Spatiotemporal Dynamic Analysis Of In-use Steel Stock In Countries Along The Belt And Road Based On Multi-source Nighttime Light Remote Sensing Images

With global population expansion and urbanization,steel resources have become a key element of global urban development.However,the uncoordinated development trend of anthropogenic steel resources in cities along the Belt and Road(B&R)has created a succession of potential problems that hinder sustainable urban development.The refined urban in-use steel stock(IUSS)spatiotemporal dynamics information provides an important analysis window for decision support of regional sustainable development of anthropogenic steel resources.Currently,the rapid development of geographic information and nighttime light remote sensing technology shows great potential in urban IUSS analysis.However,there are still many limitations in multi-source nighttime light data,such as typical continuity and consistency issues.In addition,existing studies still lack multi-scale(spatial),multi-angle,and long-term evaluation methods.How to evaluate the spatiotemporal dynamics of IUSS relatively systematically,efficiently,and finely is an important challenge at present.This study integrates multi-source datasets and proposes the full-process correction method for multi-source nighttime light data,the pixel-level IUSS estimation method,the spatiotemporal pattern quantification method,and the development difference characterization model.Created the IUSS spatiotemporal dynamic analysis framework.The evolution trend,spatial pattern,and development differences of urban anthropogenic steel resources in the B&R regions in the past 30 years(1992-2019)were revealed.Specifically,(1)Corrected long-period time-series,multi-source nighttime light remote sensing data.This paper constructs a method for full-process correction.Firstly,the saturation effect,discontinuity effect,and overglow effect of DMSP-OLS data are corrected.Second,the annual NPP-VIIRS data were composited and background noise and outliers were filtered.Finally,combined with the proposed light space shape and intensity consistency correction model,a long-term nighttime light dataset with consistency and continuity is constructed.The results show that the corrected DMSP-OLS data is significantly optimized,the composite results of NPP-VIIRS average value have a more stable light intensity trend,and the corrected light total intensity has good continuity in the time series.In addition,the multi-source data correction results show that the nighttime light data correction method proposed in this paper can effectively correct and fuse DMSP-OLS and NPP-VIIRS data,and the correction results have good continuity and consistency.(2)Estimated the pixel-level IUSS and assessed its evolutionary drivers.This study first established a pixel-level IUSS spatial distribution estimation model based on the double logarithmic function to fit the relationship between nighttime light intensity and IUSS.The IUSS dataset with a resolution of 1 km in the B&R region from 1992 to 2019 was obtained,with a median relative error of 12.4%.Second,the spatiotemporal change assessment results of the pixel-level IUSS show that the evolution between the eastern and western parts of B&R is relatively drastic,with the IUSS increasing significantly in the eastern region and a decreasing trend in the western region.The spatial distribution pattern of IUSS gradually migrated from high latitude(50°N)to low latitude(30°N).Finally,a quantitative analysis model of driving factors was established based on the IPAT and LMDI methods.The results show that the level of affluence is the main positive driver of IUSS development in most countries,accounting for approximately 70% of the overall factors in recent years.(3)Quantified the multi-scale spatiotemporal evolution pattern of IUSS.This study proposes a multi-scale normalized regional development status assessment method and quantifies the long-term IUSS spatiotemporal patterns at the B&R global,national,provincial,and prefectural levels.The results show that the overall development of IUSS in the B&R region tends to be balanced.The spatial pattern of development states and intensity presents regional differentiation,which is caused by the confrontation between the balanced development areas in the south and the declining development areas in the north of B&R,but this confrontation trend has gradually weakened in recent years.In addition,the multi-scale spatial autocorrelation evaluation results show that the overall spatial correlation strength of the B&R region increased from 0.6 in 1992 to 0.7 in 2019,and the prefectural level is slightly higher than the provincial level.In general,the spatiotemporal pattern of steel resources in the B&R regions has gradually solidified,forming a bipolar pattern of high IUSS spatial agglomeration in places such as China,Russia,and India and low IUSS spatial agglomeration in places such as Central and Eastern Europe,Southeast Asia,and Mongolia.(4)Characterized the multi-scale regional developmental differences of IUSS.This study uses grid population and IUSS data,combined with multi-order Theil index theory,establishes a multi-scale IUSS regional development gap characterization model and reveals the evolutionary dynamics of development gaps at B&R global,national and provincial.The results show that the global development gap of the B&R shows a downward trend,from 0.821 in 2000 to 0.546 in 2019,and the gap between countries accounts for the main contribution(approximately 75%).The change in the spatial pattern of the global development gap at the national level is relatively small,and the proportion of the impact of the between-provincial gap and the within-provincial gap in different countries has obvious differences.The global development gap at the provincial level shows a declining trend,which is generally consistent with the overall trend of the B&R.In addition,the scale effect and diffusion effect were found to be important factors in analyzing the coordination of regional IUSS development.