Observational farmland ecosystem data in Lhasa on the Tibetan Plateau (2006-2009)

This data set includes the biomass and photosynthesis observational data of the highland spring barley experimental plot at the Lhasa Farm Experimental Station and the meteorological data observationally obtained at the Damxung Grass Experimental Station. The time range is 2006-2009. Biomass observation method: The sampling area of each sample is 25 cm*25 cm. Photosynthetic data observation: The instrument is a LiCor-6400. The biomass data are manually entered according to the record book. The photosynthetic data are automatically recorded by the instrument. The average wind speed, prevailing wind direction, temperature, atmospheric pressure and relative humidity in the daily values of meteorological data are averaged over half-hour data. The precipitation and total radiation data are automatically recorded by the observation system. The observation process of biomass data is in strict accordance with the agronomic method, and it can be applied to the estimation of agricultural productivity. In the process of photosynthetic data observation, the operation of the instrument and the selection of the observation object are strictly in accordance with professional requirements and can be used in photosynthetic parameter simulations estimating plant leaf and productivity. The Tibetan Plateau farmland ecosystem observation data includes: 1) aboveground biomass; 2) CO2 response photosynthetic data; 3) light-response photosynthetic data; and 4) daily meteorological data in Damxung Monitoring Point. Data collection locations: Lhasa Agricultural Ecology Experimental Station, Chinese Academy of Sciences, Longitude: 91°20’, Latitude: 29°41’, Altitude: 3688 m and Damxung Alpine Meadow Carbon Flux Observation Station, Longitude: 91°05′, Latitude: 30°25′, Altitude: 4333 m.

0 2019-09-15

The observation dataset of the Guoluo meadow ecosystem on the Tibetan Plateau (2005-2009)

This data set includes biomass survey data observed from the carbon flux station in the Guoluo Army Ranch in Qinghai from 2005 to 2009. Carbon flux data observation method: vorticity-related observation instruments were used for automatic recording; biomass observation method: harvest method, weighing in a 60-degree oven for 48 hours. The carbon flux data were automatically recorded by the instruments and manually checked. Observations and data collection were carried out in strict accordance with the instrument operating specifications and were published in relevant academic journals. During the data observation process, the operation of the instrument and the selection of the observational objects were in strict accordance with professional requirements, and the data could be applied to plant leaf photosynthetic parameter simulation and production estimation. 1) Biological observational data of the Guoluo meadow ecosystem: Date, site number, vegetation type, plot number, aboveground biomass (g/m²), underground biomass (g/m²), total biomass (g/m²) 2) Carbon flux observational data of the Guoluo meadow ecosystem: Site number, date, vegetation type, soil type, water vapor flux (w/m²), carbon flux (mg/m²·S) The fixed point observation data are of high precision.

0 2019-09-15

Vegetation quadrat survey dataset in Maduo County (2016)

These are the vegetation quadrat survey data of the alpine grassland and alpine meadow in Maduo County in September 2016. The dimensions of the square quadrat are 50 cm x 50 cm. The main contents of the survey include coverage, species name, vegetation height, biomass (dry weight and fresh weight), the latitude and longitude coordinates of the quadrat, slope, aspect, slope position, soil type, vegetation type, surface features (litter, gravel, wind erosion, water erosion, saline-alkaline spots, etc.), use patterns, utilization intensity and others.

0 2019-09-15

WATER: Dataset of the survey at the sampling plots in the transit zone between oasis and desert in the Linze station foci experimental area from May to Jun, 2008

The dataset of the survey at the sampling plots in the transit zone between oasis and desert was obtained in the Linze station foci experimental area. Observation items included: (1) soil moisture and temperature of the soil profiles (0-10cm, 10-20cm, 20-30cm and 30-40cm) measured by the cutting ring method (50cm^3, once each layer) and the probe thermometer (15cm, twice each layer) on May 25, 2008. Data were archived as Excel files. (2) biomass (green weight and dry weight, samples from 0.5m×0.5m) with photos measured by the plant harvesting in LY07 quadrate on Jun. 22, 2008. Data were archived as Excel files. (3) vegetation coverage measured by the diagonal method on Jun. 22, 2008. By estimating the coverage along the two diagonals, the total coverage of the plot can be developed. Data were archived as Excel files.

0 2019-09-15

HiWATER: Dataset of fractional vegetation cover and biomass observed in the middle of Heihe River Basin (2013)

The dataset includes the fractional vegetation cover data generated from the stations of crop land, wetland, Gebi desert and desert steppe in Yingke Oasis and biomass data generated from the stations of crop land (corn) and wetland. The observations lasted for a vegetation growth cycle from 19 May, 2012 to 15 September, 2012. 1. Fractional vegetation cover observation 1.1 Observation time 1.1.1 Station of the crop land: The observations lasted from 20 May, 2012 to 15 September, 2012, and in five-day periods for each observation before 31 July and in ten-day periods for each observation after 31 July. The observation time for the station of crop land (corn) are 2013-5-20, 2013-5-25, 2013-5-30, 2013-6-5, 2013-6-10, 2013-6-16, 2013-6-22, 2013-6-27, 2013-7-2, 2013-7-7, 2013-7-12, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 1.1.2 The other four stations: The observations lasted from 20 May, 2012 to 15 September, 2012 and in ten-day periods for each observation. The observation time for the crop land are 2013-5-20, 2013-6-5, 2013-6-16, 2013-6-27, 2013-7-7, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 1.2 method 1.2.1 Instruments and measurement method Digital photography measurement is implemented to measure the FVC. Plot positions, photographic method and data processing method are dedicatedly designed. In field measurements, a long stick with the camera mounted on one end is beneficial to conveniently measure various species of vegetation, enabling a larger area to be photographed with a smaller field of view. The stick can be used to change the camera height; a fixed-focus camera can be placed at the end of the instrument platform at the front end of the support bar, and the camera can be operated by remote control. 1.2.2 Design of the samples Three and two plots with the area of 10×10 m^2 were measured for the station of the crop land and wetland, respectively. One plot with the area of 10×10 m^2 was measured for the other three stations. Shoot 9 times along two perpendicularly crossed rectangular-belt transects. The picture generated of each time is used to calculate a FVC value. “True FVC” of the plot is then acquired as the average of these 9 FVC values. 1.2.3 Photographic method The photographic method used depends on the species of vegetation and planting pattern. A long stick with the camera mounted on one end is used for the stations of crop land and wetland. For the station of the crop land, rows of more than two cycles should be included in the field of view (<30), and the side length of the image should be parallel to the row. If there are no more than two complete cycles, then information regarding row spacing and plant spacing are required. The FVC of the entire cycle, that is, the FVC of the quadrat, can be obtained from the number of rows included in the field of view. For other three stations, the photos of FVC were obtained by directly photographing for the lower heights of the vegetation. 1.2.4 Method for calculating the FVC The FVC calculation was implemented by the Beijing Normal University. The detail method can be found in the reference below. Many methods are available to extract the FVC from digital images, and the degree of automation and the precision of identification are important factors that affect the efficiency of field measurements. This method, which is proposed by the authors, has the advantages of a simple algorithm, a high degree of automation and high precision, as well as ease of operation (see the reference). 2. Biomass observation 2.1. Observation time 2.1.1 Station of the crop land: The observations lasted from 20 May 2012 to 15 September 2012, and in five-day periods for each observation before 31 July and in ten-day periods for each observation after 31 July. The observation time for the crop land are 2013-5-25, 2013-5-30, 2013-6-5, 2013-6-10, 2013-6-16, 2013-6-22, 2013-6-27, 2013-7-2, 2013-7-7, 2013-7-12, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 2.1.2 The station of wetland: The observations lasted from 20 May 2012 to 15 September 2012, and in ten-day periods for each observation. The observation time for the crop land are 2013-6-5, 2013-6-16, 2013-6-27, 2013-7-7, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 2.2. Method Station of the crop land: Three plots were selected and three strains of corn for each observation were random selected for each plot to measure the fresh weight (the aboveground biomass and underground biomass) and dry weight. Per unit biomass can be obtained according to the planting structure. Station of the wetland: Two plots of reed with the area of 0.5 m × 0.5 m were random selected for each observation. The reed of the two plots was cut to measure the fresh weight (the aboveground biomass) and dry weight. 2.3. Instruments Balance (accuracy 0.01 g); drying oven 3. Data storage All observation data were stored in excel. Other data including plant spacing, row spacing, seeding time, irrigation time, the time of cutting male parent and the harvest time of the corn for the station of cropland were also stored in the excel.

0 2019-09-15

Dataset of above ground biomass in Sanjiangyuan region (2000, 2010, 2015 )

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

0 2019-09-15

HiWATER: Dataset of ground truth measurements synchronizing with airborne PLMR mission in the upper reaches of the Heihe River Basin on August 1, 2012

The dataset of ground truth measurements synchronizing with airborne Polarimetric L-band Multibeam Radiometer (PLMR) mission was obtained in upper reaches of the Heihe River Basin on 1 August, 2012. PLMR is a dual-polarization (H/V) airborne microwave radiometer with a frequency of 1.413 GHz, which can provide multi-angular observations with 6 beams at ±7º, ±21.5º and ±38.5º. The PLMR spatial resolution (beam spot size) is approximately 0.3 times the altitude, and the swath width is about twice the altitude. The measurements were conducted along two transects respectively located at the west and east branches of the Babaohe River and two sampling plots in the A’rou foci experimental area. Along the transects, soil moisture was sampled at every 50 m in the west-east direction. In order to keep the ground measurements following the airborne mission as synchronous as possible in temporal, measurements were made discontinuously. In the A’rou foci experimental area, two sampling plots were identified with areas of 1.5 km × 0.6 km and 0.85 km × 0.6 km. In each plot, soil moisture was sampled at every 50 m in the west-east direction and 100 m in the north-south direction. Steven Hydro probes were used to collect soil moisture and other measurements. Concurrently with soil moisture sampling, vegetation properties were measured at some typical sampling plots. Observation items included: Soil parameters: volumetric soil moisture (inherently converted from measured soil dielectric constant), soil temperature, soil dielectric constant, soil electric conductivity. Vegetation parameters: biomass, vegetation water content, canopy height. Data and data format: This dataset includes two parts of measurements, i.e. soil and vegetation parameters. The former is as shapefile, with measured items stored in its attribute table. The measured vegetation parameters are recorded in an Excel file.

0 2019-09-14

Observation dataset of forest ecosystems on the eastern margin of the Tibet Plateau (2005-2008)

These are the meteorological, soil, vegetation and other data observed by the Gongga Mountain Forest Ecosystem Test Station on the eastern margin of the Tibetan plateau, primarily from 2005 to 2008. Meteorological data: temperature, air pressure, relative humidity, dew point temperature, water pressure, ground temperature, soil temperature (5 cm, 10 cm, 20 cm, and 40 cm), 10-minute average wind, 10-minute maximum wind speed, precipitation, total radiation, net radiation. Tree layer biological observation data: diameter at breast height, tree height, life form Shrub layer biological observation data: tree number, height, coverage, life form, aboveground biomass, underground biomass Herb layer biological observation data: tree (strain) number, average height, coverage, life type, aboveground biomass, underground biomass Leaf area index: tree layer leaf area index, shrub layer leaf area index, grass layer leaf area index Soil organic matter and nutrients: soil organic matter, total nitrogen, total phosphorus, total potassium, nitrate nitrogen, ammonium nitrogen, available nitrogen (alkali-hydrolysable nitrogen), available phosphorus, available potassium, slowly available potassium, PH value in aqueous solution Soil water content: depth, water content

0 2019-09-13