摘要
在地形复杂的山区,地形阴影对遥感影像信息提取造成了极大的影响,因此应对遥感影像进行地形校正,从而消除地形效应,恢复地形阴影区域的地表反射率。本文以辽宁东部林区(辽东林区)为研究区域,采用空间分辨率为16 m的GF-1 WFV遥感影像,分别使用SCS+C、Minnaert+SCS和SCEDIL校正模型对原始影像进行地形校正,通过目视分析、光谱保留效果、地形校正效果、分类精度验证和阴阳陡坡光谱反射率一致性等评价指标对校正前后的影像进行对比,最终确定适合于林区的最佳地形校正模型。研究结果表明:(1)对连续山地丘陵且地形起伏较大的林区,SCS+C相比Minnaert+SCS和SCEDIL模型光谱保留性更好,校正前后各波段反射率均值相差小于4.32,且不存在过校正现象;通过校正后近红外波段反射率与太阳入射角余弦相关性判断3种模型的地形校正效果,SCS+C模型相关性最小,地形校正效果最好,Minnaert+SCS相关性略大,SCEDIL模型存在过校正现象;SCS+C模型校正后影像分类精度比校正前提高近3%,与Minnaert+SCS及SCEDIL模型相比高出近2%。(2)基于地形校正原理新增阴阳陡坡光谱反射率一致性评价方法,利用校正前后对阴阳陡坡NDVI的影响作为地形校正效果的评价指标,SCS+C校正效果最佳,两个典型区域校正前后阴阳陡坡光谱反射率均值的绝对偏差(10^(-2))分别由1.14减小至0.58和由1.67减小至0.49,校正后阴阳陡坡光谱一致性提升。综上所述,SCS+C模型优于Minnaert+SCS和SCEDIL,更适用于林区的地形校正。
In mountainous areas with complex terrain,terrain shadows have a great impact on the extraction of remote sensing image information.Therefore,terrain correction should be carried out on remote sensing images to eliminate terrain effects and restore the surface reflectance of terrain shadow areas.This article takes the eastern forest area of Liaoning province(Liaodong Forest Area) as the research area,and uses GF-1 WFV remote sensing images with a spatial resolution of 16 m.SCS+C,Minnaert+SCS and SCEDIL correction models are used to perform terrain correction on the original images.Visual analysis,spectral retention effect,terrain correction effect,classification accuracy verification and consistency of spectral reflectance on cloudy and sunny steep slopes are used to compare the images before and after correction,Finally determine the optimal terrain correction model suitable for forest areas.The research results indicate that:(1)for forest areas with continuous mountainous and hilly terrain and significant undulations,SCS+C has better spectral retention compared to Minnaert+SCS and SCEDIL models,with a difference of less than 4.32 in the mean reflectance of each band before and after calibration,and there is no overcorrection phenomenon.The terrain correction effect of the three models is judged by the correlation between the corrected near-infrared reflectance and the cosine of the solar incidence angle.The SCS+C model has the smallest correlation,the best terrain correction effect,the Minnaert+SCS model has a slightly larger correlation and the SCEDIL model has overcorrection phenomenon.The image classification accuracy of the SCS+C model after correction has improved by nearly 3% compared to before correction,and is nearly 2% higher than the SCEDIL models of Minnaert+SCS.(2)Based on the principle of terrain correction,a new evaluation method for the consistency of spectral reflectance on steep slopes of yin and yang has been added.The impact of NDVI on steep slopes of yin and yang before and after correction is used as the evaluation index for terrain correction effect.The SCS+C correction effect is the best,and the absolute deviation(10^(-2)) of the mean spectral reflectance on steep slopes of yin and yang before and after correction in two typical areas is reduced from 1.14 to 0.58 and from 1.67 to 0.49,respectively.After correction,the consistency of steep slopes of yin and yang is improved.In summary,the SCS+C model is superior to Minnaert+SCS and SCEDIL,which is more suitable for terrain correction in forest areas.
作者
王岩
刘英杰
武晋雯
孙龙彧
刘婧楠
许常华
WANG Yan;LIU Yingjie;WU Jinwen;SUN Longyu;LIU Jingnan;XU Changhua(School of Transportation and Surveying Engineering,Shenyang Jianzhu University,Shenyang 110168,China;Shenyang Institute of Atmospheric Environment,China Meteorological Administration,Shenyang 110166,China;Key Laboratory of Agricultural Meteorological Disasters in Liaoning Province,Shenyang 110166,China;Shenyang Meteorological Administration,Shenyang 110180,China;Huludao Meteorological Administration,Huludao 125080,China;Jinzhou Meteorological Administration,Jinzhou 121000,China)
出处
《测绘通报》
CSCD
北大核心
2024年第10期91-97,共7页
Bulletin of Surveying and Mapping
基金
辽宁省自然科学基金(2023-MS-042)
沈阳市中青年科技创新人才支持计划(RC210431)
中国气象局气象能力提升联合研究专项重点项目(23NLTSZ006)
中国气象局创新发展专项(CXFZ2023J055)
国家重点研发计划专项(2022YFF0801301,2022YDF2300201)。
