ExtSpecR: An R Package and Tool for Extracting Tree Spectra from UAV-Based Remote Sensing.

IF 7.6 1区 农林科学 Q1 AGRONOMY
Plant Phenomics Pub Date : 2023-10-16 eCollection Date: 2023-01-01 DOI:10.34133/plantphenomics.0103
Zhuo Liu, Mahmoud Al-Sarayreh, Cong Xu, Federico Tomasetto, Yanjie Li
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引用次数: 0

Abstract

The development of unmanned aerial vehicle (UAV) remote sensing has been increasingly applied in forestry for high-throughput and rapid acquisition of tree phenomics traits for various research areas. However, the detection of individual trees and the extraction of their spectral data remain a challenge, often requiring manual annotation. Although several software-based solutions have been developed, they are far from being widely adopted. This paper presents ExtSpecR, an open-source tool for spectral extraction of a single tree in forestry with an easy-to-use interactive web application. ExtSpecR reduces the time required for single tree detection and annotation and simplifies the entire process of spectral and spatial feature extraction from UAV-based imagery. In addition, ExtSpecR provides several functionalities with interactive dashboards that allow users to maximize the quality of information extracted from UAV data. ExtSpecR can promote the practical use of UAV remote sensing data among forest ecology and tree breeding researchers and help them to further understand the relationships between tree growth and its physiological traits.

Abstract Image

Abstract Image

Abstract Image

ExtSpecR:一个用于从无人机遥感中提取树木光谱的R包和工具。
无人机遥感技术的发展已越来越多地应用于林业,以高通量和快速获取各个研究领域的树木表型特征。然而,单个树木的检测和光谱数据的提取仍然是一个挑战,通常需要手动注释。尽管已经开发了几种基于软件的解决方案,但它们远未被广泛采用。本文介绍了ExtSpecR,这是一种用于林业中单一树木光谱提取的开源工具,具有易于使用的交互式web应用程序。ExtSpecR减少了单树检测和注释所需的时间,并简化了从无人机图像中提取光谱和空间特征的整个过程。此外,ExtSpecR还提供了一些交互式仪表板功能,使用户可以最大限度地提高从无人机数据中提取的信息质量。ExtSpecR可以促进无人机遥感数据在森林生态学和树木育种研究人员中的实际应用,并帮助他们进一步了解树木生长与其生理特征之间的关系。
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来源期刊
Plant Phenomics
Plant Phenomics Multiple-
CiteScore
8.60
自引率
9.20%
发文量
26
审稿时长
14 weeks
期刊介绍: Plant Phenomics is an Open Access journal published in affiliation with the State Key Laboratory of Crop Genetics & Germplasm Enhancement, Nanjing Agricultural University (NAU) and published by the American Association for the Advancement of Science (AAAS). Like all partners participating in the Science Partner Journal program, Plant Phenomics is editorially independent from the Science family of journals. The mission of Plant Phenomics is to publish novel research that will advance all aspects of plant phenotyping from the cell to the plant population levels using innovative combinations of sensor systems and data analytics. Plant Phenomics aims also to connect phenomics to other science domains, such as genomics, genetics, physiology, molecular biology, bioinformatics, statistics, mathematics, and computer sciences. Plant Phenomics should thus contribute to advance plant sciences and agriculture/forestry/horticulture by addressing key scientific challenges in the area of plant phenomics. The scope of the journal covers the latest technologies in plant phenotyping for data acquisition, data management, data interpretation, modeling, and their practical applications for crop cultivation, plant breeding, forestry, horticulture, ecology, and other plant-related domains.
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