Abstract
The Chinese government has promulgated a de-capacity policy for economic growth and environmental sustainability, especially for the iron and steel industry. With these policies, this study aimed to monitor the economic activities and evaluate the production conditions of an iron and steel factory based on satellites via Landsat-8 Thermal Infrared Sensor (TIRS) data and high-resolution images from January 2013 to October 2017, and propel next economic adjustment and environmental protection. Our methods included the construction of a heat island intensity index for an iron and steel factory (ISHII), a heat island radio index for an iron and steel factory (ISHRI) and a dense classifying approach to monitor the spatiotemporal changes of the internal heat field of an iron and steel factory. Additionally, we used GF-2 and Google Earth images to identify the main production area, detect facility changes to a factory that alters its heat field and verify the accuracy of thermal analysis in a specific time span. Finally, these methods were used together to evaluate economic activity. Based on five iron and steel factories in the Beijing-Tianjin-Hebei region, when the ISHII curve is higher than the seasonal changes in a time series, production is normal; otherwise, there is a shut-down or cut-back. In the spatial pattern analyses, the ISHRI is large in normal production and decreases when cut-back or shut-down occurs. The density classifying images and high-resolution images give powerful evidence to the above-mentioned results. Finally, three types of economic activities of normal production, shut-down or cut-back were monitored for these samples. The study provides a new perspective and method for monitoring the economic activity of an iron and steel factory and provides supports for sustainable development in China.
Highlights
The iron and steel industry as a pillar industry in China has been challenged by economic sustainability and has suffered from environmental policy pressure
Combined with auxiliary information (Figure 5), a comparison of the ISHII curve with the curve of seasonal factors shows that ISHII is sensitive to the economic activity of the iron and steel factories
From 2013 to 2014, which represents the period when the economic activity of the iron and steel factory was not affected by government policy, the ISHII curve of the samples is normal and maintains a greater gap beyond the seasonal factors curve
Summary
The iron and steel industry as a pillar industry in China has been challenged by economic sustainability and has suffered from environmental policy pressure. It is worthwhile to accurately monitor the economic activity of an iron and steel factory for sustainable development of the entire industry and the environment. As a special studied object, the complexity and large number of iron and steel factories have limited our ability to obtain relatively accurate information to evaluate temporal and spatial changes via conventional methods, such as manually monitoring and random checking [6] at high cost. With the advantages of speed and ease of use, spatiotemporal monitoring approaches based on satellite data have often been used for Earth observation [7], from global changes [8] to urban extension [9], but they are gradually being applied to studying the economic environment and the specific activities of economic industries [10,11]. Remote sensing approaches are introduced here to study the economic activity of an iron and steel factory for the first time
Full Text
Topics from this Paper
Steel Factory
Landsat-8 Thermal Infrared Sensor
Supports For Sustainable Development
Sustainable Development In China
Specific Time Span
+ Show 5 more
Create a personalized feed of these topics
Get StartedTalk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Similar Papers
Remote Sensing
Feb 4, 2020
Canadian Journal of Remote Sensing
Sep 3, 2019
Jul 1, 2016
Oct 18, 2017
Jan 13, 2022
Journal of Applied Remote Sensing
May 13, 2019
Journal of Physics: Conference Series
Apr 1, 2020
International Journal of Remote Sensing and Earth Sciences (IJReSES)
Oct 23, 2019
Oct 23, 2018
Remote Sensing
Apr 14, 2015
Remote Sensing Letters
Nov 2, 2015
Remote Sensing
Oct 13, 2021
Sustainability
Jan 2, 2020
Sustainability
Sustainability
Nov 27, 2023
Sustainability
Nov 27, 2023
Sustainability
Nov 27, 2023
Sustainability
Nov 27, 2023
Sustainability
Nov 27, 2023
Sustainability
Nov 27, 2023
Sustainability
Nov 27, 2023
Sustainability
Nov 27, 2023
Sustainability
Nov 27, 2023
Sustainability
Nov 27, 2023