基于形态学建筑物指数的城市建筑物提取及其高度估算

通过引入高分辨率影像的形态学建筑物指数和阴影指数,并结合面向对象的地物信息提取思想,准确地提取出城市建筑物及其阴影,进而实现了城市建筑物的高度估算。首先,利用形态学建筑物指数的多方向多尺度特征,将建筑物与邻近光谱相似的道路目标进行分离；其次,采用双阈值策略提取建筑物与相应的阴影,进一步提高了建筑物的提取精度；最后,根据成像时刻卫星和太阳的高度角、方位角,建立建筑物阴影长度与建筑物高度的估算模型。试验利用厦门市思明区软件园资源三号(ZY\|3)数据进行城市建筑物提取及其高度估算,证实该方法能够较准确地估算出建筑物的高度信息,并且比基于SVM的监督分类方法具有更高的建筑物提取精度,建筑物高度估算的中误差可达±1 m。

Building Extraction and Its Height Estimation over Urban Areas based on Morphological Building Index

The paper introduced the morphological building/shadow indexes derived from high spatial resolution image,incorporated with object\|based information extraction routine,to extract the city buildings and its shadow to accurately and further estimate the height of buildings.Firstly,morphological building index with the multi\|scale and multiple directional features were used to separate buildings from the neighboring roads with the similar spectra.Secondly,a dual\|threshold strategy was applied to further improve the extracted accuracy of buildings.In the end,the height of buildings was estimated by the model,where the relationship among the length of buildings shadow,the azimuth and elevation of sun,and satellite is constructed.A case study with ZY-3 dataset,located in Xiamen Software Park,was used to validate the algorithm.Experimental results demonstrate that the proposed method can significantly improve the accuracy of buildings extraction,when compared with the supervised classification method with Support Vector Machine (SVM).Moreover,the mean square errors of buildings height eatimation is about ±1 m.