摘要
采用采样与实验方式对城区室外与室内环境破坏数据进行采集,利用聚类方法对采集到的数据进行处理,以处理后的数据为基础生成GF多光谱影像,对其进行校正得到真实的遥感反射率。将真实的遥感反射率进行转换并分类,采用环境破坏因素识别算法对遥感反射率数据进行识别,实现了对周边城区环境破坏因素的识别。经过实验得到,建立的环境破坏因素识别模型的识别正确率比传统模型高出38%,说明建立的环境破坏因素识别模型具有极高的有效性。
Therefore, the modeling study of environmental damage factors in surrounding urban areas by surface mine surveying and mapping is proposed. Water resource is the most destructive factor to the surrounding urban environment in open-pit mine surveying and mapping, so the main factor to identify the destructive factors of water resource is water resource. The instrument is used to collect and process the outdoor and indoor water resources data in urban area. Based on the processed data, the GF multispectral image is generated, and the real remote sensing reflectance is obtained by correcting the data. The real remote sensing reflectance is transformed and classified, and the remote sensing reflectance data is identified by using the recognition algorithm of environmental damage factors, which realizes the identification of environmental damage factors in surrounding urban areas. The experimental results show that the recognition accuracy of the established model is 38% higher than that of the traditional model, which shows that the established model is highly effective.
引文
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