《Table 4 Error analysis of simulated results》

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《基于栅格的豫西山区地形起伏特征及其对人口和经济的影响（英文）》

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As shown in 4.2.1，the spatialization results of population and economic data have good accuracy and are reliable.The simulation accuracy for population density was higher than that for economic density.According to the results，the average population density was364.17 people/km2，and the economic densities of primary，secondary and tertiary industries were 1.99 and 16.14 million yuan/km2，respectively.In order to further verify the accuracy of the results and deviation from the actual values，the simulated data of population，output of each industry and gross regional product were compared with the corresponding statistics（Table 4）.It can be seen that the relative error of total population was the lowest（0.66%），indicating that the land use impact model works well in population simulation.Some researchers have simulated the spatial distribution of population density in Henan using geostatistic methods and have reported that western Henan mountainous area is sparsely populated.The high and low population density areas are consistent with the results of this study（Zhang et al.，2016）.The relative error of the primary industry was the second lowest（1.39%）.However，the simulation accuracy for the second and tertiary industries was relatively low，resulting in low accuracy for the gross regional product.Thus，there are some limitations in spatializing economic data solely based on land use data.With the development of RS and GIS technologies，the remote sensing inversion of economic data and multi-source data fusion models have emerged（Zhao et al.，2017）.Thus，we will integrate remote sensing data，land use and other geographic data in future studies，and use the principal component analysis method to detect information redundancy in various factors.Accordingly，the spatial economic data model will be constructed from the aspect of different rural-urban areas and different industries.