摘要
为提高采煤沉陷区地质环境监测基础数据的质量,以宁夏惠农采煤沉陷区为研究区,分别选取矿山地质环境治理恢复前和治理恢复后的QuickBird遥感影像及高分二号遥感影像,运用PCA算法、NNDiffuse Pan Sharpening算法、Gram-Schmidt算法与Brovey Sharpening算法进行融合实验,并对融合结果进行定性和定量评价。结果表明:4种融合算法都在不同程度上提高了QuickBird影像和高分二号影像的原始多光谱影像空间分辨率。其中,QuickBird遥感影像使用Gram-Schmidt融合算法处理的效果最优,不仅在空间信息融入度方面表现较好,还具有很强的光谱保真能力,能够最大限度准确获取采煤沉陷区治理前的典型地物,如地裂缝、煤矸石、煤堆、矿坑水的范围、纹理及形态等相关信息;高分二号影像采用PC Spectral Sharpening融合算法处理的效果最优,不仅能够提高采煤沉陷区地物的空间细节信息,且能较多地保留原始多光谱信息,对于采煤沉陷区治理后的典型地物,如复绿植被、观景平台、中心广场等人造景观的几何结构和纹理信息表现更为明显。
In order to improve the quality of basic data of geological environment monitoring in coal mining subsidence area,this paper takes the Huinong coal mining subsidence area in Ningxia as the study area and selects the QuickBird image and Gaofen 2 image before and after the mine geological environment restoration and treatment.PC Spectral Sharpening algorithm,NNDiffuse Pan Sharpening algorithm,Gram-Schmidt algorithm and Brovey Sharpening algorithm are used to carry out fusion experiments and the fusion results of four fusion algorithms are qualitative and quantitative evaluated.The results show that:Four fusion algorithms all improve the spatial resolution of the original multi-spectral images to different degrees.The Gram-Schmidt fusion algorithm is used to process QuickBird remote sensing images with the best results obtained.The algorithm not only has a good integration of spatial information,but also has a strong spectral fidelity.It can obtain the range,texture and morphology of typical ground objects such as ground fissures,coal gangue and coal piles before coal mining subsidence governance.The PC Spectral Sharpening fusion algorithm is the best for GF-2 image processing,possible to improve the spatial detail information of ground objects in coal mining subsidence area,with more original multi-spectral information retained.It is more effective for the geometric structure and texture information of typical ground objects such as green vegetation,landscape platform,central square and other artificial landscapes after coal mining subsidence area governance.
作者
占惠珠
尚慧
甘智慧
ZHAN Huizhu;SHANG Hui;GAN Zhihui(College of Geology and Environment,Xi’an University of Science and Technology,Xi’an 710054,China)
出处
《西安科技大学学报》
CAS
北大核心
2021年第4期673-681,共9页
Journal of Xi’an University of Science and Technology
基金
国家自然科学基金项目(41702377)
陕西省自然科学基础研究计划项目(2017JQ4008)
中国博士后科学基金项目(2017M623208)。
