Monthly production estimation model for steel companies based on inversion of satellite thermal infrared temperature
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摘要: 钢铁业是国民经济发展中重要组成部分,掌握钢铁企业月产量有利于开展宏观调控及合理分配资源。以钢铁企业的月产量为研究对象,运用景观格局指数的理论和方法,利用卫星热红外遥感数据表面温度反演后的分级结果,结合厂房矢量数据来获取表面温度异常值和热力景观分布参数,以此提出并建立钢铁企业炼钢月产量估算模型。再结合华中和华北两个典型钢铁企业实际月产量数据,根据最小二乘拟合分别求估算模型,模型的决定系数(R2)大于0.9。分析后验差检验结果可知,该估算模型精度等级为二级; 且在95%的置信度下,实际产量值均落在估算值的置信区间内,综合反映本文提出的炼钢月产量估算模型精度较高。Abstract: The iron and steel industry is a very important part in economic development. Obtaining the knowledge of the monthly production of steel companies is conducive to the macro control of the economy and the rational allocation of resources. In this paper, a monthly production estimation model for steel companies was proposed based on the grading results of the surface temperature obtained from the inversion of satellite thermal infrared data as well as the theory and method of landscape pattern indices. The surface temperature anomalous values and the thermal landscape distribution parameters of steel companies can be calculated according to the vector data of the spatial framework of steel companies. Based on this and the actual monthly production data of two typical steel companies in Central China and North China, the estimation model was established through the least-squares fitting, and the coefficient of determination (R2) of the model was greater than 0.9. According to the posterior variance test results, the accuracy of the estimation model proposed in this study is level 2. Meanwhile, the actual production values all fall within the 95% confidence interval of the estimation values. All these comprehensively reflect the monthly production model proposed in this paper are highly accurate.
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