

This data was originated from the National Geographic Information Resources Catalogue Service System, which was provided free to the public by the National Basic Geographic Information Center in November 2017. We have spliced and cut the source of the three rivers as a whole, so as to facilitate the use of the study of the source area of the three rivers. The data trend is 2017. This data set is AGNP data of 1:1 million residential place names in Sanjiangyuan area, including administrative place names at all levels and urban and rural residential place names. Names and Definitions of Attribute Items of Residential Place Name Data (AGNP): Attribute Item Description Fill in Example CLASS Geographical Name Classification Code AK NAME Name Quanqu Village PINYIN Chinese Pinyin Quanqucun GNID Place Name Code 632524000000 XZNAME Township Name Ziketan Township

This data originates from the National Geographic Information Resources Catalogue Service System, which was provided free to the public in November 2017. We have spliced and cut the source of the three rivers as a whole, so as to facilitate the use of the study of the source area of the three rivers. This data set is composed of 1:1 million water coefficient data in Sanjiangyuan area, including three layers: water system surface (HYDA), water system line (HYDL) and water system point (HYDP). The water system surface (HYDA) includes lakes, reservoirs and double-line rivers; the water system line (HYDL) includes single-line rivers, ditches, river structure lines; and the water system point (HYDP) includes springs and wells. HYDA Attribute Item Name and Definition: Attribute Item Description Fill in Example GB National Standard Classification Code 210101 HYDC Water System Name Code KJ2103 NAME Name Heihe WQL Water Quality PERIOD Seasonal Month 7-9 TYPE Type Pass HYDL property item name and definition: Attribute Item Description Fill in Example GB National Standard Classification Code 210101 HYDC Water System Name Code KJ2103 NAME Name Heihe PERIOD Seasonal Month 7-9 HYDP property item name and definition: Attribute Item Description Fill in Example GB National Standard Classification Code 210101 NAME TYPE Type ANGLE Angle 75 Water coefficient data GB code and its meaning: Attribute Item Code Description GB 210101 Surface rivers 210200 Seasonal River 210300 Dry River 230101 Lakes 230102 Ponds 230200 Seasonal Lake 230300 Dry Lake 240101 Build Reservoir 240102 Built-in Reservoir

On August 22, 2018, in the Lancang River Source Park, a camera was carried on DJI Elf 4 UAV to take aerial photographs of the sample area. A total of 20 routes (5 missing routes) were set up, flying at a height of 100 m, and the overlap degree of adjacent photos was not less than 70%. A total of 1160 aerial photographs were obtained and stored in two folders of "100 MEDIA" and "101 MEDIA".

This data set was derived from MODIS version 005 and the IMS data set. It is a daily cloudless snow area product processed by cloud removal. Value range: 0%-100%. 200: snow; 100: lake ice; 25: land; 37: sea. The spatial resolution is 0.005 degrees (approximately 500 m), and the temporal coverage is from July 5, 2002, to December 31, 2014.