Estimating Forest Structural Characteristics With Airborne Lidar Scanning And A Near Real Time Profiling Laser Systems
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Estimating Forest Structural Characteristics With Airborne Lidar Scanning And A Near Real Time Profiling Laser Systems
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Author : Kaiguang Zhao
language : en
Publisher:
Release Date : 2010
Estimating Forest Structural Characteristics With Airborne Lidar Scanning And A Near Real Time Profiling Laser Systems written by Kaiguang Zhao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatiallyexplicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for realtime remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real- time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real- time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for realtime forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of airborne scanning or profiling laser systems for remotely measuring various forest structural attributes at a range of scales, i.e., from individual tree, plot, stand and up to regional levels. The system not only provides a regional assessment tool, one that can be used to repeatedly, remotely measure hundreds or thousands of square kilometers with little/no analyst interaction or interpretation, but also serves as a paradigm for future efforts in building more advanced airborne laser systems such as real-time laser scanners.
Topographic Laser Ranging And Scanning
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Author : Jie Shan
language : en
Publisher: CRC Press
Release Date : 2017-12-19
Topographic Laser Ranging And Scanning written by Jie Shan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-19 with Technology & Engineering categories.
A systematic, in-depth introduction to theories and principles of Light Detection and Ranging (LiDAR) technology is long overdue, as it is the most important geospatial data acquisition technology to be introduced in recent years. An advanced discussion, this text fills the void. Professionals in fields ranging from geology, geography and geoinformatics to physics, transportation, and law enforcement will benefit from this comprehensive discussion of topographic LiDAR principles, systems, data acquisition, and data processing techniques. The book covers ranging and scanning fundamentals, and broad, contemporary analysis of airborne LiDAR systems, as well as those situated on land and in space. The authors present data collection at the signal level in terms of waveforms and their properties; at the system level with regard to calibration and georeferencing; and at the data level to discuss error budget, quality control, and data organization. They devote the bulk of the book to LiDAR data processing and information extraction and elaborate on recent developments in building extraction and reconstruction, highlighting quality and performance evaluations. There is also extensive discussion of the state-of-the-art technological developments used in: filtering algorithms for digital terrain model generation; strip adjustment of data for registration; co-registration of LiDAR data with imagery; forestry inventory; and surveying. Readers get insight into why LiDAR is the effective tool of choice to collect massive volumes of explicit 3-D data with unprecedented accuracy and simplicity. Compiled by leading experts talking about much of their own pioneering work, this book will give researchers, professionals, and senior students novel ideas to supplement their own experience and practices.
The Use Of Lidar In Multi Scale Forestry Applications
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Author :
language : en
Publisher:
Release Date : 2017
The Use Of Lidar In Multi Scale Forestry Applications written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Forest ecosystems are a significant faction of the Earth's landscape, and accurate estimates of forest structures are important for understanding and predicting how forest ecosystems respond to climate change and human activities. Light detection and ranging (LiDAR) technology, an active remote sensing technology, can penetrate the forest canopy and greatly improve the efficiency and accuracy of mapping forest structures, compared to traditional passive optical remote sensing and radar technologies. However, currently, LiDAR has two major weaknesses, the lack of spectral information and the limited spatial coverage. These weaknesses have limited its accuracy in certain forestry applications (e.g., vegetation mapping) and its application in large-scale forest structure mapping. The aim of research described in this dissertation is to develop data fusion algorithms to address these limitations. In this dissertation, the effectiveness of LiDAR in estimating forest structures and therefore monitoring forest dynamics is first compared with aerial imagery by detecting forest fuel treatment activities at the local scale. Then, a vegetation mapping algorithm is developed based on the fusion of LiDAR data and aerial imagery. This algorithm can automatically determine the optimized number of vegetation units in a forest and take both the vegetation species and vegetation structure characteristics into account in classifying the vegetation types. To extend the use of LiDAR in mapping forest structures in areas without LiDAR coverage, a data fusion algorithm is proposed to map fine-resolution tree height from airborne LiDAR, spaceborne LiDAR, optical imagery and radar data in regional scale. Finally, this dissertation further investigates the methodology to integrate spaceborne LiDAR, optical imagery, radar data and climate surfaces for the purpose of mapping national- to global-scale forest aboveground biomass. The proposed data fusion algorithms and the generated regional to global forest structure parameters will have important applications in ecological and hydrologic studies and forest management.
On The Use Of Rapid Scan Low Point Density Terrestrial Laser Scanning Tls For Structural Assessment Of Complex Forest Environments
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Author : Ali Rouzbeh Kargar
language : en
Publisher:
Release Date : 2020
On The Use Of Rapid Scan Low Point Density Terrestrial Laser Scanning Tls For Structural Assessment Of Complex Forest Environments written by Ali Rouzbeh Kargar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Forests and forestry categories.
"Forests fulfill an important role in natural ecosystems, e.g., they provide food, fiber, habitat, and biodiversity, all of which contribute to stable ecosystems. Assessing and modeling the structure and characteristics in forests can lead to a better understanding and management of these resources. Traditional methods for collecting forest traits, known as “forest inventory”, is achieved using rough proxies, such as stem diameter, tree height, and foliar coverage; such parameters are limited in their ability to capture fine-scale structural variation in forest environments. It is in this context that terrestrial laser scanning (TLS) has come to the fore as a tool for addressing the limitations of traditional forest structure evaluation methods. However, there is a need for improving TLS data processing methods. In this work, we developed algorithms to assess the structure of complex forest environments – defined by their stem density, intricate root and stem structures, uneven-aged nature, and variable understory - using data collected by a low-cost, portable TLS system, the Compact Biomass Lidar (CBL). The objectives of this work are listed as follow: 1. Assess the utility of terrestrial lidar scanning (TLS) to accurately map elevation changes (sediment accretion rates) in mangrove forest; 2. Evaluate forest structural attributes, e.g., stems and roots, in complex forest environments toward biophysical characterization of such forests; and 3. Assess canopy-level structural traits (leaf area index; leaf area density) in complex forest environments to estimate biomass in rapidly changing environments. The low-cost system used in this research provides lower-resolution data, in terms of scan angular resolution and resulting point density, when compared to higher-cost commercial systems. As a result, the algorithms developed for evaluating the data collected by such systems should be robust to issues caused by low-resolution 3D point cloud data. The data used in various parts of this work were collected from three mangrove forests on the western Pacific island of Pohnpei in the Federated States of Micronesia, as well as tropical forests in Hawai’i, USA. Mangrove forests underscore the economy of this region, where more than half of the annual household income is derived from these forests. However, these mangrove forests are endangered by sea level rise, which necessitates an evaluation of the resilience of mangrove forests to climate change in order to better protect and manage these ecosystems. This includes the preservation of positive sediment accretion rates, and stimulating the process of root growth, sedimentation, and peat development, all of which are influenced by the forest floor elevation, relative to sea level. Currently, accretion rates are measured using surface elevation tables (SETs), which are posts permanently placed in mangrove sediments. The forest floor is measured annually with respect to the height of the SETs to evaluate changes in elevation (Cahoon et al. 2002). In this work, we evaluated the ability of the CBL system for measuring such elevation changes, to address objective #1. Digital Elevation Models (DEMs) were produced for plots, based on the point cloud resulted from co-registering eight scans, spaced 45 degree, per plot. DEMs are refined and produced using Cloth Simulation Filtering (CSF) and kriging interpolation. CSF was used because it minimizes the user input parameters, and kriging was chosen for this study due its consideration of the overall spatial arrangement of the points using semivariogram analysis, which results in a more robust model. The average consistency of the TLS-derived elevation change was 72%, with and RMSE value of 1.36 mm. However, what truly makes the TLS method more tenable, is the lower standard error (SE) values when compared to manual methods (10-70x lower). In order to achieve our second objective, we assessed structural characteristics of the above-mentioned mangrove forest and also for tropical forests in Hawaii, collected with the same CBL scanner. The same eight scans per plot (20 plots) were co-registered using pairwise registration and the Iterative Closest Point (ICP). We then removed the higher canopy using a normal change rate assessment algorithm. We used a combination of geometric classification techniques, based on the angular orientation of the planes fitted to points (facets), and machine learning 3D segmentation algorithms to detect tree stems and above-ground roots. Mangrove forests are complex forest environments, containing above-ground root mass, which can create confusion for both ground detection and structural assessment algorithms. As a result, we needed to train a supporting classifier on the roots to detect which root lidar returns were classified as stems. The accuracy and precision values for this classifier were assessed via manual investigation of the classification results in all 20 plots. The accuracy and precision for stem classification were found to be 82% and 77%, respectively. The same values for root detection were 76% and 68%, respectively. We simulated the stems using alpha shapes in order to assess their volume in the final step. The consistency of the volume evaluation was found to be 85%. This was obtained by comparing the mean stem volume (m3/ha) from field data and the TLS data in each plot. The reported accuracy is the average value for all 20 plots. Additionally, we compared the diameter-at-breast-height (DBH), recorded in the field, with the TLS-derived DBH to obtain a direct measure of the precision of our stem models. DBH evaluation resulted in an accuracy of 74% and RMSE equaled 7.52 cm. This approach can be used for automatic stem detection and structural assessment in a complex forest environment, and could contribute to biomass assessment in these rapidly changing environments. These stem and root structural assessment efforts were complemented by efforts to estimate canopy-level structural attributes of the tropical Hawai’i forest environment; we specifically estimated the leaf area index (LAI), by implementing a density-based approach. 242 scans were collected using the portable low-cost TLS (CBL), in a Hawaii Volcano National Park (HAVO) flux tower site. LAI was measured for all the plots in the site, using an AccuPAR LP-80 Instrument. The first step in this work involved detection of the higher canopy, using normal change rate assessment. After segmenting the higher canopy from the lidar point clouds, we needed to measure Leaf Area Density (LAD), using a voxel-based approach. We divided the canopy point cloud into five layers in the Z direction, after which each of these five layers were divided into voxels in the X direction. The sizes of these voxels were constrained based on interquartile analysis and the number of points in each voxel. We hypothesized that the power returned to the lidar system from woody materials, like branches, exceeds that from leaves, due to the liquid water absorption of the leaves and higher reflectivity for woody material at the 905 nm lidar wavelength. We evaluated leafy and woody materials using images from projected point clouds and determined the density of these regions to support our hypothesis. The density of points in a 3D grid size of 0.1 m, which was determined by investigating the size of the branches in the lower portion of the higher canopy, was calculated in each of the voxels. Note that “density” in this work is defined as the total number of points per grid cell, divided by the volume of that cell. Subsequently, we fitted a kernel density estimator to these values. The threshold was set based on half of the area under the curve in each of the distributions. The grid cells with a density below the threshold were labeled as leaves, while those cells with a density above the threshold were set as non-leaves. We then modeled the LAI using the point densities derived from TLS point clouds, achieving a R2 value of 0.88. We also estimated the LAI directly from lidar data by using the point densities and calculating leaf area density (LAD), which is defined as the total one-sided leaf area per unit volume. LAI can be obtained as the sum of the LAD values in all the voxels. The accuracy of LAI estimation was found to be 90%. Since the LAI values cannot be considered spatially independent throughout all the plots in this site, we performed a semivariogram analysis on the field-measured LAI data. This analysis showed that the LAI values can be assumed to be independent in plots that are at least 30 m apart. As a result, we divided the data into six subsets, where each of the plots were 30 meter spaced for each subset. LAI model R2 values for these subsets ranged between 0.84 - 0.96. The results bode well for using this method for automatic estimation of LAI values in complex forest environments, using a low-cost, low point density, rapid-scan TLS."--Abstract.
Wildland Fire Danger Estimation And Mapping
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Author : Emilio Chuvieco
language : en
Publisher: World Scientific
Release Date : 2003
Wildland Fire Danger Estimation And Mapping written by Emilio Chuvieco and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Nature categories.
The book presents a wide range of techniques for extracting information from satellite remote sensing images in forest fire danger assessment. It covers the main concepts involved in fire danger rating, and analyses the inputs derived from remotely sensed data for mapping fire danger at both the local and global scale. The questions addressed concern the estimation of fuel moisture content, the description of fuel structural properties, the estimation of meteorological danger indices, the analysis of human factors associated with fire ignition, and the integration of different risk factors in a geographic information system for fire danger management.
3d Feature Extraction And Geometric Mappings For Improved Parameter Estimation In Forested Terrain Using Airborne Lidar Data
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Author : Heezin Lee
language : en
Publisher:
Release Date : 2008
3d Feature Extraction And Geometric Mappings For Improved Parameter Estimation In Forested Terrain Using Airborne Lidar Data written by Heezin Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
ABSTRACT: Scanning laser ranging technology is well suited for measuring point-to-point distances because of its ability to generate small beam divergences. As a result, many of the laser pulses emitted from airborne light detection and ranging (LiDAR) systems are able to reach the ground underneath tree canopies through small (10 cm scale) gaps in the foliage. Using high pulse rate lasers and fast optical scanners, airborne LiDAR systems can provide both high spatial resolution and canopy penetration, and these data have become more widely available in recent years for use in environmental and forestry applications. The small-footprint, discrete-return Airborne Laser Swath Mapping (ALSM) system at the University of Florida (UF) is used to directly measure ground surface elevations and the three-dimensional (3D) distribution of the vegetative material above the soil surface. Field of view geometric mappings are explored to find optical gaps inside forests. First, a method is developed to detect walking trails in natural forests that are obscured from above by the canopy. Several features are derived from the ALSM data and used to constrain the search space and infer the location of trails. Second, a robust and simple procedure for estimating intercepted photosynthetically active radiation (IPAR), which is an important measure of forest timber productivity and of daylight visibility in forested terrain, is presented. Simple scope functions that isolate the relevant LiDAR reflections between observer locations and the sun are defined and shown to give good agreement between the LiDAR-derived estimates and values of IPAR measured in situ. A conical scope function with an angular divergence from the centerline of "7° provided the best agreement with the in situ measurements.
Forestry Applications Of Airborne Laser Scanning
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Author : Matti Maltamo
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-04-08
Forestry Applications Of Airborne Laser Scanning written by Matti Maltamo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-08 with Technology & Engineering categories.
Airborne laser scanning (ALS) has emerged as one of the most promising remote sensing technologies to provide data for research and operational applications in a wide range of disciplines related to management of forest ecosystems. This book provides a comprehensive, state-of-the-art review of the research and application of ALS in a broad range of forest-related disciplines, especially forest inventory and forest ecology. However, this book is more than just a collection of individual contributions – it consists of a well-composed blend of chapters dealing with fundamental methodological issues and contributions reviewing and illustrating the use of ALS within various domains of application. The reviews provide a comprehensive and unique overview of recent research and applications that researchers, students and practitioners in forest remote sensing and forest ecosystem assessment should consider as a useful reference text.
Forest Structure From Terrestrial Laser Scanning
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Author : David Kelbe
language : en
Publisher:
Release Date : 2015
Forest Structure From Terrestrial Laser Scanning written by David Kelbe and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Forests and forestry categories.
"Forests are an important part of the natural ecosystem, providing resources such as timber and fuel, performing services such as energy exchange and carbon storage, and presenting risks, such as fire damage and invasive species impacts. Improved characterization of forest structural attributes is desirable, as it could improve our understanding and management of these natural resources. However, the traditional, systematic collection of forest information -- dubbed 'forest inventory' -- is time-consuming, expensive, and coarse when compared to novel 3-D measurement technologies. Remote sensing estimates, on the other hand, provide synoptic coverage, but often fail to capture the fine-scale structural variation of the forest environment. Terrestrial laser scanning (TLS) has demonstrated a potential to address these limitations, but its operational use has remained limited due to unsatisfactory performance characteristics vs. budgetary constraints of many end-users. To address this gap, my dissertation advanced affordable mobile laser scanning capabilities for operational forest structure assessment. We developed geometric reconstruction of forest structure from rapid-scan, low-resolution point cloud data, providing for automatic extraction of standard forest inventory metrics. To augment these results over larger areas, we designed a view-invariant feature descriptor to enable marker-free registration of TLS data pairs, without knowledge of the initial sensor pose. Finally, a graph-theory framework was integrated to perform multi-view registration between a network of disconnected scans, which provided improved assessment of forest inventory variables. This work addresses a major limitation related to the inability of TLS to assess forest structure at an operational scale, and may facilitate improved understanding of the phenomenology of airborne sensing systems, by providing fine-scale reference data with which to interpret the active or passive electromagnetic radiation interactions with forest structure. Outputs are being utilized to provide antecedent science data for NASA's HyspIRI mission and to support the National Ecological Observatory Network's (NEON) long-term environmental monitoring initiatives."--Abstract.
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.
The Wildlife Techniques Manual
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Author : Nova J. Silvy
language : en
Publisher: JHU Press
Release Date : 2012-03
The Wildlife Techniques Manual written by Nova J. Silvy and has been published by JHU Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03 with Science categories.
A standard text in a variety of courses, the Techniques Manual, as it is commonly called, covers every aspect of modern wildlife management and provides practical information for applying the hundreds of methods described in its pages. To effectively incorporate the explosion of new information in the wildlife profession, this latest edition is logically organized into a two-volume set: Volume 1 is devoted to research techniques and Volume 2 focuses on management methodologies.