scholarly journals Drone data for decision making in regeneration forests: from raw data to actionable insights

2020 ◽  
Author(s):  
Stefano Puliti ◽  
Aksel Granhus
Keyword(s):  
Data Analytics ◽  
Logistic Model ◽  
Laser Scanning ◽  
Binary Classification ◽  
Multiple Linear Regression Model ◽  
Cost Models ◽  
Airborne Laser ◽  
Aerial Vehicle ◽  
The Cost

Unmanned aerial vehicle (UAV) photogrammetric data and data analytics were used to model stand-level immediate tending need and cost in regeneration forests. Field reference data were used to train and validate a logistic model for the binary classification of immediate tending need and a multiple linear regression model to predict the cost to perform the tending operation. The performance of the models derived from UAV data was compared to models utilizing the following alternative data sources: airborne laser scanning data (ALS), prior inventory information (Prior), and the combination of UAV and Prior and ALS and Prior. The use of UAV and Prior data outperformed the remaining alternatives in terms of classification of tending needs, while UAV alone produced the most accurate cost models. Our results are encouraging for further use of UAVs in the operational management of regeneration forests and show that UAV data and data analytics are useful for deriving actionable insights.

scholarly journals Segmentation and Multi-Scale Convolutional Neural Network-Based Classification of Airborne Laser Scanner Data

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3347 ◽  
Author(s):  
Zhishuang Yang ◽  
Bo Tan ◽  
Huikun Pei ◽  
Wanshou Jiang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Region Growing ◽  
Point Clouds ◽  
Classification Method ◽  
Multi Scale ◽  
Airborne Laser

The classification of point clouds is a basic task in airborne laser scanning (ALS) point cloud processing. It is quite a challenge when facing complex observed scenes and irregular point distributions. In order to reduce the computational burden of the point-based classification method and improve the classification accuracy, we present a segmentation and multi-scale convolutional neural network-based classification method. Firstly, a three-step region-growing segmentation method was proposed to reduce both under-segmentation and over-segmentation. Then, a feature image generation method was used to transform the 3D neighborhood features of a point into a 2D image. Finally, feature images were treated as the input of a multi-scale convolutional neural network for training and testing tasks. In order to obtain performance comparisons with existing approaches, we evaluated our framework using the International Society for Photogrammetry and Remote Sensing Working Groups II/4 (ISPRS WG II/4) 3D labeling benchmark tests. The experiment result, which achieved 84.9% overall accuracy and 69.2% of average F1 scores, has a satisfactory performance over all participating approaches analyzed.

scholarly journals Requirements for a global lidar system: spaceborne lidar with wall-to-wall coverage

2021 ◽  
Vol 8 (12) ◽  
Author(s):  
Steven Hancock ◽  
Ciara McGrath ◽  
Christopher Lowe ◽  
Ian Davenport ◽  
Iain Woodhouse
Keyword(s):  
Laser Scanning ◽  
Unit Area ◽  
Time Frame ◽  
Lidar System ◽  
Continuous Map ◽  
Airborne Laser ◽  
Readiness Level ◽  
Technological Developments ◽  
Global Coverage ◽  
The Cost

Lidar is the optimum technology for measuring bare-Earth elevation beneath, and the structure of, vegetation. Consequently, airborne laser scanning (ALS) is widely employed for use in a range of applications. However, ALS is not available globally nor frequently updated due to its high cost per unit area. Spaceborne lidar can map globally but energy requirements limit existing spaceborne lidars to sparse sampling missions, unsuitable for many common ALS applications. This paper derives the equations to calculate the coverage a lidar satellite could achieve for a given set of characteristics (released open-source), then uses a cloud map to determine the number of satellites needed to achieve continuous, global coverage within a certain time-frame. Using the characteristics of existing in-orbit technology, a single lidar satellite could have a continuous swath width of 300 m when producing a 30 m resolution map. Consequently, 12 satellites would be needed to produce a continuous map every 5 years, increasing to 418 satellites for 5 m resolution. Building 12 of the currently in-orbit lidar systems is likely to be prohibitively expensive and so the potential of technological developments to lower the cost of a global lidar system (GLS) are discussed. Once these technologies achieve a sufficient readiness level, a GLS could be cost-effectively realized.

scholarly journals Classification of Needle Loss of Individual Scots Pine Trees by Means of Airborne Laser Scanning

Forests ◽  
2013 ◽  
Vol 4 (2) ◽  
pp. 386-403 ◽  
Author(s):  
Tuula Kantola ◽  
Mikko Vastaranta ◽  
Päivi Lyytikäinen-Saarenmaa ◽  
Markus Holopainen ◽  
Ville Kankare ◽  
...  
Keyword(s):  
Scots Pine ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser ◽  
Pine Trees ◽  
Needle Loss

scholarly journals Ontology-Based Classification of Building Types Detected from Airborne Laser Scanning Data

2014 ◽  
Vol 6 (2) ◽  
pp. 1347-1366 ◽  
Author(s):  
Mariana Belgiu ◽  
Ivan Tomljenovic ◽  
Thomas Lampoltshammer ◽  
Thomas Blaschke ◽  
Bernhard Höfle
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser

An approach to classification of airborne laser scanning point cloud data in an urban environment

2011 ◽  
Vol 32 (24) ◽  
pp. 9151-9169 ◽  
Author(s):  
Cici Alexander ◽  
Kevin Tansey ◽  
Jörg Kaduk ◽  
David Holland ◽  
Nicholas J. Tate
Keyword(s):  
Urban Environment ◽  
Point Cloud ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Airborne Laser

scholarly journals Detection and Classification of Changes in Buildings from Airborne Laser Scanning Data

2015 ◽  
Vol 7 (12) ◽  
pp. 17051-17076 ◽  
Author(s):  
Sudan Xu ◽  
George Vosselman ◽  
Sander Oude Elberink
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser
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