Population density, climate zone, and ecological services data in the Loess Plateau and Qinling Mountains in China

<strong>1. Climate zone</strong> China’s climate zone data is compiled by China meteorological administration. The data takes the average daily temperature that more than 10 ℃ and the coldest temperature or multi-year extreme minimum temperature as heat index. Taking dryness as water index. Combining these two indices with topography and geomorphology characteristics, the country is divided into 8 primary climate regions and 32 secondary climate regions. Data Format: Shapefile. Projected Coordinate System: Krassovsky_1940_Albers. URL: https://www.resdc.cn/data.aspx?DATAID=243 <strong>2. Ecological services</strong> Ecological services are the many and varied benefits to humans provided by the natural environment and from healthy ecosystems. To assess the value of ecological services is an important basis for ecological environment protection, ecological function zoning, environmental economic accounting and ecological compensation decision-making. Based on the assessment of global ecological services by Costanza et al. (1997) and Xie et al. (2003), the equivalent weight factor table of ecological services of terrestrial ecosystems was formulated in China. This method has been widely adopted and quoted. In the estimation process, considering the basic equivalent of each ecosystem type, the method also considered the influence of spatiotemporal dynamic factors of NPP, precipitation and soil conservation regulation. The data was revised by biomass parameters to reflect regional differences in ecological services value. Units:￥·hm-1. Spatial resolution: 1 km. Projected Coordinate System: GCS_Krassovsky_1940. Data format: ArcGis Grid. URL: https://www.resdc.cn/DOI/DOI.aspx?DOIID=48 <strong>3. Population density</strong> The kilometre grid dataset of China's population spatial distribution is based on the demographic data of the national population statistics. Taking into account land use type, night light intensity, residential density and other factors that closely related to population. Using the multi-factor weight allocation method to upscale the population data which based on administrative regions as the basic statistical units. Firstly, calculate the population distribution weight of land use type, night light intensity, and residential density. Secondly, the total weight of each country-level administrative unit is calculated on the basic of standardizing the influence weights of above three aspects. Finally, using grid space calculation method to combine the unit weight of population with the total weight to spatialize population. Units: person·km-2. Spatial resolution: 1 km. Projected Coordinate System: GCS_Krassovsky_1940. Data format: ArcGis Grid. URL: https://www.resdc.cn/DOI/DOI.aspx?DOIid=32