The data set is based on the NPP simulated by 16 dynamic global vegetation models (TRENDY v8) under S2 Scenario (CO2+Climate) and represents the net primary productivity of the ecosystem. Data was derived from Le Quéré et al. (2019). The range of source data is global, and the Qinghai Tibet plateau region is selected in this data set. Original data is interpolated into 0.5*0.5 degree by the nearest neighbor method in space, and the original monthly scale is maintained in time. The data set is the standard model output data, which is often used to evaluate the temporal and spatial patterns of gross primary productivity, and compared with other remote sensing observations, flux observations and other data.
2022-04-19
The dataset is the normalized difference water index (NDWI) products from 1970s to 2020 over the Tibetan Plateau。The dataset is producted based on Landsat surface reflectance dataset. It is calculated by the NDWI equation which use the difference ratio between the green band and NIR band to enhance the water information, and then to weaken the information of vegetation, soil, buildings and other targets.And the corresponding production of quality identification documents (QA) is also generated to identify the cloud, ice and snow.NDWI is usually used to extract surface water information effectively, therefore it is widely used in water resoureces, hydrology, forestry and agriculture.
2022-04-19
Based on a large number of measured aboveground biomass data of grassland, the temperate grassland types were divided according to the vegetation type map of China in 1980s Based on the Landsat remote sensing data of engine platform, the random forest model of grassland aboveground biomass and remote sensing data was constructed for different grassland types. On the basis of reliable verification, the annual aboveground biomass of grassland from 1993 to 2019 was estimated, and the annual spatial data set of aboveground biomass of temperate grassland in Northern China from 1993 to 2019 was formed. Aboveground biomass is defined as the total amount of organic matter of vegetation living above the ground in unit area. The original grid value has been multiplied by a factor of 100, unit: 0.01 g / m2 (g / m2). This data set can provide a scientific basis for the dynamic monitoring and evaluation of temperate grassland resources and ecological environment in northern China.
2022-04-18
A total of 52 sample sites were selected in the desert belts of Qinghai and Tibet for field sampling of aboveground biomass of vegetation during the vegetation growing season in 2019 and 2020. At the same time, the longitude, latitude and altitude of the experimental site were recorded using handheld GPS devices. The field setting method of the quadrate is as follows: select a section with uniform vegetation. When the vegetation is relatively abundant, the quadrate is set as a 10 m x10 m square plot, and when the vegetation is relatively sparse, the quadrate is set as a 30 m x30 m square plot or a 30 m x90 m rectangular plot. 3-5 small sample boxes (1m x 1m) were randomly thrown into the set sample plot to determine the specific location of the sample. Collect plant samples by sample harvesting method: register plant species, number of plants of each species and other information in sample area of 1 square meter. All kinds of plants in the quadrate were planted and mowed on the ground, and the collected herbaceous plant samples were placed in archives and marked with species, sample site name and number, collection time and other information. They were brought back to the laboratory and dried to a constant weight in a constant temperature drying oven at 65 ℃. The dry weight of the plant samples was measured. Finally, the aboveground biomass of the vegetation was calculated. In addition, two kinds of remote sensing net primary productivity (NPP) data of the 52 sample points were extracted by the longitude and latitude of the sampling points. (1) Enhanced Vegetation Index (EVI) from 2000 to 2018, and calculated the annual Integrated Enhanced Vegetation Index (IEVI). IEVI was highly correlated with net primary productivity (NPP). Can be used as a proxy indicator of net primary productivity (He et al. 2021, Science of The Total Environment). (2) Percentage of remote sensing net primary productivity (NPP) and its quality control (QC) in 2001-2020, NPP remote sensing data from MOD17A3HGF Version 6 product (https://lpdaac.usgs.gov/products/mod17a3hgfv006/), the net photosynthetic value (the total primary productivity - keep breathing) is calculated. In the sample sites with low vegetation coverage, there may be null value (NA) of remote sensing net primary productivity.
2022-04-18
Fraction of Absorbed Photosynthetically Active Radiation (FPAR) is a key physiological variable in the study of carbon cycling and is one of the basic variables to describe vegetation ecosystems. The classification results of surface vegetation types in Qinghai-Tibet Plateau region are obtained based on the Landsat reflectance data(30m spatial resolution). According to NDVI of different vegetation types, the remote sensing inversion model is constructed to produce the growing season FPAR products for each vegetation type. This product can be used as one of the parameters to calculate vegetation carbon sequestration and evaluate vegetation ecosystem status.
2022-04-18
The dataset is the Landsat surface reflectance products from 1980s to 2019 over the Tibetan Plateau, it is the key input parameter of many surface geophysical parameters (such as leaf area index, chlorophyll and biomass). The dataset is retrieved based on Landsat level 4 products from China satellite remote sensing ground station, and it is retrived by using the atmospheric correction based on 6S model and BRDF correction model based on C-factor .The RMSE of geometric correction is less than 12m and the RMSD of surface reflectance is less than 5%. And the corresponding production of quality identification documents (QA) is also generated to identify the cloud, ice and snow.The Landsat surface reflectance play an important role in forest, water resources, climate change.
2022-04-18
Grassland actual net primary production (NPPa) was calculated by CASA model. CASA model was calculated with the combination of satellite-observed NDVI and climate (e.g. temperature, precipitation and radiation) as the driving factors, and other factors, such as land-use change and human harvest from plant material, were reflected by the changes of NDVI. CASA NPP was determined by two variables, absorbed photosynthetically active radiation’ (APAR) and the light-use efficiency (LUE). Grassland potential net primary production (NPPp) was calculated by TEM model. TEM is one of process-based ecosystem model, which was driven by spatially referenced information on vegetation type, climate, elevation, soils, and water availability to calculate the monthly carbon and nitrogen fluxes and pool sizes of terrestrial ecosystems. TEM can be only applied in mature and undisturbed ecosystem without take the effects of land use into consideration due to it was used to make equilibrium predications. Grassland potential aboveground biomass (AGBp) was estimated by random forest (RF) algorithm, using 345 AGB observation data in fenced grasslands and their corresponding climate data, soil data, and topographical data.
2022-04-18
Data content: The data set products include impervious surface products with a resolution of 10 meters in the Qinghai-Tibet Plateau, which can be used as a key parameter for related research on the Qinghai-Tibet Plateau ecosystem. Data source and processing method: Product inversion is mainly based on Sentinel series data, considering joint features, combining depth spatial features, long-time NDVI and other exponential features, and topographic features, and using random forest model to achieve impervious surface information extraction. Data quality: The overall accuracy is high. Data application results and prospects: The data set will be continuously updated and can be used to further clarify the impact of human activities on the ecosystem of the Qinghai-Tibet Plateau.
2022-04-18
Data set contains tree age of trees growing at different glacier moraines in the central Himalayas. The data were obtained using tree ring samples. Cores samples were collected (almost near to the ground level to estimate the minimum age of the related moraine) using an increment borer. Samples were processed by using standard dendrochronological techniques.
2022-04-15
Based on a large number of measured aboveground biomass data of grassland, the temperate grassland types were divided according to the vegetation type map of China in 1980s Based on the Landsat remote sensing data of engine platform, the random forest model of grassland aboveground biomass and remote sensing data was constructed for different grassland types. On the basis of reliable verification, the annual aboveground biomass of grassland from 1993 to 2019 was estimated, and the annual spatial data set of aboveground biomass of temperate grassland in Northern China from 1993 to 2019 was formed. Aboveground biomass is defined as the total amount of organic matter of vegetation living above the ground in unit area. The original grid value has been multiplied by a factor of 100, unit: 0.01 g / m2 (g / m2). This data set can provide a scientific basis for the dynamic monitoring and evaluation of temperate grassland resources and ecological environment in northern China.
2021-01-27
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