2020年青藏高原GDP空间分布数据集

A dataset of GDP spatial distribution on the Qinghai-Tibet Plateau(2020)

经济空间分布数据是进行灾害损失评估的重要指标之一。青藏高原地区经济相对落后,地质灾害频发,研究该地区灾害对经济造成的影响意义重大。本研究基于分区分产业模拟的方法,将第一产业增加值(GDP of Primary Industry,GDP1)与土地利用类型、数字高程模型(Digital Elevation Model,DEM)、村落点、道路、河流缓冲区建立对应关系,第二三产业增加值(GDP of Secondary and Tertiary Industries,GDP23)与多元信息耦合后的夜间灯光、建筑用地、兴趣点数据分市区与县域创建空间模型。采用随机森林确定第二三产业中各类指标的权重,计算GDP23格网值,最终将GDP1与GDP23栅格叠加,构建2020年青藏高原100 m×100 m的国内生产总值(Gross Domestic Product,GDP)空间化分布图。利用县级GDP统计数据进行精度验证,相对均方根误差为0.0385,表明数据能较好地反映青藏高原GDP空间分布情况。本数据可为青藏高原灾害风险评估、防灾减灾提供数据支撑。

Economic spatial distribution data serve as an indicator for disaster loss assessment.The economy of the Qinghai-Tibet Plateau is relatively backward and geological disasters occur frequently,so it is of great significance to study the impact of disasters on the economy in this area.Based on the method of zoning and industry simulation,this study establishes the corresponding relationship between the GDP1(GDP of Primary Industry)and land use types,DEM(Digital Elevation Model),village points,roads and river buffers.Spatial models of night lighting,building site and points of interest data after the coupling of the GDP23(GDP of Secondary and Tertiary Industries)and multiple information are established in urban areas and counties.We used the random forest to determine the weights of various indicators in the secondary and tertiary industries,and calculated the grid value of GDP23.Finally,we superimposed the grid of GDP1 and GDP23 and created the spatial distribution map of GDP(Gross Domestic Product)of 100 m×100 m on the Qinghai-Tibet Plateau in 2020.According to the accuracy verification using county-level GDP statistical data,the Root Mean Square Error is 0.0385,which shows that the data can better reflect the spatial distribution of GDP on the Qinghai-Tibet Plateau.This dataset can provide GDP spatial data support for disaster risk assessment,disaster prevention and mitigation on the Qinghai-Tibet Plateau.