针对精细化工业热源遥感监测困难与误差较大等问题,本文聚焦单个规模较大的工厂内部热场分布情况,提出一种基于中高分辨率卫星影像(Landsat -8)的装置级别工业热源的多层级识别方法。该方法基于双通道非线性劈窗算法反演的地表温度,利用多种空间统计分析方法分别对单期影像开展热源装置范围的识别检测,筛选出识别位置准确、边界清晰的方法,进而开展多时相热源装置识别分析,确定厂区范围内稳定出现的热源装置的位置,并结合高分辨率卫星影像进一步确定热源装置的边界范围。在某石油化工企业厂区的实验研究表明,聚类与异常值分析方法识别结果受季节变化影响较小,正确检出率在80%以上,适用于监测装置级别(主要包括生产装置、循环水、锅炉装置、储存库、火炬装置以及罐区)的工业生产活动变化情况,各类型装置与厂区平均温度的差值显示厂区内循环水装置、生产装置分布区为生产区内主要的发热区。研究结果还表明,中高分辨率卫星遥感影像数据源可以有效监测工业企业的精细尺度发热单元,为环境保护与管理、工业去产能监测提供技术支撑。

In view of the problems of insufficient refinement and large errors in the existing remote sensing monitoring of industrial heat sources, this paper focuses on the internal thermal field distribution of a single large-scale factory, and proposes a device-level industrial heat source identification method based on medium and high-resolution satellite images. . That is, the surface temperature is first obtained based on the dual-channel nonlinear split-window algorithm, and then a variety of spatial statistical analysis methods are used to identify candidate high-temperature areas, and the location of high-temperature devices in the plant is determined by multi-temporal superposition analysis of the identification results, and then combined with high-resolution satellite images. Determine the range of the high temperature device, compare and analyze the difference in the accuracy of the recognition results of several methods, and determine the method with the best recognition effect. The conclusions are as follows: (1) Multi-temporal-hot spot analysis and multi-temporal-clustering and outlier analysis methods have better recognition results, and the identified pixels fall in rates above 80%, and the overall omission rate and the omission of production equipment rate is less than 10%. (2) A total of 139 high-temperature devices were identified in the test area, including 56 production devices, followed by a total of 11 storage warehouses, and less than 10 of other types of devices. The production device is the main heating device. It is simple and effective to identify industrial heat sources at the device level based on multi-phase-cold-hot spot analysis and multi-phase-clustering and outlier analysis methods, and the results are accurate and reliable. It can monitor changes in industrial production activities at the device level. Provide technical support services.