Detection of lying tree stems from airborne laser scanning data using a line template matching algorithm

Lindberg, Eva; Hollaus, Markus; Mücke, Werner; Fransson, Johan E. S.; Pfeifer, Norbert

doi:10.5194/isprsannals-ii-5-w2-169-2013

Cited by 25 publications

(29 citation statements)

References 15 publications

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“…Lindbergand and Nyström reduced interference from other objects by executing binary classification based on height and then extracted fallen trees using template matching. They reported a correctness of 32% and 38%, respectively [18,19]. The interference of objects with a similar geometry (e.g., river boundaries and shrub rows) also poses a challenge as it cannot be effectively removed using only height or geometric characteristics.…”

Section: Comparison With Conventional Methodsmentioning

confidence: 99%

“…They reported a completeness of 75.6% and an accuracy of 89.9%. Lindberg and Nyström et al performed binary classification based on height characteristics to eliminate the interference of foreign objects under a closed canopy [18,19]. Their techniques were based on the template matching method, with a reported correctness of 32% and 38% at individual tree level, respectively.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Approach for Coarse-to-Fine Windthrown Tree Extraction Based on Unmanned Aerial Vehicle Images

2017

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Surveys of windthrown trees, resulting from hurricanes and other types of natural disasters, are an important component of agricultural insurance, forestry statistics, and ecological monitoring. Aerial images are commonly used to determine the total area or number of downed trees, but conventional methods suffer from two primary issues: misclassification of windthrown trees due to the interference from other objects or artifacts, and poor extraction resolution when trunk diameters are small. The objective of this study is to develop a coarse-to-fine extraction technique for individual windthrown trees that reduces the effects of these common flaws. The developed method was tested using UAV imagery collected over rubber plantations on Hainan Island after the Nesat typhoon in China on 19 October 2011. First, a coarse extraction of the affected area was performed by analyzing the image spectrum and textural characteristics. A thinning algorithm was then used to simplify downed trees into skeletal structures. Finally, fine extraction of individual trees was achieved using a line detection algorithm. The completeness of windthrown trees in the study area was 75.7% and the correctness was 92.5%. While similar values have been reported in other studies, they often include constraints, such as tree height. This technique is proposed to be a more feasible extraction algorithm as it is capable of achieving low commission errors across a broad range of tree heights and sizes. As such, it is a viable option for extraction of windthrown trees with a small trunk diameter.

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Section: Comparison With Conventional Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Coarse-to-Fine Windthrown Tree Extraction Based on Unmanned Aerial Vehicle Images

2017

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“…The results concerning the detection of the downed trees was good. In previous studies, direct ALS-based detection methods have found between 41% (Lindberg et al 2013) and 75% ) of the downed stems.…”

Section: Resultsmentioning

confidence: 99%

Developing laser scanning applications for mapping and monitoring single tree characteristics for the needs of urban forestry

Tanhuanpää¹

2016

Diss. For.

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To be presented with the permission of the Faculty of Agriculture and Forestry, University of Helsinki, for public criticism in lecture room B5, B-building (Viikki Campus, Latokartanonkaari 7, Helsinki) on October 28 th , 2016 at 12 o'clock noon. ABSTRACTUrban forests provide various ecosystem services. However, they also require fairly intensive management, which can be supported with up-to-date tree-level data. Until recently, the data have been collected using traditional field measurements. Laser scanning (LS) techniques provide efficient means for acquiring detailed three-dimensional (3D) data from the vegetation. The objective of this dissertation was to develop methods for mapping and monitoring urban forests at tree level.In substudy I, a method (MS-STI) utilizing multiple data sources was developed for extracting tree-level attributes. The method combined airborne laser scanning (ALS), field measurements, and tree locations. The field sample was generalized using the non-parametric nearest neighbor (NN) approach. The relative root mean square error (RMSE) of diameter at breast height (DBH) varied between 18.8-33.8%.The performance of MS-STI was assessed in substudy II by applying it to an existing tree register. 88.8% of the trees were successfully detected, and the relative RMSE of DBH for the most common diameter classes varied between 21.7-24.3%.In substudy III, downed trees were mapped from a recreational forest area by detecting changes in the canopy. 97.7% of the downed trees were detected and the commission error was 10%. Species group, DBH, and volume were estimated for all downed trees using ALS metrics and existing allometric models. For the DBH, the relative RMSE was 20.8% and 34.1% for conifers and deciduous trees respectively.Finally, in substudy IV, a method utilizing terrestrial laser scanning (TLS) and tree basic density was developed for estimating tree-level stem biomass for urban trees. The relative RMSE of the stem biomass estimates varied between 8.4-10.5%.The dissertation demonstrates the applicability of LS data in assessing tree-level attributes for urban forests. The methods developed show potential in providing the planning and management of urban forests with cost-efficient and up-to-date tree-level data.

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“…This procedure is similar to methods used in remote sensing for the detection of circular or linear features in digital elevation models (Pirotti, ; Nyström et al ., ; Schneider et al ., ). Whereas for the extraction of circular anomalies the correlation can be calculated by simply sliding the template across the image, for linear features such as windthrown trees, the template needs to be rotated in small increments to find the highest NCC (Lindberg et al , ; Mücke et al , ). For a set of orthogonal walls, as presented in this paper, only one orientation needs to be determined.…”

Section: Methods For the Detection Of Wall Structuresmentioning

confidence: 99%

Detection of Buried Roman Wall Remains in Ground‐penetrating Radar Data using Template Matching

Verdonck

2016

Archaeological Prospection

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Whereas in the last decades the acquisition and processing of archaeological ground-penetrating radar (GPR) data have become mature, the interpretation is still challenging. Manual delineation in three dimensions is time consuming, and often the determination of an isosurface value is not straightforward. This paper presents a method designed specifically for the extraction of buried linear features such as wall foundations, based on template matching. First, the three-dimensional (3D) GPR data cube is synthesized into a two-dimensional (2D) slice. To achieve this, an energy slice based on a sufficiently large time window may often be appropriate, although in this study a combination with other attributes, for example based on phase symmetry, made weak anomalies more distinct. In the next step, we compute the 2D normalized cross-correlation of the composite 2D slice and a number of templates with dimensions similar to the walls in the data set. Of the resulting correlation matrices, the highest correlation coefficient is kept for each pixel, if it exceeds a certain threshold. In this way, wall foundations are successfully mapped, but also many false detections are produced. The latter are greatly reduced in number by using a size threshold and discarding isolated features. The remaining regions are enclosed in bounding boxes, which after vertical extrusion can be used as a simplified 3D representation of the wall structures, and for the creation of a filtered isosurface. For the evaluation of our results, a manual interpretation was used. In the 2D case (i.e. when comparing the total area of the automatically mapped structures versus the manually delineated ones), both the detection rate and the correctness were~77%. Slightly lower rates (~71%) were obtained in the 3D case (i.e. comparing volumes). Our method was applied to the GPR survey of a Roman villa in Kent, UK.

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Detection of lying tree stems from airborne laser scanning data using a line template matching algorithm

Cited by 25 publications

References 15 publications

A Novel Approach for Coarse-to-Fine Windthrown Tree Extraction Based on Unmanned Aerial Vehicle Images

A Novel Approach for Coarse-to-Fine Windthrown Tree Extraction Based on Unmanned Aerial Vehicle Images

Developing laser scanning applications for mapping and monitoring single tree characteristics for the needs of urban forestry

Detection of Buried Roman Wall Remains in Ground‐penetrating Radar Data using Template Matching

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