This dataset, based on night light data and macro statistical data, uses remote sensing inversion method（1km*1km）to obtain the poverty rate in different regions within each country. It has three advantages. a) The calculation unit can be adjusted according to the boundaries of administrative regions to reflect the poverty rate of sub-regions within the large country and scale, which is rare in statistically data. b) The survey and summary cycle limits the updating of national and sub-regional poverty rate, while the method based on night light data is more convenient. c) Due to the continuous annual data of night light, the difficulty of obtaining regional poverty rate in a long period was overcome. In view of the three outstanding advantages mentioned above, this data set can support to achieve the research subjects and provide scientific data for understanding the basic situation of poverty along the Silk Roads.
Qian ZHANG, Linxiu ZHANG
The distribution data of Central Asia desert oil and gas fields are in the form of vector data in ". SHP". Including the distribution of oil and gas fields and major urban settlements in the five Central Asian countries. The data is extracted and cut from modis-mcd12q product. The spatial resolution of the product is 500 m, and the time resolution is 1 year. IGBP global vegetation classification scheme is adopted as the classification standard. The scheme is divided into 17 land cover types, among which the urban data uses the construction and urban land in the scheme. The data can provide data support for the assessment and prevention of sandstorm disasters in Central Asia desert oil and gas fields and green town.