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使用植被和形态学复合波器与SfM点云开发流DTM生成方法

Hyeokjin Lee¹, Jaejun Gou¹, Jinseok Park²

¹Department of Rural System Engineering, Global Smart Farm Convergence Major, Seoul National University, Seoul, 08826, South Korea.

Scientific reports

|April 4, 2025

概括

本研究介绍了一种先进的方法,用于创建精确的数字地形模型 (DTM) 的流使用结构从运动 (SfM) 无人机数据. SfM方法为绘制沿海区域地图的传统调查提供了一种高效且具有成本效益的替代方案.

科学领域:

地质科学地质科学
遥感遥感遥感遥感
这是一种摄影计量技术 (photogrammetry).

背景情况:

传统的流量调查是耗时的,昂贵的,缺乏连续的数据.
准确的数字地形模型 (DTM) 对于了解水文过程和管理河岸区域至关重要.
现有方法的局限性要求开发先进,高效的DTM生成技术.

研究的目的:

开发和评估一种先进的方法,使用结构从运动 (SfM) 数据生成高质量的流的DTM.
确定最佳的植被和形态波器组合,以处理沿海环境中的SfM数据.
评估拟议的基于SfM的DTM生成方法的效率和准确性.

主要方法:

使用幻影4多光谱无人机图像,采用了来自运动的结构 (SfM) 光谱法.
在Bokha溪的四个截面上进行了平面调查以进行地面验证.
应用了各种植被 (NDVI,NDI) 和形态 (ATIN,CSF) 过器,并使用平均绝对误差 (MAE) 和根平均平方误差 (RMSE) 进行了评估.

主要成果:

整合NDVI和CSF过器在植被地区表现出卓越的性能.
单次NDVI应用在赤裸的地面区域产生了最低的MAE.
通过SfM方法有效地去除了海植被,达到0.299米的总体MAE和0.375米的RMSE.

结论:

拟议的基于SfM的方法提供了一种高效且具有成本效益的解决方案,用于生成精确的溪流和河岸区域的DTM.
这种先进的技术克服了传统现场调查的局限性,提供连续的数据和缩短的调查时间.
这些发现支持基于无人机的SfM在植被水生环境中的水文和地形学研究的更广泛应用.

关键词:

数字地形模型 (DTM) 是一个数字地形模型.形态学过器是形态学过器一个点云点云.运动结构 (SfM)植物过器是一种植物过器.

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