scholarly journals Stand delineation based on laser scanning data and simulated annealing

2021 ◽  
Author(s):  
Yusen Sun ◽  
Weifang Wang ◽  
Timo Pukkala ◽  
Xingji Jin
Keyword(s):  
Simulated Annealing ◽  
Unmanned Aerial Vehicles ◽  
Laser Scanning ◽  
Optimization Problem ◽  
Combinatorial Optimization Problem ◽  
Canopy Height ◽  
Echo Intensity ◽  
Airborne Laser ◽  
Aerial Vehicles ◽  
Raster Cell

AbstractThe use of airborne laser scanning (LS) is increasing in forestry. Scanning can be conducted from manned aircrafts or unmanned aerial vehicles (UAV). The scanning data are often used to calculate various attributes for small raster cells. These attributes can be used to segment the forest into homogeneous areas, called segments, micro-stands, or, like in this study, stands. Delineation of stands from raster data is equal to finding the most suitable stand number for each raster cell, which is a combinatorial optimization problem. This study tested the performance of the simulated annealing (SA) metaheuristic in the delineation of stands from grids of UAV-LS attributes. The objective function included three criteria: within-stand variation of the LS attributes, stand area, and stand shape. The purpose was to create delineations that consisted of homogeneous stands with a low number of small stands and a regular and roundish stand shape. The results showed that SA is capable of producing stand delineations that meet these criteria. However, the method tended to produce delineations where the stands often consisted of disconnected parts and the stand borders were jagged. These problems were mitigated by using a mode filter on the grid of stand numbers and giving unique numbers for all disconnected parts of a stand. Three LS attributes were used in the delineation. These attributes described the canopy height, the height of the bottom of the canopy and the variation of echo intensity within 1-m2 raster cells. Besides, a texture variable that described the spatial variation of canopy height in the proximity of a 1-m2 raster cell was found to be a useful variable. Stand delineations where the average stand area was about one hectare explained more than 80% of the variation in canopy height.

scholarly journals COMPARISON OF FOREST STRUCTURE METRICS DERIVED FROM UAV LIDAR AND ALS DATA

2019 ◽  
Vol IV-2/W5 ◽  
pp. 325-332 ◽  
Author(s):  
M. Bruggisser ◽  
M. Hollaus ◽  
D. Kükenbrink ◽  
N. Pfeifer
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Forest Structure ◽  
Laser Scanning ◽  
Point Clouds ◽  
Sensor Systems ◽  
Fractional Cover ◽  
Airborne Laser ◽  
Raster Cell ◽  
Structure Metrics ◽  
System Characteristics

<p><strong>Abstract.</strong> Point clouds derived from airborne laser scanning (ALS) and from LiDAR sensors mounted on unmanned aerial vehicles (ULS) reveal differences caused by the different sensor systems and acquisition geometries. These differences in the system characteristics are reflected in forest structure metrics that are derived from the respective point clouds. In our study, we investigate the completeness of scene coverage between the two systems and address differences between structure metrics derived from ULS and ALS, namely in point height quantiles, fractional cover (<i>fc</i>), the vertical complexity index (<i>VCI</i>) and the number of canopy layers (<i>nLayers</i>). The metrics are evaluated for raster cell sizes of 1&amp;ndash;10&amp;thinsp;m in order to investigate the spatial scale on which the sensor systems provide comparable metrics. We found highest correspondences between ALS and ULS in the <i>VCI</i>- and the <i>nLayers</i>-metrics, while fc revealed large differences. For the height quantiles, the absolute differences were larger for the 10%- (<i>h</i>10) and the 50%- (<i>h</i>50) than for the 90%- (<i>h</i>90) height quantile. Furthermore, we found differences between ALS- and ULS-metrics to decrease for larger cell sizes, except for <i>fc</i>, for which the differences increased, and <i>h</i>50 and <i>h</i>90, respectively, for which the differences were relatively stable for all cell sizes.</p>

Matched Field Processing Based on the Simulated Annealing

2013 ◽  
Vol 651 ◽  
pp. 879-884
Author(s):  
Qi Wang ◽  
Ying Min Wang ◽  
Yan Ni Gou
Keyword(s):  
Global Optimization ◽  
Simulated Annealing ◽  
Combinatorial Optimization ◽  
Mediterranean Sea ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Combinatorial Optimization Problem ◽  
Matched Field Processing ◽  
Combinatorial Optimization Problems ◽  
Passive Localization

The matched field processing (MFP) for localization usually needs to match all the replica fields in the observation sea with the received fields, and then find the maximum peaks in the matched results, so how to find the maximum in the results effectively and quickly is a problem. As known the classical simulated annealing (CSA) which has the global optimization capability is used widely for combinatorial optimization problems. For passive localization the position of the source can be recognized as a combinatorial optimization problem about range and depth, so a new matched field processing based on CSA is proposed. In order to evaluate the performance of this method, the normal mode was used to calculate the replica field. Finally the algorithm was evaluated by the dataset in the Mediterranean Sea in 1994. Comparing to the conventional matched field passive localization (CMFP), it can be conclude that the new one can localize optimum peak successfully where the output power of CMFP is maximum, meanwhile it is faster than CMFP.

scholarly journals Monitoring Forests in Space and Time Using Close-Range Sensing

2020 ◽  
Author(s):  
Mikko Vastaranta ◽  
Ninni Saarinen ◽  
Tuomas Yrttimaa ◽  
Ville Kankare ◽  
Samuli Junttila
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Laser Scanning ◽  
Structural Changes ◽  
Method Development ◽  
Forest Growth ◽  
Forest Monitoring ◽  
Time Dimension ◽  
Range Sensing ◽  
Aerial Vehicles ◽  
Close Range

In this review, we summarize the current state-of-the-art in the utilization of close-range sensing in forest monitoring. We include technologies, such as terrestrial and mobile laser scanning as well as unmanned aerial vehicles, which are mainly used for collecting detailed information from single trees, forest patches or small forested landscapes. Based on the current published scientific literature, the capacity to characterize changes in forest ecosystems using close-range sensing has clearly been recognized. Forest growth has been the most investigated cause for changes and terrestrial laser scanner the most applied sensor for capturing forest structural changes. Unmanned aerial vehicles, on the other hand, have been used to acquire aerial imagery for detecting tree height growth and monitoring forest health. Mobile laser scanning has not yet been used in forest change monitoring except for a few early investigations. Considering the length of the forest growth process, investigated time spans have been rather short, less than 10 years. In addition, data from only two time points have been used in many of the studies, which has further been limiting the capability of understanding dynamics related to forest growth. In general, method development and quantification of changes have been the main interests so far regardless of the driver of change. This shows that the close-range remote sensing community has just started to explore the time dimension and its possibilities for forest characterization.

scholarly journals AN ENERGY-BASED APPROACH FOR DETECTION AND CHARACTERIZATION OF SUBTLE ENTITIES WITHIN LASER SCANNING POINT-CLOUDS

2016 ◽  
Vol XLI-B3 ◽  
pp. 167-171
Author(s):  
Reuma Arav ◽  
Sagi Filin
Keyword(s):  
Laser Scanning ◽  
Optimization Problem ◽  
Point Clouds ◽  
Urban Environments ◽  
Natural Environments ◽  
Detection Scheme ◽  
Airborne Laser ◽  
The Common ◽  
Geomorphological Features

Airborne laser scans present an optimal tool to describe geomorphological features in natural environments. However, a challenge arises in the detection of such phenomena, as they are embedded in the topography, tend to blend into their surroundings and leave only a subtle signature within the data. Most object-recognition studies address mainly urban environments and follow a general pipeline where the data are partitioned into segments with uniform properties. These approaches are restricted to man-made domain and are capable to handle limited features that answer a well-defined geometric form. As natural environments present a more complex set of features, the common interpretation of the data is still manual at large. In this paper, we propose a data-aware detection scheme, unbound to specific domains or shapes. We define the recognition question as an energy optimization problem, solved by variational means. Our approach, based on the level-set method, characterizes geometrically local surfaces within the data, and uses these characteristics as potential field for minimization. The main advantage here is that it allows topological changes of the evolving curves, such as merging and breaking. We demonstrate the proposed methodology on the detection of collapse sinkholes.

scholarly journals Estimating the Potential of Unmanned Aerial Vehicle Use in the Oil and Gas Industry

2020 ◽  
Vol 20 (4) ◽  
pp. 344-355
Author(s):  
Anastasia D. Anikaeva ◽  
◽  
Dmitry A. Martyushev ◽  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Laser Scanning ◽  
Oil And Gas ◽  
Oil Spills ◽  
Oil And Gas Industry ◽  
Advanced Technology ◽  
Labor Costs ◽  
Gas Industry ◽  
Aerial Vehicles ◽  
Erdas Imagine

The relevance of the study is explained by the need to use unmanned aerial vehicles (UAV) to serve engineering and geodetic tasks in the oil and gas industry. Airborne photographic survey using unmanned aerial vehicles is currently an advanced technology in the area of geodesy and it replaces such methods as tacheometry, satellite-based positioning in RTK modes, manned aerial photography, and aiborne laser scanning (ALS). The potential for using UAVs in the oil and gas industry today is truly enormous. Numerous safety and reliability problems, which traditionally have been cost consuming for oil and gas companies, can be effectively addressed using UAVs. The study included processing of data obtained from the unmanned complex in three modern software packages (Agisoft Photoscan Professional, v 1.2.5.2594 (Russia), ERDAS IMAGINE, v 2015 (USA) and Pix4Dmapper Pro (Switzerland)) of various automation degrees; assessment of accuracy in ArcMap software by superimposing a topographic plan on an orthomosaic with a scale of 1: 500 on the territory under consideration; calculation of economic and labor costs. As part of the study, it was proved that the use of UAVs was possible not only for the geodetic work, but also for solving other equally important tasks of the oil and gas industry, which leads to a decrease in economic and environmental risks, automation of processes related to monitoring of oil facilities, prevention of illegal attempts of pipeline tie-ins, oil spills. In addition, based on the obtained orthophotomaps, the economic, accuracy and labor-time feasibility of using unmanned systems were confirmed. It has been established that the use of unmanned aerial vehicles in various fields of oil and gas activities for solving engineering and geodetic problems is an integral part of any company engaged in the production and transportation of hydrocarbons.

scholarly journals COMPARATIVE EVALUATION EFFICIENCY OF MOBILE LASER SCANNING AND AERIAL SURVEYING FROM UNMANNED AERIAL VEHICLES FOR ROAD SURVEY

2021 ◽  
Vol 26 (3) ◽  
pp. 20-27
Author(s):  
Mikhail Y. Bryn ◽  
◽  
Dinara R. Bashirova ◽  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Aerial Photography ◽  
Laser Scanning ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Road Survey ◽  
The Cost ◽  
Scanning Systems ◽  
Practical Recommendations

The application of mobile laser scanning and aerial photography from unmanned aerial vehicles for shooting highways is considered. The aim of the research was to compare the results of shooting using mobile laser scanning systems and aerial photography from an unmanned aerial vehicle to de-termine the preferred option for shooting a highway. The experimental part of the research was carried out using the following equipment: scanning was performed using the Topcon IP - S2 Compact sys-tem, aerial photography was carried out from the GEOSCAN 201 unmanned aerial vehicle. Based on the comparative tests performed on the section of the A - 121 "Sortavala" highway, a comparative analysis of the data obtained for various indicators was carried out: the speed of the shooting stages, the cost of a set of equipment, the cost of shooting, and the accuracy of the results was evaluated. Practical recommendations for the application of these methods are given, their advantages and disad-vantages are indicated.

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