Journal ArticleDOI
Estimation of wetland vegetation height and leaf area index using airborne laser scanning data
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TLDR
In this paper, the authors explored the potential of estimating vegetation structural parameters such as vegetation height and leaf area index (LAI) for short wetland vegetation using airborne discrete-return LiDAR data.About:
This article is published in Ecological Indicators.The article was published on 2015-01-01. It has received 89 citations till now. The article focuses on the topics: Enhanced vegetation index & Vegetation (pathology).read more
Citations
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Journal ArticleDOI
An Overview of Global Leaf Area Index (LAI): Methods, Products, Validation, and Applications
TL;DR: In this article, the authors provide a comprehensive analysis of field measurements and remote sensing estimation methods, the product validation methods and product uncertainties, and the application of LAI in global studies.
Journal ArticleDOI
Review of indirect optical measurements of leaf area index: Recent advances, challenges, and perspectives
Guangjian Yan,Ronghai Hu,Ronghai Hu,Jinghui Luo,Marie Weiss,Hailan Jiang,Xihan Mu,Donghui Xie,Wuming Zhang +8 more
TL;DR: In this article, the authors comprehensively review the temporal development, theoretical framework, and issues of indirect leaf area index (LAI) measurement, followed by current methods, instruments, and platforms.
Journal ArticleDOI
Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system
TL;DR: In this article, hundreds of stereo images with very high resolution were collected to estimate H canopy and AGB of maize using a low-cost unmanned aerial vehicle (UAV) system.
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Site-based and remote sensing methods for monitoring indicators of vegetation condition: An Australian review
TL;DR: In this paper, the authors consider vegetation condition to include compositional, structural and functional attributes of vegetation relative to undisturbed vegetation of the same type, and find that remote sensing methods have the advantage of offering broad scale automated and repeatable methods for monitoring indicators of vegetation condition, but when combined with detailed ecological site-based data, together can improve monitoring for answering ecological questions.
Journal ArticleDOI
A review of methodologies and success indicators for coastal wetland restoration
TL;DR: In this article, the authors reviewed the methodology of coastal wetland restoration and criteria for success evaluation, and then summarized the issues for current wetland rehabilitation and success evaluation based on literature review.
References
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Journal ArticleDOI
Lidar Remote Sensing for Ecosystem Studies
TL;DR: Lidar has been shown to accurately estimate aboveground biomass and leaf area index even in those high-biomass ecosystems where passive optical and active radar sensors typically fail to do so as discussed by the authors.
Journal ArticleDOI
Review of methods for in situ leaf area index determination Part I. Theories, sensors and hemispherical photography
TL;DR: It is suggested that the use of a digital camera with high dynamic range has the potential to overcome a number of described technical problems related to indirect LAI estimation.
Journal ArticleDOI
Review of methods for in situ leaf area index (LAI) determination: Part II. Estimation of LAI, errors and sampling
TL;DR: In this paper, the theoretical background of modeling the gap fraction and the leaf inclination distribution is presented and different techniques used to derive leaf area index (LAI) and leaf inclination angle from gap fraction measurements are reviewed.
Journal ArticleDOI
LiDAR remote sensing of forest structure
TL;DR: In this article, LiDAR data is used to estimate the canopy height of a single tree in a forest and to model the above-ground biomass and canopy volume of the forest.
Journal ArticleDOI
Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review
TL;DR: In this paper, the authors provide an overview on the status of remote sensing applications in discriminating and mapping wetland vegetation, and estimating some of the biochemical and biophysical parameters of the vegetation.
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