Comparison Of Low Cost Commercial Unpiloted Digital Aerial Photogrammetry To Airborne Laser Scanning Across Multiple Forest Types In California
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Comparison Of Low Cost Commercial Unpiloted Digital Aerial Photogrammetry To Airborne Laser Scanning Across Multiple Forest Types In California
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Author : James E. Lamping
language : en
Publisher:
Release Date : 2021
Comparison Of Low Cost Commercial Unpiloted Digital Aerial Photogrammetry To Airborne Laser Scanning Across Multiple Forest Types In California written by James E. Lamping and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Forest surveys categories.
Science-based forest management requires quantitative information about forest attributes traditionally collected via sampled field plots in a forest inventory program. Remote sensing tools, such as active three-dimensional (3D) Light Detection and Ranging (lidar), are increasingly utilized to supplement and even replace field-based forest inventories. However, lidar remains cost prohibitive for smaller areas and repeat measurement, often limiting its use to single acquisitions of large contiguous areas. Recent advancements in unpiloted aerial systems (UAS), digital aerial photogrammetry (DAP) and high precision global positioning systems (HPGPS) have the potential to provide low-cost time and place flexible 3D data to support forest inventory and monitoring. The primary objective of this research was to assess the ability of low-cost commercial off the shelf UAS DAP and HPGPS to create accurate 3D data and predictions of key forest attributes, as compared to both lidar and field observations, in a wide range of forest conditions in California, USA. A secondary objective was to assess the accuracy of nadir vs. off-nadir UAS DAP, to determine if oblique imagery provides more accurate 3D data and forest attribute predictions. UAS DAP digital terrain models were comparable to lidar across sites and nadir vs. off-nadir imagery collection, although model accuracy using off-nadir imagery was very low in mature Douglas-fir forest. Surface and canopy height models were shown to have less agreement to lidar, with high canopy density sites captured with off-nadir imagery showing the lowest amounts of agreement. UAS DAP models accurately predicted key forest metrics when compared to field data and were comparable to predictions made by lidar. Although lidar provided more accurate estimates of forest attributes across a range of forest conditions, this study shows that UAS DAP models, when combined with low-cost HPGPS, can accurately predict key forest attributes across a range of forest types, canopies densities, and structural conditions throughout California.
Potential Of Modern Photogrammetry Versus Airborne Laser Scanning For Estimating Forest Variables In A Mountain Environment
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Author : Sami Ullah
language : en
Publisher:
Release Date : 2019
Potential Of Modern Photogrammetry Versus Airborne Laser Scanning For Estimating Forest Variables In A Mountain Environment written by Sami Ullah and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Abstract: Digital stereo aerial photographs are periodically updated in many countries and offer a viable option for the regular update of information on forest variables. We compared the potential of image-based point clouds derived from three different sets of aerial photographs with airborne laser scanning (ALS) to assess plot-level forest attributes in a mountain environment. The three data types used were (A) high overlapping pan-sharpened (80/60%); (B) high overlapping panchromatic band (80/60%); and (C) standard overlapping pan-sharpened stereo aerial photographs (60/30%). We used height and density metrics at the plot level derived from image-based and ALS point clouds as the explanatory variables and Lorey's mean height, timber volume, and mean basal area as the response variables. We obtained a RMSE = 8.83%, 29.24% and 35.12% for Lorey's mean height, volume, and basal area using ALS data, respectively. Similarly, we obtained a RMSE = 9.96%, 31.13%, and 35.99% and RMSE = 11.28%, 31.01%, and 35.66% for Lorey's mean height, volume and basal area using image-based point clouds derived from pan-sharpened stereo aerial photographs with 80/60% and 60/30% overlapping, respectively. For image-based point clouds derived from a panchromatic band of stereo aerial photographs (80%/60%), we obtained an RMSE = 10.04%, 31.19% and 35.86% for Lorey's mean height, volume, and basal area, respectively. The overall findings indicated that the performance of image-based point clouds in all cases were as good as ALS. This highlights that in the presence of a highly accurate digital terrain model (DTM) from ALS, image-based point clouds offer a viable option for operational forest management in all countries where stereo aerial photographs are updated on a routine basis. View Full-Text
Assessing The Potential Of Airborne Laser Scanning And Digital Anlysis Of Aerial Photogrammetry In Forestry Applications
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Author : Inga Sokvitne
language : en
Publisher:
Release Date : 2004
Assessing The Potential Of Airborne Laser Scanning And Digital Anlysis Of Aerial Photogrammetry In Forestry Applications written by Inga Sokvitne and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Aerial photography in forestry categories.
An Assessment Of Small Unmanned Aerial Systems In Support Of Sustainable Forestry Management Iniatives
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Author : Michael P. McClelland
language : en
Publisher:
Release Date : 2018
An Assessment Of Small Unmanned Aerial Systems In Support Of Sustainable Forestry Management Iniatives written by Michael P. McClelland and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Drone aircraft categories.
"Sustainable forest management practices are receiving renewed attention in the growing effort to make efficient long-term use of natural resources. Sustainable management approaches require accurate and timely measurement of the world’s forests to monitor volume, biomass, and changes in sequestered carbon. It is in this context that remote sensing technologies, which possess the capability to rapidly capture structural data of entire forests, have become a key research area. Laser scanning systems, also known as lidar (light detection and ranging), have reached a maturity level where they may be considered a standard data source for structural measurements of forests; however, airborne lidar mounted on manned aircraft can be cost-prohibitive. The increasing performance capabilities and reduction of cost associated with small unmanned aerial systems (sUAS), coupled with the decreasing size and mass of lidar sensors, provide the potential for a cost-effective alternative. Our objectives for this study were to assess the extensibility of established airborne lidar algorithms to sUAS data and to evaluate the use of more cost-effective structure-from-motion (SfM) point cloud generation techniques from imagery obtained by the sUAS. A data collection was completed by both manned and sUAS lidar and imaging systems in Lebanon, VA and Asheville, NC. Both systems produced adequately dense point clouds with the manned system exceeding 30 pts/m^2 and the sUAS exceeding 400 pts/m^2. A cost analysis, two carbon models and a harvest detection algorithm were explored to test performance. It was found that the sUAS performed similarly on one of the two biomass models, while being competitive at a cost of $8.12/acre, compared to the manned aircraft’s cost of $8.09/acre, excluding mobilization costs of the manned system. On the biomass modeling front, the sUAS effort did not include enough data for training the second model or classifier, due to a lack of samples from data corruption. However, a proxy data set was generated from the manned aircraft, with similar results to the full resolution data, which then was compared to the sUAS data from four overlapping plots. This comparison showed good agreement between the systems when ingested into the trained airborne platform’s data model (RMSE = 1.77 Mg/ha). Producer’s accuracy, User’s accuracy, and the Kappa statistic for detection of harvested plots were 94.1%, 92.2% and 89.8%, respectively. A leave-one-out and holdout cross validation scheme was used to train and test the classifier, using 1000 iterations, with the mean values over all trials presented in this study. In the context of an investigative study, this classifier showed that the detection of harvested and non-harvested forest is possible with simple metrics derived from the vertical structure of the forest. Due to the closed nature of the forest canopy, the SfM data did not contain many ground returns, and thus, was not able to match the airborne lidar’s performance. It did, however, provide fine detail of the forest canopy from the sUAS platform. Overall, we concluded that sUAS is a viable alternative to airborne manned sensing platforms for fine-scale, local forest assessments, but there is a level of system maturity that needs to be attained for larger area applications."--Abstract.
Advancing Low Cost Mobile Remote Sensing Technologies For Forest Resource Management
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Author : Brennan Holderman
language : en
Publisher:
Release Date : 2018
Advancing Low Cost Mobile Remote Sensing Technologies For Forest Resource Management written by Brennan Holderman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Advances in active sensor technology have made them more readily available than ever before. Light detection and ranging (LiDAR) technology has been used as a tool in forest management for several decades to model tree characteristics at both the stand and plot levels. From aerial mapping campaigns, to static terrestrial scanning, tree structure estimates derived from high density point clouds have proven to be accurate. Historical access to these technologies and services have often been prohibitively expensive, with terrestrial laser scanner costs exceeding six-figures and aerial campaigns costing tens-of-thousands of dollars, daily. This has limited their use in forestry to high-value, or short-rotation, species such as loblolly pine (Pinus taeda) across the American South and Eucalyptus in the tropics. In addition, the conifers across the western U.S. and Europe have been the subject of extensive LiDAR research and deployment. The mixed hardwood deciduous forests characteristic of south-central Pennsylvania present challenges to LiDAR mapping on multiple fronts. The complex upper canopy structure makes isolating individual trees from above difficult. Diverse and variable topography can present significant data capture and processing issues. In addition, present market values of eastern hardwoods limit the stakeholders ability to invest additional resources for advanced inventory techniques and technology. However, as the technology matures, it could allow for more advanced sampling techniques, such as 3P, at similar costs to present plot-based methods.Rapid expansion in the autonomous vehicle sector has created the need for affordable robotic vision sensors. The sensor of choice for many automotive manufacturers are small, affordable LiDAR units. Due to this, large capital investments are no longer required to rapidly collect dense point cloud data. Small, modular LiDAR sensors from companies such as Velodyne LiDAR can now be had for $4,000 USD. The availability of these sensors is only the first step to integrating them into natural resource management solutions and tools. This study has focused on standardizing both the protocols by which a low-cost laser scanner can be deployed in the field, how those data are collected and processed, and an evaluation of the individual stem detection and diameter estimates produced from the dense point clouds. Developing free and open source software solutions, processes and schematics was central to the aim of this study. Chapter 2 provides extensive documentation of system requirements, set-up parameters, embedded computer systems and required software to successfully capture LiDAR data in a variety of configurations. Significant effort was put forth to create a modular LiDAR system that can be deployed both aerially, and terrestrially, with minimal downtime between configurations. To assess the capacity of the system, it was deployed in both static and mobile terrestrial configurations to collect plot-level data in forested stands. Data were captured, processed and compared to in-situ measures taken from 7.5 m plots at three site locations. Estimates of stem diameter, taper, branching structure, and height are central measures to evaluating both biomass and potential market value of individual trees. The traditionally required field work to assess both value and volume are time- and labor-intensive. Two algorithms were evaluated for their ability to detect individual stems and estimate their diameter in the collected point clouds (Chapter 3). The LAS2Rings and TreeLS algorithms use the Hough Transform to identify stem locations and RANSAC fitting to estimate diameter. The algorithms were both able to successfully produce stem locations and diameters. However, due to the small n, statistically significant conclusions could not be drawn when comparing the in-situ and cloud measures. Other limitations were observed throughout the study and potential solutions were addressed to better process and capture data (Chapter 4).The technology presented and developed within this study shows considerable promise. Additional research is required to fully realize its potential as a widely adopted tool for natural resource land managers. This would include refinement of the capture methodology, optimization of the co-registration algorithms, and a substantial increase in in-situ measures for further statistical comparison.
International Aerospace Abstracts
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Author :
language : en
Publisher:
Release Date : 1997
International Aerospace Abstracts written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Aeronautics categories.
International Forum
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Author : Petawawa National Forestry Institute
language : en
Publisher: [Chalk River, Ont.] : Petawawa National Forestry Institute
Release Date : 1993
International Forum written by Petawawa National Forestry Institute and has been published by [Chalk River, Ont.] : Petawawa National Forestry Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Aerial photography in forestry categories.
The objective of the Forum was to reach a consensus on what are the mapping and forestry applications that airborne scanner technology can fill now or in the near future; what are the appropriate sensors, processing systems, and analysis methods; what developments are needed to get the applications implemented; what expertise is available; and what is the likelihood of success. The key to achieving this objective was to develop an understanding by all participants of the application problems, financial constraints, technical problems, and scientific issues. Part 1 of this report consists of syntheses of introductory presentations and the work session discussions, as well as a summary of the wrap-up session. Part 2 contains the papers presented and the banquet speech is in part 3. Appendices include the final agenda, questions for the work sessions, an executive summary of other relevant initiatives mentioned during the Forum, and a list of participants.
Calibration Of Full Waveform Airborne Laser Scanning Data For 3d Object Segmentation
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Author : Fanar Mansour Abed Abed
language : en
Publisher:
Release Date : 2012
Calibration Of Full Waveform Airborne Laser Scanning Data For 3d Object Segmentation written by Fanar Mansour Abed Abed and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Digital Aerial Survey
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Author : Ron Graham (Ph. D.)
language : en
Publisher:
Release Date : 2002
Digital Aerial Survey written by Ron Graham (Ph. D.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
CD-ROM contains: Air survey logistics planner, tables 12.3, 12.4, 12.5, 12.6 and sample MF-DMC imagery.
Extraction Of Digital Terrain Models From Airborne Laser Scanning Data Based On Transfer Learning
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Author : Weiya Ye
language : en
Publisher:
Release Date : 2019
Extraction Of Digital Terrain Models From Airborne Laser Scanning Data Based On Transfer Learning written by Weiya Ye and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Artificial intelligence categories.
With the rapid urbanization, timely and comprehensive urban thematic and topographic information is highly needed. Digital Terrain Models (DTMs), as one of unique urban topographic information, directly affect subsequent urban applications such as smart cities, urban microclimate studies, emergency and disaster management. Therefore, both the accuracy and resolution of DTMs define the quality of consequent tasks. Current workflows for DTM extraction vary in accuracy and resolution due to the complexity of terrain and off-terrain objects. Traditional filters, which rely on certain assumptions of surface morphology, insufficiently generalize complex terrain. Recent development in semantic labeling of point clouds has shed light on this problem. Under the semantic labeling context, DTM extraction can be viewed as a binary classification task. This study aims at developing a workflow for automated point-wise DTM extraction from Airborne Laser Scanning (ALS) point clouds using a transfer-learning approach on ResNet. The workflow consists of three parts: feature image generation, transfer learning using ResNet, and accuracy assessment. First, each point is transformed into a feature image based on its elevation differences with neighbouring points. Then, the feature images are classified into ground and non-ground using ResNet models. The ground points are extracted by remapping each feature image to its corresponding points. Lastly, the proposed workflow is compared with two traditional filters, namely the Progressive Morphological Filter (PMF) and the Progress TIN Densification (PTD). Results show that the proposed workflow establishes an advantageous accuracy of DTM extraction, which yields only 0.522% Type I error, 4.84% Type II error and 2.43% total error. In comparison, Type I, Type II and total error for PMF are 7.82%, 11.6%, and 9.48%, for PTD are 1.55%, 5.37%, and 3.22%, respectively. The root mean squared error of interpolated DTM of 1 m resolution is only 7.3 cm. Moreover, the use of pre-trained weights largely accelerated the training process and enabled the network to reach unprecedented accuracy even on a small amount of training set. Qualitative analysis is further conducted to investigate the reliability and limitations of the proposed workflow.