Land Use Classification from Lidar Data and Ortho‐Images in a Rural Area
Land Use Classification from Lidar Data and Ortho‐Images in a Rural Area
复制标题
DOI：
10.1111/j.1477-9730.2012.00698.x
复制
发表时间：
2012-12
期刊：
影响因子：
--
通讯作者：
S. Buján;E. González-Ferreiro;Fabián Reyes-Bueno;Laura Barreiro-Fernández;R. Crecente;D. Miranda
中科院分区：
文献类型：
--
作者：
S. Buján;E. González-Ferreiro;Fabián Reyes-Bueno;Laura Barreiro-Fernández;R. Crecente;D. Miranda
获取农村景观类型分布的信息是西班牙农村研究中的一个活跃的研究课题。本文提出了一种新的基于分层对象的分类方法，结合激光雷达数据和航空影像，自动检测农村地区的各种土地利用类别。鉴于西班牙大部分地区即将获得低密度激光雷达数据（0.5脉冲/m2），本文评估了所提出的方法在各种激光雷达数据密度下的可行性和准确性。这样的评估使用两种方法进行：首先，基于最终分类，对于具有四种不同密度的航空图像和激光雷达数据集的组合，其总体准确度超过96%，kappa指数超过0.95;其次，仅基于被分类为建筑物的区域。在第二种方法中，在像素和对象级别的建筑物检测的分类的准确性进行了评估。面向对象的建筑物分类的正确性指数超过99%，完整性指数约为95%。结果表明，分类和地面实况数据之间的高度一致性。
Obtaining information on the distribution of rural landscape types is an active research topic within Spanish rural studies. This paper presents a new hierarchical object‐based classification method for the automatic detection of various land use classes in a rural area, combining lidar data and aerial images. In view of the upcoming availability of low‐density lidar data (0·5 pulses/m2) for most of the territory of Spain, this paper assesses the feasibility and accuracy of the proposed method for various lidar data densities. Such an assessment was conducted using two approaches: firstly, based on the final classification, which produced an overall accuracy over 96% and a kappa index above 0·95 for the combinations of the aerial image and lidar data‐sets with four different densities; and secondly, based solely on the areas classified as buildings. In the second approach, the accuracy of the classification for building detection at pixel and object level was assessed. The object‐oriented classification of buildings produced an index of correctness of over 99% and an index of completeness of about 95%. The results reveal a high agreement between classification and ground truth data.