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4 results for “tree diameter estimation”
Supporting data sets for "Estimating Carbon Fixation of Plant Organs for Afforestation Monitoring using a Process-based Ecosystem Model and Ecophysiological Parameter Optimization". (the survey of tree breast diameter and tree height in 11-year old Eucommia ulmoides plantation, values of simulation results used in figures and tables.)
<p>Supporting data sets for Miyauchi et al., Ecology and Evolution, 2019 (accepted).</p> <p>The files store: </p> <p>(1) The survey of tree breast diameter and tree height in <em>Eucommia ulmoides</em> plantation<em>.</em> The ring and stem analysis and dry weight of seven harvested sample trees in the plantation.</p> <p>(2) Values of optimization result used fig.7.</p> <p>(3) Values of prediction result used fig.8. and table 4.</p> <p>(4) Values of optimized parameters by optimization methods, parameter range and constrain.</p>
Data from: Robust single-image tree diameter estimation with mobile phones
<p>Ground-based forest inventories are a key element of forest carbon monitoring, reporting, and verification schemes and a cornerstone of forest ecology research. Recent work using LiDAR-equipped mobile phones to automate parts of the forest inventory process assumes that tree trunks are well-spaced and visually unoccluded, or else requires manual intervention or offline processing to identify and measure tree trunks.</p> <p>In this paper, we design an algorithm that exploits a low-cost smartphone LiDAR sensor to estimate trunk diameter automatically from a single image in complex and realistic field conditions. We implement our design and build it into an app on a Huawei P30 Pro smartphone, demonstrating that the algorithm has low enough computational cost to run on this commodity platform in near real-time.</p> <p>We evaluate our app in three different forests across three seasons and find that in a corpus of 97 sample tree images, our app estimates trunk diameter with RMSE of 3.7 cm (R<sup>2</sup> = .97; 8.0% mean error) compared to manual DBH measurement. It achieves a 100% tree detection rate while reducing surveyor time by up to a factor of 4.6.</p> <p>Our work contributes to the search for a low-cost, low-expertise alternative to Terrestrial Laser Scanning that is nonetheless robust and efficient enough to compete with manual methods. We highlight the challenges that low-end mobile depth scanners face in occluded conditions and offer a lightweight, fully automatic approach for segmenting depth images and estimating trunk diameter despite these challenges. Our approach lowers the barriers to in situ forest measurement outside of an urban or plantation context, maintaining a tree detection and accuracy rate comparable to previous mobile phone methods even in complex forest conditions.</p>
Data from: Robust single-image tree diameter estimation with mobile phones
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Data From: An App for Tree Trunk Diameter Estimation from Coarse Optical Depth Maps
<p><strong>Overview</strong></p> <p>This dataset contains RGB and depth images (raw images and text files) of tree trunks collected using Google ARCore. It has 378 samples from four countries, with DBH ranging from 4.8-155.3cm. We annotated aspects like trunk shapes, leaning, lighting conditions when captured, etc. The data was originally intended for evaluating our designed tree diameter measurement app (https://github.com/MingyueX/GreenLens).</p> <p><em>Note: treedata.zip is deprecated, please download treedata_version_2.zip instead.</em></p> <p><strong>Data introduction</strong></p> <ul> <li>treedata_version_2.zip contains two folders - <em>rgb </em>and <em>depthtxt </em>- representing raw RGB images and depth text files respectively.</li> <li>data_label.xlsx includes the labels and corresponding descriptions.</li> </ul> <p><strong>Usage Notes</strong></p> <p>The <em>rgb </em>folder contains jpg images with 480*360 resolution.</p> <p>The files with no extension in the <em>depthtxt</em> folder are stored in the format as x-coordinate of pixel, y-coordinate of pixel, depth measurement of pixel and confidence value.</p>
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