Research on GDP Prediction of Yangtze River Delta Based on Long Time-series Night Light Remote Sensing Data
This paper combines DMSP/OLS and NPP/VIIRS two kinds of common night light remote sensing data to extend the time span of night light remote sensing data. Taking three provinces and one city in the Yangtze River Delta region as an example, a com-parison was made between the univariate ARIMA model, the ARIMAX model with NPP/VIIRS data added, and the ARIMAX model with the fusion of two types of night light data in this paper to study the GDP of the study area. 2019-2021 was used as the predicted year, and compared with the actual value. The experimental results show that different economic structures have different accuracy in GDP prediction results. The addition of night light remote sensing data models will significantly reduce the accuracy of predicting GDP in economically developed and small areas. The average GDP prediction accuracy of the fused night light data has been significantly improved compared to before, which can effectively improve GDP prediction results.
night light remote sensingGDP dataDMSP/OLS dataNPP/VIIRS data
万方数据
维普
