DOI: 10.57760/sciencedb.nbsdc.00238
title: Industrial heat sources in China during 2012 and 2023
title: 中国2012-2023年工业热源数据集

description: Comprehensively grasping the high spatiotemporal dynamic information of industrial heat sources (IHS) in China is of great significance for the green, high-quality and sustainable development of industry under the background of "dual carbon". At present, there is still a lack of dynamic data on industrial heat sources for large regions, long time series, and high spatiotemporal, and measures such as structural adjustment and capacity reduction in China have not been effectively tracked and monitored in space. This article utilizes a long time sequence of 375m NPP VIIRS（United States Suomi National Polar-orbiting Partnership, Visible Infrared Imaging Radiometer Suite） Active fire/hotspot data (ACF), based on an improved Kmeans industrial heat source identification method, combined with POI topology analysis and high-resolution remote sensing image features of different types of factories and mines, is used to identify and classify industrial heat sources in China from 2021 to 2023. A dataset of industrial heat sources in China from 2021 to 2023 including type information in vector format is first constructed and public free. The dynamic remote sensing monitoring results of industrial heat sources in China from 2021 to 2023 provide independent scientific basis for China to actively respond to the upgrading of the "structural adjustment and capacity reduction" industrial model, domestic and international carbon tax trading, and improvement of atmospheric environment and other sustainable development processes. The results show that extending the time span to 2012-2023, combined with POI topology analysis based industrial heat source category recognition, can effectively reveal the spatiotemporal evolution laws of different types of industrial heat sources during the critical period of industrial transformation and upgrading; Based on the improved Kmeans industrial heat source recognition method, while ensuring recognition accuracy (98.14%), the number, accuracy, average particle size, and spatial coverage of industrial heat source recognition have been effectively improved; The dataset includes 20 characteristic parameters such as factory and mine locations, annual operating conditions, and categories, which fully record the radiation flux characteristics and production activity intensity of different types of industrial heat sources, providing richer data support for industrial carbon emission estimation and regional economic development assessment.
description: Comprehensively grasping the high spatiotemporal dynamic information of industrial heat sources (IHS) in China is of great significance for the green, high-quality and sustainable development of industry under the background of "dual carbon". At present, there is still a lack of dynamic data on industrial heat sources for large regions, long time series, and high spatiotemporal, and measures such as structural adjustment and capacity reduction in China have not been effectively tracked and monitored in space. This article utilizes a long time sequence of 375m NPP VIIRS（United States Suomi National Polar-orbiting Partnership, Visible Infrared Imaging Radiometer Suite） Active fire/hotspot data (ACF), based on an improved Kmeans industrial heat source identification method, combined with POI topology analysis and high-resolution remote sensing image features of different types of factories and mines, is used to identify and classify industrial heat sources in China from 2021 to 2023. A dataset of industrial heat sources in China from 2021 to 2023 including type information in vector format is first constructed and public free. The dynamic remote sensing monitoring results of industrial heat sources in China from 2021 to 2023 provide independent scientific basis for China to actively respond to the upgrading of the "structural adjustment and capacity reduction" industrial model, domestic and international carbon tax trading, and improvement of atmospheric environment and other sustainable development processes. The results show that extending the time span to 2012-2023, combined with POI topology analysis based industrial heat source category recognition, can effectively reveal the spatiotemporal evolution laws of different types of industrial heat sources during the critical period of industrial transformation and upgrading; Based on the improved Kmeans industrial heat source recognition method, while ensuring recognition accuracy (98.14%), the number, accuracy, average particle size, and spatial coverage of industrial heat source recognition have been effectively improved; The dataset includes 20 characteristic parameters such as factory and mine locations, annual operating conditions, and categories, which fully record the radiation flux characteristics and production activity intensity of different types of industrial heat sources, providing richer data support for industrial carbon emission estimation and regional economic development assessment.