激光雷达数据在数字地形模型中的精度评估及改进研究

Research on Accuracy Evaluation and Improvement of LiDAR Data in Digital Terrain Models

本文的研究目的是解决数字地形模型构建中的挑战,特别关注激光雷达数据的应用和精度方面的问题。为了实现这一目标,采取了多重方法。在方法方面,首先,明确定义了精度评估指标和方法,包括高程中误差(RMSE)、绝对高程误差、Kappa系数和交叉验证等,以确保对DTM质量的准确评估;其次,相关人员进行了一系列对比实验,将采用改进方法构建的DTM与传统DTM进行比较,这些实验涵盖了复杂地形和植被覆盖较多的区域,以全面评估改进方法的有效性;最后,文章进行了多个实际应用案例研究,包括电力勘测设计、水资源管理和灾害监测等领域,以展示改进的激光雷达数据在实际应用中的表现和效果。研究结果表明,改进的DTM相对于传统方法在高程精度和地物分类精度上表现出明显的优势,尤其在复杂地形和植被覆盖较多的区域。这些结果为数字地形模型的质量提升和可用性提供了有力支持。总之,本研究通过明确定义问题、采用多重方法进行实验和案例研究,为改进数字地形模型的构建过程提供了有益的见解,从而更好地满足各领域的需求,推动现代科学和工程领域的发展。

Our research objective is to address the challenges in constructing digital terrain models,with a particular focus on the application and accuracy of LiDAR data.To achieve this goal,we have adopted multiple methods.In terms of methods,firstly,we have clearly defined accuracy evaluation indicators and methods,including Mean Square Error(RMSE),Absolute Elevation Error,Kappa Coefficient,and Cross validation,to ensure accurate evaluation of DTM quality.Secondly,we conducted a series of comparative experiments to compare the DTM constructed using improved methods with traditional DTM.These experiments covered areas with complex terrain and high vegetation coverage to comprehensively evaluate the effectiveness of the improved methods.Finally,we conducted multiple practical application case studies,including power survey and design,water resource management,and disaster monitoring,to demonstrate the performance and effectiveness of improved LiDAR data in practical applications.The research results indicate that the improved DTM has significant advantages over traditional methods in terms of elevation accuracy and ground object classification accuracy,especially in areas with complex terrain and high vegetation coverage.These results provide strong support for the quality improvement and usability of digital terrain models.In summary,this study provides useful insights for improving the construction process of digital terrain models by clearly defining problems,using multiple methods for experiments,and conducting case studies,in order to better meet the needs of variousfields and promote the development of modern science and engineering.