Abstract
The mining industry production is an important pillar industry in China, while its extensive production activities have led to several ecological and environmental problems. Earth observation technology using high-resolution satellite imagery can help us efficiently obtain information on surface elements, surveying and monitoring various land occupation issues arising from open-pit mining production activities. Conventional pixel-based interpretation methods for high-resolution remote sensing images are restricted by “salt and pepper” noise caused by environmental factors, making it difficult to meet increasing requirements for monitoring accuracy. With the Jingxiang phosphorus mining area in Jingmen Hubei Province as the studied area, this paper uses a multi-scale segmentation algorithm to extract large-scale main characteristic information using a layered mask method based on the hierarchical structure of the image object. The remaining characteristic elements were classified and extracted in combination with the random forest model and characteristic factors to obtain land occupation information related mining industry production, which was compared with the results of the Classification and Regression Tree model. 23 characteristic factors in three aspects were selected, including spectral, geometric and texture characteristics. The methods employed in this study achieved 86% and 0.78 respectively in overall extraction accuracy analysis and the Kappa coefficient analysis, compared to 79% and 0.68 using the conventional method.
Highlights
With the continuous development of the Chinese economy, mining production has become an essential part of China’s economic development
In order to analyse and compare single classifier and ensemble learning classifiers, the machine learning algorithms used in this experiment include Classification and Regression Tree model (CART), and Random Forest model (RF), which was set CART as base classifier [30–33]
For the random forest model, the scores are calculated for the importance of characteristic factors by getting the Gini index through calculation in the process of building the model [33]
Summary
With the continuous development of the Chinese economy, mining production has become an essential part of China’s economic development. Continuous developments and improvements in the mining economy have led to several challenges for its sustainable development [1, 2]. Data shows that as of 2015, more than 1.06 million hectares of forested land have been cleared for the exploitation of mineral resources, while 263,000 hectares of grassland have been destroyed. More than 1.4 million hectares of accessible land. Land use classification of open-pit mine who needs these confidential data can contact the email and obtain the data after approval. Like other researchers who need to obtain these data, the authors submitted a data use application to associate professor Zhou, and obtained the right to use these data only after the application was approved
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