基于地形特征的无人机遥感梯田影像边缘提取方法

doi:10.12133/j.smartag.2019.1.4.201908-SA005

摘要/Abstract

摘要：

梯田具有蓄水固沙的作用，是旱作农业区重点建设的高产稳产农田设施，为粮食增产、农民增收提供了有力保障。因仅基于影像数据采用边缘提取方法进行梯田区域分割效果不理想，及时准确地掌握梯田信息较为困难。无人机遥感技术的不断发展为高精度梯田地形信息的获取提供了新方法。本研究以甘肃省榆中县为例，首先从数字高程模型DEM数据中提取坡度，将正射影像与坡度数据融合，并通过基于Canny算子的粗边缘提取方法和基于多尺度分割的精细边缘提取方法，对比分析坡度对无人机遥感梯田影像边缘提取的影响。试验结果表明，正射影像和坡度融合的提取效果均优于单一的正射影像数据提取效果，粗边缘提取方法中正射影像和坡度融合的数据源精度平均提高了23.97%，精细边缘提取方法中正射影像和坡度融合的数据源精度平均提高了17.84%。研究表明，在无人机遥感梯田影像边缘提取中加入一定的地形特征，可以取得更好的边缘提取效果。

关键词: 无人机影像, 梯田, 边缘提取, 坡度, 区域分割

Abstract:

Terraces achieve water storage and sediment function by slowing down the slope and soil erosion. This kind of terraced or wave-section farmland built along the contour line on is a high-yield and stable farmland facility with key construction in the dry farming area. It provides a strong guarantee for increasing grain production and farmers' income. In recent years, Gansu province has carried out a large amount of construction on terraces, however, due to the poor quality of the previous construction and management, the terraced facilities are in danger of being destroyed. In order to prevent and repair the terraces, it is necessary to timely and accurately extract the terrace information. The segmentation of terraces can be obtained by edge extraction, but the effect of satellite data is not ideal. With the continuous development of remote sensing technology of drones, the acquisition of high-precision terrace topographic information has become possible. In this research, the slope is extracted from the digital elevation model data in the data preprocessing stage, then the orthophoto data of the three experimental areas are merged with the corresponding slope data, respectively. Then the rough edge extraction method based on Canny operator and the fine edge extraction method based on multi-scale segmentation are used to perform edge detection on two data sources. Finally, the influence of slope on the extraction of terraced edges of remote sensing images of UAVs was analyzed based on the overall accuracy of edge detection and user accuracy. The experimental results showed that, in the rough edge extraction method, the data source accuracy of the fusion slope and image was improved by 23.97% in the OA precision evaluation, and the average improvement in the UV accuracy was 20.68%. In the fine edge extraction method, the accuracy based on the data source 2 was also increased by 17.84% on average in the OA accuracy evaluation of the data source 1, and by an average of 19.0% in the UV accuracy evaluation. The research shows that in the extraction of terraced edges of UAV remote sensing images, adding certain terrain features can achieve better edge extraction results.

Key words: UAV image, terrace, edge extraction, slope, region segmentation

中图分类号:

TN957.52

杨亚男, 康洋, 樊晓, 常亚栋, 张瀚文, 张宏鸣. 基于地形特征的无人机遥感梯田影像边缘提取方法[J]. 智慧农业, 2019, 1(4): 50-61.

Yang Yanan, Kang Yang, Fan Xiao, Chang Yadong, Zhang Hanwen, Zhang Hongming. Edge extraction method of remote sensing UAV terrace image based on topographic feature[J]. Smart Agriculture, 2019, 1(4): 50-61.

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