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Remote Sensing for Land & Resources    2019, Vol. 31 Issue (1) : 220-228     DOI: 10.6046/gtzyyg.2019.01.29
A study of auxiliary monitoring in iron and steel plant based on multi-temporal thermal infrared remote sensing
Jing LI1, Qiangqiang SUN1, Ping ZHANG1, Danfeng SUN1(), Li WEN2, Xianwen LI2
1.College of Land Science and Technology, China Agricultural University, Beijing 100193, China
2.China Institute of Land Survey and Planning, Beijing 100035, China
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In order to monitor production state of iron and steel enterprises with auxiliary, the authors took Tangshan iron and steel enterprises as study cases to obtain the land surface temperature in tenth band of TIRS inversion derived from Landsat8 data on February 7, March 10, March 26, May 13 and May 29, 2016,in combination with the spatial structure of iron and steel enterprise information provided by GF-2 data from September 26, 2015 and September 10, 2016. The land surface temperature was finally divided into low temperature region (mainly non-production area) and high temperature region (mainly production area) by using threshold. On such a basis, the authors established production thermal radiation model to determine the production status of iron and steel enterprises in this period. Finally, the results obtained by the authors were preliminarily validated by the spatial structure change information provided by GF-2 satellite data and monthly output data of iron and steel enterprises. The results show that it is feasible to evaluate the production status of iron and steel enterprises by using thermal radiation model of production based on thermal infrared remote sensing.

Keywords thermal infrared remote sensing      Landsat8 TIRS      GF-2      iron and steel enterprises      monitoring     
:  TP79  
Corresponding Authors: Danfeng SUN     E-mail:
Issue Date: 14 March 2019
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Jing LI
Qiangqiang SUN
Danfeng SUN
Xianwen LI
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Jing LI,Qiangqiang SUN,Ping ZHANG, et al. A study of auxiliary monitoring in iron and steel plant based on multi-temporal thermal infrared remote sensing[J]. Remote Sensing for Land & Resources, 2019, 31(1): 220-228.
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Fig.1  Schematic diagram of thermal radiation in iron and steel enterprises
Fig.2  Technical route
Fig.3  Threshold selection
Fig.4  Landsat8 image in Tangshan on May 13,2016
时相 卫星 轨道号 产品 云覆盖
20160207 Landsat8 122/32 OLI TIRS L1T 3.59 30
20160310 Landsat8 122/32 OLI TIRS L1T 0.30 30
20160326 Landsat8 122/32 OLI TIRS L1T 0.05 30
20160513 Landsat8 122/32 OLI TIRS L1T 0.02 30
20160529 Landsat8 122/32 OLI TIRS L1T 0.16 30
20150926 GF-2 PMS
20160910 GF-2 PMS
Tab.1  Image data list
Fig.5-1  Monitoring results of thermal radiation in iron and steel enterprises
Fig.5-2  Monitoring results of thermal radiation in iron and steel enterprises
Fig.6-1  H line chart
Fig.6-2  H line chart
Fig.7  Spatial structure change in iron and steel works
Fig.8  Steel companies D monthly yield in 2016 and linear regression analysis of production in heat radiation H and monthly production
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