1 km grid data set of industrial output value in China（2010）

The lack of spatial industrial output value data limited the risk and disaster assessment of industrial economy responding to global change. Therefore, we developed a new method to spatialize industrial output value coupling DMSP/OLS (Defense meteorological satellite program/operational linescan system) nighttime light data, MODIS (Moderate-resolution imaging spectroradiometer) annual vegetation data and industrial land distribution data. A grid data set of 1 km industrial output value of China was created using this method. The main steps creating the data set were as follows: (1) data preprocessing and selecting stable lighting data; (2) constructing an Enhanced Vegetation Index (EVI) adjusted nighttime light index (EANTLI) using nighttime light data which eliminated saturation and overflow by virtue of MODIS Vegetation Index; (3) obtaining optimum light index with EANTLI index which has been modified by industrial land distribution data; (4) constructing spatial distribution model of industrial output value; (5) verifying data accuracy. We randomly selected 90 cities nationwide to assess the accuracy of the data set. The results show that the relative errors of whole samples ranged from 0% to 39.6%,the relative errors of most samples were less than 15%, and the average accuracy of the data set was as high as 80.32%.