Continuous observation data set of leaf area index (based on hemispheric image) in Zhangye City (2019-2021)

Leaf area index is an important structural parameter of ecosystem, which is used to reflect the number of plant leaves, changes in canopy structure, life vitality of plant community and its environmental effects, provide structured quantitative information for the description of material and energy exchange on the surface of plant canopy, and balance the energy of carbon accumulation, vegetation productivity and interaction between soil, plant and atmosphere in ecosystem, Vegetation remote sensing plays an important role. The data comes from the distributed leaf area index instrument independently developed by the project (based on hemispheric image), which takes hemispheric images of forest canopy at fixed time, fixed point and from bottom to top, and uploads them through wireless network. This data acquisition is the original hemispherical image, which needs further processing to calculate the leaf area index, which can be processed by hemiview and other software.

0 2021-11-01

Ground observation dataset of corn biomass, vegetation coverage, leaf area index and plant height at Daman station in the middle reaches of Heihe River (growth period in 2020)

This dataset is a continuous ground observation data of vegetation coverage (%), biomass (g/plant), leaf area index (LAI) and plant height (cm) of seed corn during the growing period in 2020 at Daman Station ( 38.85551N,100.37223E)in the middle reaches of the Heihe River. Ground observation was carried out in three sample plots. Biomass observation included fresh and dry aboveground biomass, fresh and dry underground biomass (fresh and dry root weight), vegetation coverage was observed by digital camera, leaf area index was observed by LAI 2200, and plant height was observed by tape measure. The observation period was from May 31 to September 22, 2020. Observation parameters were observed every 5 days before July 31 and every 10 days thereafter, and a total of 19 observations were carried out during the whole growing period. The dataset can provide data basis for inversion and validation of surface vegetation parameters.

0 2021-10-26

Ground observation dataset of corn biomass, vegetation coverage, leaf area index and plant height at Daman station in the middle reaches of Heihe River (growth period in 2019)

This dataset is a continuous ground observation data of vegetation coverage (%), biomass (g/plant), leaf area index (LAI) and plant height (cm) of seed corn during the growing period in 2019 at Daman Station ( 38.85551N,100.37223E)in the middle reaches of the Heihe River. Ground observation was carried out in three sample plots. Biomass observation included fresh and dry aboveground biomass, fresh and dry underground biomass (fresh and dry root weight), vegetation coverage was observed by digital camera, leaf area index was observed by LAI 2200, and plant height was observed by tape measure. The observation period was from May 17 to September 23, 2019, in which LAI started from June 11. Observation parameters were observed every 5 days before July 31 and every 10 days thereafter, and a total of 20 observations (LAI was 15) were carried out during the whole growing period. The dataset can provide data basis for inversion and validation of surface vegetation parameters.

0 2021-10-26

Ground observation dataset of corn biomass, vegetation coverage, leaf area index and plant height at Daman station in the middle reaches of Heihe River (growth period in 2018)

This dataset is a continuous ground observation data of vegetation coverage (%), biomass (g/plant), leaf area index (LAI) and plant height (cm) of field corn during the growing period in 2018 at Daman Station ( 38.85551N,100.37223E)in the middle reaches of the Heihe River. Ground observation was carried out in three sample plots. Biomass observation included fresh and dry aboveground biomass, fresh and dry underground biomass (fresh and dry root weight), vegetation coverage was observed by digital camera, leaf area index was observed by LAI 2200, and plant height was observed by tape measure. The observation period was from May 26 to September 26, 2018, in which LAI started from May 30. Observation parameters were observed every 5 days before July 31 and every 10 days thereafter, and a total of 22 observations (LAI was 20) were carried out during the whole growing period. The dataset can provide data basis for inversion and validation of surface vegetation parameters.

0 2021-10-26

Ground observation dataset of corn biomass, vegetation coverage, leaf area index and plant height at Daman station in the middle reaches of Heihe River (growth period in 2017)

This dataset is a continuous ground observation data of vegetation coverage (%), biomass (g/plant), leaf area index (LAI) and plant height (cm) of seed corn during the growing period in 2017 at Daman Station ( 38.85551N,100.37223E)in the middle reaches of the Heihe River. Ground observation was carried out in three sample plots. Biomass observation included fresh and dry aboveground biomass, fresh and dry underground biomass (fresh and dry root weight), vegetation coverage was observed by digital camera, leaf area index was observed by LAI 2200, and plant height was observed by tape measure. The observation period was from May 15 to September 21, 2017, in which LAI started from June 6. Observation parameters were observed every 5 days before July 31 and every 10 days thereafter, and a total of 21 observations (LAI was 17) were carried out during the whole growing period. The dataset can provide data basis for inversion and validation of surface vegetation parameters.

0 2021-10-26

Ground observation dataset of corn biomass, vegetation coverage, leaf area index and plant height at Daman station in the middle reaches of Heihe River (growth period in 2016)

This dataset is a continuous ground observation data of vegetation coverage (%), biomass (g/plant), leaf area index (LAI) and plant height (cm) of seed corn during the growing period in 2016 at Daman Station ( 38.85551N,100.37223E)in the middle reaches of the Heihe River. Ground observation was carried out in three sample plots. Biomass observation included fresh and dry aboveground biomass, fresh and dry underground biomass (fresh and dry root weight), vegetation coverage was observed by digital camera, leaf area index was observed by LAI 2200, and plant height was observed by tape measure. The observation period was from May 19 to September 5, 2016, in which LAI started from May 30. Observation parameters were observed every 5 days before July 31 and every 10 days thereafter, and a total of 18 observations (LAI was 9) were carried out during the whole growing period. The dataset can provide data basis for inversion and validation of surface vegetation parameters.

0 2021-10-26

Ground observation dataset of corn biomass, vegetation coverage, leaf area index and plant height at Daman station in the middle reaches of Heihe River (growth period in 2015)

This dataset is a continuous ground observation data of vegetation coverage (%), biomass (g/plant), leaf area index (LAI) and plant height (cm) of seed corn during the growing period in 2015 at Daman Station ( 38.85551N,100.37223E)in the middle reaches of the Heihe River. Ground observation was carried out in three sample plots. Biomass observation included fresh and dry aboveground biomass, fresh and dry underground biomass (fresh and dry root weight), vegetation coverage was observed by digital camera, leaf area index was observed by LAI 2200, and plant height was observed by tape measure. The observation period was from May 10 to September 21, 2015, in which LAI started from May 25. Observation parameters were observed every 5 days before July 31 and every 10 days thereafter, and a total of 21 observations (LAI was 18) were carried out during the whole growing period. The dataset can provide data basis for inversion and validation of surface vegetation parameters.

0 2021-10-26

Dataset of ecological survey in the urbanized area of Tibetan Plateau (2019-2020)

This dataset includes photosynthetic parameters and leaf area index of major vegetation types in the urbanized area of Tibetan Plateau (Huangshui river basin, Heihe river basin and major towns on the Tibetan Plateau). 1) Objectives The ecological survey data can be used for the parameterization and validation of ecohydrological models in the urbanized areas of the Tibetan Plateau. 2) Instrument of the observation: LI-6800 Portable Photosynthesis System and LAI-2200 Plant Canopy Analyzer 3) Time and sites of observations: The measurements were conducted in the Heihe River Basin from July to August in 2019, and in the Huangshui River Basin and key urban areas on the Tibetan Plateau from July to August in 2020. 4) Measured parameters and data processing Considering the needs of the ecohydrological models, we selected 12 main indexes from the original data measured by LI-6800 and LAI-2200, such as E: evapotranspiration rate (mol m⁻² s⁻¹), A: net photosynthesis rate (µmol m⁻² s⁻¹), Ci: intercellular CO2 concentration (µmol mol⁻¹). 5) Data storage The dataset was stored in Excel format, other ancillary data include the longitude and latitude of sample site and the main vegetation types, etc.

0 2021-05-21

Vegetation environmental research data set in key areas of Asian water tower area of Qinghai Tibet Plateau (2019-2020)

This data set includes six data files, which are: (1) soil temperature and moisture data of alpine meadow elevation gradient_ Dangxiong, Tibet (2019-2020). This data is the hourly observation data of temperature and water content at different soil depths (5cm and 20cm) of the alpine meadow at 4400m, 4500m, 4650m, 4800m, 4950m and 5100m above sea level in Dangxiong, Tibet during 2019-2020. (2) Meteorological environment data of Sejila Mountain Forest line_ Linzhi, Tibet (2019), the data is the hourly meteorological environment (including wind speed, air temperature 1 m away from the surface, relative humidity 1 m away from the surface, air temperature 3 m away from the surface, relative humidity 3 m away from the surface, atmospheric pressure, total radiation, net radiation, photosynthetically active radiation, 660 nm) of the forest line of Sejila Mountain in Linzhi, Tibet in 2019 Hourly observation data of red light radiation, 730nm infrared radiation, surface temperature, atmospheric long wave radiation, surface long wave radiation, underground 5cm-20cm-60cm heat flux, underground 5cm-20cm-60cm soil temperature and humidity, rainfall and snow thickness, among which some observation data are missing due to equipment power failure in plateau area, which has been explained in the data. (3) NDVI of vegetation at major meteorological stations_ In the Qinghai Tibet Plateau (2020), NDVI survey data and average values of vegetation near 25 meteorological stations are included. (4) Land use survey data set_ Along the Sichuan Tibet Railway (2019), including 35 survey points along the Sichuan Tibet railway land use survey data, including survey time, location, latitude and longitude, altitude, slope aspect, main vegetation types and dominant species. (5) Leaf area index survey data_ The leaf area index (LAI) of main vegetation types along Sichuan Tibet Railway (2019) was measured by SunScan canopy analyzer and lai-2200. (6) Survey data of soil temperature and humidity_ Along the Sichuan Tibet Railway (2019), including 34 survey points along the Sichuan Tibet Railway: location, longitude and latitude, altitude, soil surface temperature, soil moisture at 30cm, the data were recorded as 3 repeated measurements at each survey point. The data set can be used to analyze and study the change law of vegetation environment in Qinghai Tibet Plateau.

0 2021-04-20

Field LAI dataset in the Heihe River Basin (2012)

The ground sample data was collected by LAI-2000 canopy analyzer, and the collection area was located in Dayekou, Wuxing Village (2012) and other areas. The main measure of vegetation is corn. The LAI value of the corn was obtained using the LAI2000, and the observation was repeated twice in a pattern of “one up and four down”. The leaf area of each leaf of the corn plant was obtained using CD202, and a total of three corns were collected.

0 2020-09-15