Current Browsing: Social and Economic


Net primary productivity data set of the Tibetan Plateau (1980-2018)

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

Grassland actual net primary production, potential net primary production and potential aboveground biomass on the Tibetan Plateau from 2000 to 2017

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

The dataset of community statistics of each county in Three-River-Source National Park (2017)

This data set contains statistical tables on the community situation of each county in Three-River-Source National Park. The specific contents include: Table 1 includes: number of administrative villages, number of natural villages, number of households, population, number of rural labor force, total value of primary and secondary industries, net income per capita, and number of livestock. Table 2 includes: the ethnic composition of the population (population of each ethnic group), education-related statistics (number of primary and secondary schools and number of students), health-related statistics (number of hospitals, health rooms and medical personnel), and statistics on the education level of the population (number of people with different education levels); Table 3 includes: the grassland (total grassland area, usable grassland area, moderately degraded area and grassland vegetation coverage), woodland (total area, arbor forest area, shrub forest area and sparse forest area), water area (total area, river area, lake area, glacier area, snowy mountain area and wetland area). A total of four counties were designed: Maduo, Qumalai, Zaduo and Zhiduo. This data comes from statistics of government departments.

2021-04-20

Provincial macro social-economic indicators of Heihe River Basin

It includes the social and economic data of Gansu, Qinghai and Inner Mongolia from 2000 to 2012. The specific indicators include GDP, income, population, employment, medical care, education, land area, finance and a series of social and economic indicators;

2020-07-28

Input-output table of Heihe River basin (2012)

Input output table of 11 districts and counties in Heihe River Basin in 2012

2020-07-28

Scenario analysis of social and economic development over Heihe River Basin (2020 & 2030)

Data analysis method: macroeconomic development forecast Space scope: Sunan County, Ganzhou District, Minle County, Linze County, Gaotai County, Shandan County, Jinta County, Ejina, Suzhou District, Jiayuguan Time frame: 2020, 2030 Data: GDP (1 million yuan), GDP growth rate, primary production (1 million yuan), primary production growth rate, secondary production (million yuan), secondary production growth rate, tertiary production (million yuan), tertiary production growth rate, primary production rate Second rate, third rate

2020-07-28

Scenario data of social and economic development in Heihe River Basin

Input output table of 11 districts and counties in Heihe River Basin in 2012

2020-07-28

SAM for Gaotai (2012)

The social accounting matrix, also known as the national economy comprehensive matrix or the national economy circulation matrix, uses the matrix method to connect the various accounts of the national economy systematically, represents the statistical index system of the national economy accounting system, and reflects the circulation process of the national economy operation. It uses the matrix form to arrange the national accounts orderly according to the flow and stock, domestic and foreign. The data reflects the balanced value of social accounting matrix in Gaotai County.

2020-06-03

Data of grassland community diversity and main plant functional trait under the influence of herdsmen's livestock raising activities (2012)

1) Initial data of community characteristics and main plant biological characteristics of the grass-animal equilibrium stage of the test grassland in 1983; 2) Livestock management data of 4-5 grazing grasslands; 3) Observation data of diversity, productivity and functional group of different grazing grassland communities; 4) Observation data on the height, coverage, biomass, and flower morphology, tillering, and leaf characteristics of main plants in different grazing gradient grasslands 5) Observation data of soil nutrients and litter in different grazing grasslands.

2020-04-12

Data on formation and evolution of pastoral animal husbandry policies in pastoral areas, and herdsmen's perceptions and responses to pastoral animal husbandry policies in pastoral areas

1. The grassland animal husbandry production and management policies in the study area from 1954 to 2012 mainly include: 1) the time series of the formation and evolution of various policies; 2) the key policies related to herdsman's livestock activities and grassland management and utilization. 2. Residents' perception and response to pastoral socio-economic development policies, grassland management systems, ecological compensation policies, ecological restoration projects, and ecological environment status quo.

2020-04-12