...
首页> 外文期刊>Catena: An Interdisciplinary Journal of Soil Science Hydrology-Geomorphology Focusing on Geoecology and Landscape Evolution >Automatic clod detection and boundary estimation from Digital Elevation Model images using different approaches.
【24h】

Automatic clod detection and boundary estimation from Digital Elevation Model images using different approaches.

机译:使用不同的方法从数字高程模型图像中自动进行土块检测和边界估计。

获取原文
获取原文并翻译 | 示例

摘要

Soil micro-topography characterization is an important issue for both soil science and remote sensing data interpretation. The objective of present study is to propose and discuss some methods dedicated to the automatic localization of clods (or big aggregates) on Digital Elevation Model images of soil. Two new image processing methods are introduced. The first one deals with the clod detection and the rough estimation of their boundaries. It is based on the adaptation of a famous segmentation algorithm applied to a modified surface enhancing the main features characterizing the clods. The second proposed method deals with the accurate estimation of clod boundaries. Clod boundaries are moved based on dynamic programming. Both proposed methods are validated on laboratory-built surfaces and on an actual surface recorded in an agricultural field. Results show that the proposed methods outperformed previously published methods. The proposed processing of DEM images allows the detection of the aggregates and clods deposited on the soil surface and the accurate estimation of their boundaries. The practice is facilitated by the proposition of default values for the parameters. The implications are the automatic analysis of DEM images that is a step towards micro-topography statistical characterization.
机译:土壤微观形貌的表征是土壤科学和遥感数据解释的重要问题。本研究的目的是提出和讨论一些专门用于土壤数字高程模型图像上土块(或大聚集体)自动定位的方法。介绍了两种新的图像处理方法。第一个处理凝块检测及其边界的粗略估计。它基于著名的分割算法的改编,该算法应用于改进的表面,从而增强了表征土块的主要特征。提出的第二种方法处理凝块边界的准确估计。基于动态编程来移动块边界。两种建议的方法都在实验室建造的表面和农业领域记录的实际表面上进行了验证。结果表明,所提出的方法优于以前发表的方法。提议的DEM图像处理功能可以检测出聚集在土壤表面的聚集体和凝块,并可以准确估计它们的边界。建议使用参数的默认值来简化此操作。含义是对DEM图像的自动分析,这是朝着微形貌统计特征迈出的一步。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号