为了高效、准确地从高分辨率遥感影像中提取裸岩,利用国产高分二号(GF-2)影像数据,通过构建斜率差异裸岩指数模型(slope difference bare rock index,简称SDBRI)和裸岩阴影指数模型(bare rock shadow index,简称BRSI),提出了亚米级高分影像的露天矿区裸岩提取技术方案.以青州市南部山区为试验区对此方法进行检验,结果表明:在SDBRI指数图像中,裸岩能够与周边植被较好区分,裸岩与其他地物的可分性显著高于NDVI、CRI1、CRI2等指数模型;以基于谷歌地球高清影像的目视解译结果作为验证数据进行精度评估,交并比(IoU)指标达到91%左右.此方法能够满足基于国产高分影像数据进行大范围矿区裸岩制图的需求,可以为矿山环境的遥感监测提供技术支持,具有较强的实践价值.
Mapping Bare Rock in Open-Pit Limestone Mining Area Using Gaofen-2 Satellite Image
In order to extract accurately and efficiently the bare rock from high-resolution remote sensing image,in this study it used Chinese Gaofen-2(GF-2)satellite imagery as data source,the slope difference bare rock index(SDBRI)and bare rock shadow index(BRSI)for the extraction of bare rock and bare rock shadow were created,respectively.Based on the two index models,it proposed a strategy for sub-meter-level high-resolution image bare rock extraction in the open-pit mining area.Then the southern mountainous area of Qingzhou City,Shandong Province was selected as the test area.The results show follows:In the SDBRI index image,the values of the bare rock can be easily distinguished from the surrounding vegetation.And the separability of bare rock and other objectives is significantly higher than that of other index models such as NDVI,CRI1,and CRI2.The visual interpretation results from the Google Earth high resolution images are used as verification data for accuracy evaluation,and the IoU index reaches about 91%.The method proposed in this paper can meet the needs of large-scale open rock mapping in mining areas based on Chinese high-resolution image data,and can provide technical support for remote sensing monitoring of mine environment,which has strong practical value.
Gaofen-2sub-meter satellite imageopen-pit mining areaindex modelbare rock extractionremote sensing
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万方数据
