Mapping Individual Trees With Airborne Laser Scanning Data In An European Lowland Forest Using A Self Calibration Algorithm

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Mapping Individual Trees with Airborne Laser Scanning Data in an European Lowland Forest Using a Self-calibration Algorithm

Author : Krzysztof Sterenczak
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (124 download)

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Book Synopsis Mapping Individual Trees with Airborne Laser Scanning Data in an European Lowland Forest Using a Self-calibration Algorithm by : Krzysztof Sterenczak

Download or read book Mapping Individual Trees with Airborne Laser Scanning Data in an European Lowland Forest Using a Self-calibration Algorithm written by Krzysztof Sterenczak and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Traditional field-based forest inventories tend to be expensive, time-consuming, and cover only a limited area of a forested region. Remote sensing (RS), especially airborne laser scanning (ALS) has opened new possibilities for operational forest inventories, particularly at the single-tree level, and in the prediction of single-tree characteristics. Throughout the world, forests have varying characteristics that necessitate the development of modern, effective, and versatile tools for ALS data processing. To address this need, we aimed to develop a tool for individual tree detection (ITD) utilising a self-calibrating algorithm procedure and to verify its accuracy using the complicated forest structure of near natural forests in the temperate zone. This study was carried out in the Polish part of the Białowieża Forest (BF). The airborne laser scanner (ALS) and color-infrared (CIR) datasets were acquired for more than 60 000 ha. Field-based measurements were performed to provide reference data at the single tree level. We introduced a novel ITD method that is self-calibrated and uses a hierarchical analyses of the canopy height model. There were more than 20 000 000 of trees in first layer in BF above 7 m height. Trees visible from above were divided into coniferous, deciduous and mixed trees that were then matched with an accuracy of 85 %, 85 % and 75 %, respectively. Compared to existing methods, the proposed method is more flexible and achieves better results, especially for deciduous species. Before application of the presented method to other regions, the calibration based on the developed optimisation procedure is needed

Forestry Applications of Airborne Laser Scanning

Author : Matti Maltamo
Publisher : Springer Science & Business Media
ISBN 13 : 9401786631
Total Pages : 460 pages
Book Rating : 4.4/5 (17 download)

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Book Synopsis Forestry Applications of Airborne Laser Scanning by : Matti Maltamo

Download or read book Forestry Applications of Airborne Laser Scanning written by Matti Maltamo and published by Springer Science & Business Media. This book was released on 2014-04-08 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Classification of Full-waveform Airborne Laser Scanning Data and Extraction of Attributes of Vegetation for Topographic Mapping

Author : Cicimol Alexander
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (86 download)

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Book Synopsis Classification of Full-waveform Airborne Laser Scanning Data and Extraction of Attributes of Vegetation for Topographic Mapping by : Cicimol Alexander

Download or read book Classification of Full-waveform Airborne Laser Scanning Data and Extraction of Attributes of Vegetation for Topographic Mapping written by Cicimol Alexander and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: There is an increasing demand for urban vegetation mapping, and airborne laser scanning (ALS) has the unique ability to provide geo-referenced three-dimensional data useful for mapping of surface features. This thesis examines the ability of full-waveform and discrete return ALS point data to distinguish urban surface features, and represent the three-dimensional attributes of vegetation at different scales in a vector-based GIS environment. Two full-waveform datasets, at a wavelength of 1550 nm, and a discrete return dataset, at 1064 nm, are used. Points extracted from the first full-waveform dataset are classified with k-means clustering and decision tree into vegetation, buildings and roads, based on the attributes of individual points and the relationships between neighbouring points. A decision tree is shown to perform significantly better (74.62%) than k-means clustering (51.59%) based on the overall accuracies. Grass and paved areas could be distinguished better using intensity from discrete return data than amplitude from full-waveform data, both values proportional to the strength of the return signal. The differences in the signatures of surfaces could be related to the wavelengths of the lasers, and need to be explored further. Calibration of intensity is currently possible only with full-waveform data. When the decision tree is applied on the second full-waveform dataset, the backscatter coefficient proves to be a more useful attribute than amplitude, pointing to the need for calibration if a classification method using intensity is to be applied on datasets with different scanning geometries. A vector-based approach for delineating tree crowns is developed and implemented at three scales. The first scale provides a good estimation of the tree crown area and structure, suitable for estimating biomass and canopy gaps. The third scale identifies the number of trees and their locations and can be used for modelling individual trees.

A Voxel-based Method for Individual Tree Detection Using Airborne Lidar in Eastern U.S. Hardwood Forests

Author : Jeff Hershey
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (127 download)

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Book Synopsis A Voxel-based Method for Individual Tree Detection Using Airborne Lidar in Eastern U.S. Hardwood Forests by : Jeff Hershey

Download or read book A Voxel-based Method for Individual Tree Detection Using Airborne Lidar in Eastern U.S. Hardwood Forests written by Jeff Hershey and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: For more than a century, forest inventories have been used to support forest management and timber valuation activities. Today's inventories still rely primarily on manual measurements combined with sampling and modeling techniques. In recent years, new opportunities in carbon sequestration and an increasingly sophisticated timber market have prompted a need for more scalable and efficient inventory methods. To meet this demand, the industry has turned to remote sensing--predominantly light detection and ranging (LiDAR), which utilizes lasers to scan and measure features in 3D space. While much progress has been made, data resolution and cost challenges for both airborne and terrestrial LiDAR still exist. Airborne Laser Scanning (ALS) is more efficient for measuring large forest areas but faces challenges with respect to resolution and occlusion, leading to omission of understory trees. Terrestrial Laser Scanning (TLS) performs better in those respects but relies on expensive and typically unwieldy hardware. Area-based LiDAR approaches have been successful for large-scale applications but are not ideal for smaller parcels. As such, a need persists for a LiDAR-based solution that enables efficient generation of large-area forest inventory data yet is scalable to smaller forest plots and a range of forest types. The objective of this study was the development of a scalable individual tree detection method that leveraged airborne LiDAR data and performed well in mixed-species hardwood forests found in the northeastern United States. Existing research in individual tree detection has focused on methods that work well in conifer-dominated forests and homogenous settings such as plantations. These approaches, many of them based on top-down canopy height models, perform less favorably in deciduous stands due to the canopy complexity and crown characteristics inherent to these forest types. The voxel-based method proposed here uses detailed ground-measured tree survey data and leaf-off LiDAR collected in 2019-2020 over the Shavers Creek Watershed in Pennsylvania, United States. The method detected 68% of all reference trees greater than 10cm diameter at breast height (DBH) and 87% of sawtimber-sized trees greater than 28cm DBH, and it performed consistently across 48 subplots in the three-hectare test area. A new tree matching method leveraging linear integer programming was used for training and evaluation of the method. This tool enabled true one-to-one matching of predicted and reference trees and the validation of tree detections. Mean positional accuracy for predicted trees was within one meter of ground-measured reference trees. The results indicate the method has potential to be operationalized for both traditional forest management activities and in meeting the demand for more frequent and scalable inventories spurred by a growing forest carbon sequestration industry.

Individual Tree Measurements by Means of Digital Aerial Photogrammetry

Author : Ilkka Korpela
Publisher :
ISBN 13 :
Total Pages : 100 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Individual Tree Measurements by Means of Digital Aerial Photogrammetry by : Ilkka Korpela

Download or read book Individual Tree Measurements by Means of Digital Aerial Photogrammetry written by Ilkka Korpela and published by . This book was released on 2004 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:

New Methods, Algorithms, and Software for Rapid Mapping of Tree Positions in Coordinate Forest Plots

Author : A. D. Wilson
Publisher :
ISBN 13 :
Total Pages : 40 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis New Methods, Algorithms, and Software for Rapid Mapping of Tree Positions in Coordinate Forest Plots by : A. D. Wilson

Download or read book New Methods, Algorithms, and Software for Rapid Mapping of Tree Positions in Coordinate Forest Plots written by A. D. Wilson and published by . This book was released on 2000 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Improving LIDAR-based Tree Species Mapping in Central European Mixed Forests Using Multitemporal Digital Aerial Colour-infrared Photographs

Download Improving LIDAR-based Tree Species Mapping in Central European Mixed Forests Using Multitemporal Digital Aerial Colour-infrared Photographs PDF Online Free

Author : Yifang Shi
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (124 download)

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Book Synopsis Improving LIDAR-based Tree Species Mapping in Central European Mixed Forests Using Multitemporal Digital Aerial Colour-infrared Photographs by : Yifang Shi

Download or read book Improving LIDAR-based Tree Species Mapping in Central European Mixed Forests Using Multitemporal Digital Aerial Colour-infrared Photographs written by Yifang Shi and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Digital colour-infrared (CIR) aerial photographs, which have been collected routinely in many parts of the world, are an invaluable data source for the monitoring and assessment of forest resources. Yet, the potential of these data for automated individual tree species mapping remains largely unexplored. One way to maximize the usefulness of digital CIR aerial photographs for individual tree species mapping is to integrate them with modern and complementary remote sensing technologies such as the light detection and ranging (LiDAR) system and 3D segmentation algorithms. In this study, we examined whether multi-temporal digital CIR orthophotos could be used to further increase the accuracy of airborne LiDAR-based individual tree species mapping for a temperate mixed forest in eastern Germany. Our results showed that the texture features captured by multi-temporal digital CIR orthophotos under different view-illumination conditions were species-specific. As a consequence, combining these texture features with LiDAR metrics significantly improved tree species mapping accuracy (overall accuracy: 77.4%, kappa: 0.68) compared to using LiDAR data alone (overall accuracy: 69.3%, kappa: 0.58). Among various texture features, the average gray level in the near-infrared band was found to contribute most to the classification. Our results suggest that the synergic use of multi-temporal digital aerial photographs and airborne LiDAR data has the potential to accurately classify individual tree species in Central European mixed forests

Mapping Forest Landscape Patterns

Author : Tarmo K. Remmel
Publisher : Springer
ISBN 13 : 1493973312
Total Pages : 333 pages
Book Rating : 4.4/5 (939 download)

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Book Synopsis Mapping Forest Landscape Patterns by : Tarmo K. Remmel

Download or read book Mapping Forest Landscape Patterns written by Tarmo K. Remmel and published by Springer. This book was released on 2017-09-07 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the concepts, premises, advancements, and challenges in quantifying natural forest landscape patterns through mapping techniques. After several decades of development and use, these tools can now be examined for their foundations, intentions, scope, advancements, and limitations. When applied to natural forest landscapes, mapping techniques must address concepts such as stochasticity, heterogeneity, scale dependence, non-Euclidean geometry, continuity, non-linearity, and parsimony, as well as be explicit about the intended degree of abstraction and assumptions. These studies focus on quantifying natural (i.e., non-human engineered) forest landscape patterns, because those patterns are not planned, are relatively complex, and pose the greatest challenges in cartography, and landscape representation for further interpretation and analysis.

Multi-temporal Terrestrial Lidar for Estimating Individual Tree Dimensions and Biomass Change

Author : Shruthi Srinivasan
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (881 download)

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Book Synopsis Multi-temporal Terrestrial Lidar for Estimating Individual Tree Dimensions and Biomass Change by : Shruthi Srinivasan

Download or read book Multi-temporal Terrestrial Lidar for Estimating Individual Tree Dimensions and Biomass Change written by Shruthi Srinivasan and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate measures of forest structural parameters are essential to forest inventory and growth models, managing wildfires, and modeling of carbon cycle. Terrestrial laser scanning (TLS) provides accurate understory information rapidly through non-destructive methods. This study developed algorithms to extract individual tree height, diameter at breast height (DBH), and crown width in plots at Ecosystem Science and Management (ESSM) research area and Huntsville, Texas. Further, the influence of scan settings and processing choices on the accuracy of deriving tree measurements was also investigated. The study also developed models to estimate aboveground biomass (AGB) and investigate different conceptual approaches to study tree level growth in forest structural parameters and AGB using multi-temporal TLS datasets. DBH was retrieved by cylinder fitting at different height bins. Individual trees were extracted from the TLS point cloud to determine tree heights and crown widths. The R-squared value ranged from 0.91 to 0.97 when field measured DBH was validated against TLS derived DBH using different methods. An accuracy of 92% was obtained for predicting tree heights. The R-squared value was 0.84 and RMSE was 1.08 m when TLS derived crown widths were validated using field measured crown widths. Examples of underestimations of field measured forest structural parameters due to tree shadowing have also been discussed in this study. Correction factors should be applied or multiple high resolution scans should be conducted to reduce the errors in estimation of forest structural parameters. TLS geometric and statistical parameters were derived for individual trees and used as explanatory variables to estimate AGB. An extensive literature review reveals that this is the first study to model the change in AGB using different innovative and conceptual approaches with multi-temporal TLS data. Tree level AGB growth was studied over a period of three years using three different approaches. Results showed that TLS derived geometric parameters were better correlated to field measured AGB. Promising results for AGB change were obtained using the direct modeling approach; hence forest growth could be studied independent of any field measurements when biomass models are available. However, the models could be improved by incorporating more trees with a wide range of DBH and tree heights. The results from this study will benefit foresters, planners, and other remote sensing studies from airborne and spaceborne platforms, for map upscaling, data fusion, or calibration purposes. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/151740

Single Tree Detection from Airborne Laser Scanning Data

Author : Junjie Zhang
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Single Tree Detection from Airborne Laser Scanning Data by : Junjie Zhang

Download or read book Single Tree Detection from Airborne Laser Scanning Data written by Junjie Zhang and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Estimating Forest Structural Characteristics with Airborne Lidar Scanning and a Near-real Time Profiling Laser Systems

Author : Kaiguang Zhao
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (69 download)

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Book Synopsis Estimating Forest Structural Characteristics with Airborne Lidar Scanning and a Near-real Time Profiling Laser Systems by : Kaiguang Zhao

Download or read book Estimating Forest Structural Characteristics with Airborne Lidar Scanning and a Near-real Time Profiling Laser Systems written by Kaiguang Zhao and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Terrestrial, UAV-borne, and Airborne Laser Scanning Point Clouds of Central European Forest Plots, Germany, with Extracted Individual Trees and Manual Forest Inventory Measurements

Download Terrestrial, UAV-borne, and Airborne Laser Scanning Point Clouds of Central European Forest Plots, Germany, with Extracted Individual Trees and Manual Forest Inventory Measurements PDF Online Free

Author : Hannah Weiser
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (141 download)

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Book Synopsis Terrestrial, UAV-borne, and Airborne Laser Scanning Point Clouds of Central European Forest Plots, Germany, with Extracted Individual Trees and Manual Forest Inventory Measurements by : Hannah Weiser

Download or read book Terrestrial, UAV-borne, and Airborne Laser Scanning Point Clouds of Central European Forest Plots, Germany, with Extracted Individual Trees and Manual Forest Inventory Measurements written by Hannah Weiser and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Advanced Methods for 3-D Forest Characterization and Mapping from Lidar Remote Sensing Data

Author : Carlos Alberto Silva
Publisher :
ISBN 13 : 9780438392953
Total Pages : 296 pages
Book Rating : 4.3/5 (929 download)

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Book Synopsis Advanced Methods for 3-D Forest Characterization and Mapping from Lidar Remote Sensing Data by : Carlos Alberto Silva

Download or read book Advanced Methods for 3-D Forest Characterization and Mapping from Lidar Remote Sensing Data written by Carlos Alberto Silva and published by . This book was released on 2018 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate and spatially explicit measurements of forest attributes are critical for sustainable forest management and for ecological and environmental protection. Airborne Light Detection and Ranging (lidar) systems have become the dominant remote sensing technique for forest inventory, mainly because this technology can quickly provide highly accurate and spatially detailed information about forest attributes across entire landscapes. This dissertation is focused on developing and assessing novel and advanced methods for three dimensional (3-D) forest characterization. Specifically, I map canopy structural attributes of individual trees, as well as forests at the plot and landscape levels in both natural and industrial plantation forests using lidar remote sensing data. Chapter 1 develops a novel framework to automatically detect individual trees and evaluates the efficacy of k-nearest neighbor (k-NN) imputation models for estimating tree attributes in longleaf pine (Pinus palustris Mill.) forests. Although basal area estimation accuracy was poor because of the longleaf pine growth habit, individual tree locations, height and volume were estimated with high accuracy, especially in low-canopy-cover conditions. The root mean square distance (RMSD) for tree-level height, basal area, and volume were 2.96%, 58.62%, and 8.19%, respectively. Chapter 2 presents a methodology for predicting stem total and assortment volumes in industrial loblolly pine (Pinus taeda L.) forest plantations using lidar data as inputs to random forest models. When compared to reference forest inventory data, the accuracy of plot-level forest total and assortment volumes was high; the root mean square error (RMSE) of total, commercial and pulp volume estimates were 7.83%, 7.71% and 8.63%, respectively. Chapter 3 evaluates the impacts of airborne lidar pulse density on estimating aboveground biomass (AGB) stocks and changes in a selectively logged tropical forest. Estimates of AGB change at the plot level were only slightly affected by pulse density. However, at the landscape level we observed differences in estimated AGB change of >20 Mg ̇ha−1 when pulse density decreased from 12 to 0.2 pulses ̇m−2. The effects of pulse density were more pronounced in areas of steep slope, but when the DTM from high pulse density in 2014 was used to derive the forest height from both years, the effects on forest height and subsequent AGB stocks and change estimates did not exceed 20 Mg ̇ha−1. Chapter 4 presents a comparison of airborne small-footprint (SF) and large-footprint (LF) lidar retrievals of ground elevation, vegetation height and biomass across a successional tropical forest gradient in central Gabon. The comparison of the two sensors shows that LF lidar waveforms are equivalent to simulated waveforms from SF lidar for retrieving ground elevation (RMSE=0.5 m, bias=0.29 m) and maximum forest height (RMSE=2.99 m; bias=0.24 m). Comparison of gridded LF lidar height with ground plots showed that an unbiased estimate of aboveground biomass at 1-ha can be achieved with a sufficient number of large footprints (> 3). Lastly, Appendix A presents an open source R package for airborne lidar visualization and processing for forestry applications.

Adoption of Airborne LiDAR Data and High Spatial Resolution Satellite Imagery for Characterisation and Classification of Forest Communities

Download Adoption of Airborne LiDAR Data and High Spatial Resolution Satellite Imagery for Characterisation and Classification of Forest Communities PDF Online Free

Author : Zhenyu Zhang
Publisher :
ISBN 13 :
Total Pages : 896 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Adoption of Airborne LiDAR Data and High Spatial Resolution Satellite Imagery for Characterisation and Classification of Forest Communities by : Zhenyu Zhang

Download or read book Adoption of Airborne LiDAR Data and High Spatial Resolution Satellite Imagery for Characterisation and Classification of Forest Communities written by Zhenyu Zhang and published by . This book was released on 2012 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: High resolution spatial data, including airborne LiDAR data and newly available WorldView-2 satellite imagery, offer excellent opportunities to develop new and efficient ways of solving conventional problems in forestry. Those responsible for monitoring forest changes over time relevant to timber harvesting and native forest conservation see the potential for improved documentation from using such data. However, the transfer of new remote sensing technologies from the research domain into operational forestry applications poses challenges. One of the key challenges is the development of a comprehensive procedure which involves deployment of these new remote sensing data to create forest mapping products that are comparable (or superior) in accuracy to conventional photo-interpreted maps. The last decade has witnessed an increase in interest in the application of airborne LiDAR data and high spatial resolution satellite imagery for tree species identification and classification. The research investigations have focused on open forests, and conifer or deciduous forests which are even-aged and of relatively homogenous structures. The suitability of these new remotely sensed data for delineating the structure of complex forest types, particularly for Australian cool temperate rainforest and neighbouring uneven-aged mixed forests in a severely disturbed landscape has hitherto remained untested. This thesis presents ways of processing airborne LiDAR data and high spatial resolution WorldView-2 satellite imagery for characterisation and classification of forest communities in the Strzelecki Ranges, Victoria, Australia. This is a highly disturbed landscape that consists of forestry plantations and large stands of natural forest, including cool temperate rainforest remnants. The k-means clustering algorithm was applied to nonnalised LiDAR points to stratify the vertical forest structure into three layers. Variables characterising the height distribution and density of forest components were derived from LiDAR data within each of these layers. These layer-specific variables were found to be effective in forest classification. Individual trees, including locations and crown sizes, were identified from a LiDAR-derived canopy height model using the TreeVaW algorithm. Augmentation of infonnation extraction from LiDAR data for tree species identification by inclusion of LiDAR intensity data was then tested using statistical analysis techniques. This study demonstrated the contribution of LiDAR-derived intensity variables to the identification of Myrtle Beech (Nothofagus cunninghamii -the dominant species of the Australian cool temperate rainforest in the study area) and adjacent tree species -notably, Silver Wattle (Acacia dealbata) at the individual tree level. Nonparametric classifiers including support vector machines (SVMs) and decision trees were employed to take full advantage of the rich set of infonnation derived from the LiDAR and WorldView-2 imagery data for further improvement in classification accuracy. It is evident that the SVMs have significant advantages over the traditional classification methods in tenns of classification accuracy. Cool temperate rainforest and adjacent forest species were successfully classified from airborne LiDAR data and WorldView-2 satellite imagery using a decision tree approach to object-based analyses in eCognition software. The improvements in results from the methods developed in this study strongly warrant the operational adoption of airborne LiDAR data and high spatial resolution satellite imagery in the management of Australia's forestry resources.

Urban Forest Inventory Using Airborne LiDAR Data and Hyperspectral Imagery

Author : Caiyun Zhang
Publisher :
ISBN 13 :
Total Pages : 286 pages
Book Rating : 4.:/5 (795 download)

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Book Synopsis Urban Forest Inventory Using Airborne LiDAR Data and Hyperspectral Imagery by : Caiyun Zhang

Download or read book Urban Forest Inventory Using Airborne LiDAR Data and Hyperspectral Imagery written by Caiyun Zhang and published by . This book was released on 2010 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this research was to develop new algorithms to automate urban forest inventory at the individual tree level using two emerging remote sensing technologies, LiDAR and hyperspectral sensors. LiDAR data contain 3-Dimensional structure information that can be used to estimate tree height, base height, crown depth, and crown diameter, while hyperspectral data contain rich spectral contents that can be used to discriminate tree species. The synergy of two data sources would allow precision urban forest inventory down to individual trees. Unlike most of the published algorithms that isolate individual trees from a raster surface built from LiDAR data to estimate tree metrics, this study worked directly from the vector LiDAR point cloud data for separating individual trees and estimating tree metrics, in order to generate a better accuracy by preserving the original height values.

The Automatic Recognition of Individual Trees in Aerial Images of Forests Based on a Synthetic Tree Crown Image Model [microform]

Author : Richard Pollock
Publisher : National Library of Canada = Bibliothèque nationale du Canada
ISBN 13 : 9780612148154
Total Pages : 172 pages
Book Rating : 4.1/5 (481 download)

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Book Synopsis The Automatic Recognition of Individual Trees in Aerial Images of Forests Based on a Synthetic Tree Crown Image Model [microform] by : Richard Pollock

Download or read book The Automatic Recognition of Individual Trees in Aerial Images of Forests Based on a Synthetic Tree Crown Image Model [microform] written by Richard Pollock and published by National Library of Canada = Bibliothèque nationale du Canada. This book was released on 1996 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Classification of Tree Species as Well as Standing Dead Trees Using Triple Wavelength Lidar in a Temperate Forest

Author : Nina Amiri
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (115 download)

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Book Synopsis Classification of Tree Species as Well as Standing Dead Trees Using Triple Wavelength Lidar in a Temperate Forest by : Nina Amiri

Download or read book Classification of Tree Species as Well as Standing Dead Trees Using Triple Wavelength Lidar in a Temperate Forest written by Nina Amiri and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Knowledge about forest structures, particularly of deadwood, is fundamental for understanding, protecting, and conserving forest biodiversity. While individual tree-based approaches using single wavelength airborne laserscanning (ALS) can successfully distinguish broadleaf and coniferous trees, they still perform multiple tree species classifications with limited accuracy. Moreover, the mapping of standing dead trees is becoming increasingly important for damage calculation after pest infestation or biodiversity assessment. Recent advances in sensor technology have led to the development of new ALS systems that provide up to three different wavelengths. In this study, we present a novel method which classifies three tree species (Norway spruce, European beech, Silver fir), and dead spruce trees with crowns using full waveform ALS data acquired from three different sensors (wavelengths 532 nm, 1064 nm, 1550 nm). The ALS data were acquired in the Bavarian Forest National Park (Germany) under leaf-on conditions with a maximum point density of 200 points/m 2 . To avoid overfitting of the classifier and to find the most prominent features, we embed a forward feature selection method. We tested our classification procedure using 20 sample plots with 586 measured reference trees. Using single wavelength datasets, the highest accuracy achieved was 74% (wavelength = 1064 nm), followed by 69% (wavelength = 1550 nm) and 65% (wavelength = 532 nm). An improvement of 8-17% over single wavelength datasets was achieved when the multi wavelength data were used. Overall, the contribution of the waveform-based features to the classification accuracy was higher than that of the geometric features by approximately 10%. Our results show that the features derived from a multi wavelength ALS point cloud significantly improve the detailed mapping of tree species and standing dead trees