Suppr超能文献

利用 SAR 干涉测量技术估算异龄林和混交林的树木高度和垂直结构。

Estimation of trees height and vertical structure using SAR interferometry in uneven-aged and mixed forests.

机构信息

Faculty of Environmental and Natural Resources, Science and Research Branch of Islamic Azad University, Tehran, Iran.

K.N. Toosi University of Technology, Tehran, Iran.

出版信息

Environ Monit Assess. 2021 Apr 24;193(5):298. doi: 10.1007/s10661-021-09095-x.

Abstract

Estimation of forest height is an important parameter of stands structure that aids in the determination of forest biomass, successional stage dynamics, and the decision of the type of forest management. In addition, estimating the height of trees especially in uneven-aged, massive, and multi-storied forest stands always faces challenges in kind of inventory and accuracy of the assessment. In this research, the synthetic aperture radar (SAR) interferometry technique was used to estimate the height of trees for determining the vertical structure of forest. For this purpose, we focused on an area at the mixed and uneven-aged forest in Iran and evaluated the potential of Envisat ASAR data to characterize the tree height in the forest patches and the digital surface model (DSM) was produced via SAR interferometry. The height of trees and the vertical structure of the forest stands were estimated using produced DSM and Digital elevation Model (DEM). Furthermore, the accuracy of estimated parameters was evaluated with real ground data (11 × 1 ha (100 × 100 m) sample plots). The results indicated that the estimated height of trees was meanly 7.69 m with a 22 m STDV over the reality. Furthermore, the vertical structure in all the plots was three-storied that they are the same as ground truth, but the percentage of the share of trees in the under and middle story was different from the ground truth. In conclusion, the tree height and vertical structure of forest stands can be determined with acceptable accuracy via SAR interferometry and Envisat ASAR data.

摘要

森林高度估测是林分结构的一个重要参数,有助于确定森林生物量、演替阶段动态和森林管理类型的决策。此外,估算树木,特别是在异龄、块状和多层林分中的树木高度,在某种程度上总是面临着清查和评估准确性的挑战。在这项研究中,合成孔径雷达(SAR)干涉测量技术被用于估计树木高度,以确定森林的垂直结构。为此,我们专注于伊朗混合异龄林地区,并评估了 Envisat ASAR 数据在描述森林斑块中树木高度方面的潜力,并通过 SAR 干涉测量生成数字表面模型(DSM)。利用生成的 DSM 和数字高程模型(DEM)来估计树木高度和林分的垂直结构。此外,还利用真实地面数据(11×1 公顷(100×100 米)样本)评估了估计参数的准确性。结果表明,树木的估计高度平均为 7.69 米,标准偏差为 22 米,与实际情况相比。此外,所有样地的垂直结构均为三层,与地面真实情况相同,但底层和中层树木的比例与地面真实情况不同。总之,通过 SAR 干涉测量和 Envisat ASAR 数据可以以可接受的精度确定森林林分的树木高度和垂直结构。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验