A Novel Automatic Method for the Fusion of ALS and TLS LiDAR Data for Robust Assessment of Tree Crown Structure

Paris, Claudia; Kelbe, David; Aardt, Jan van; Bruzzone, Lorenzo

doi:10.1109/tgrs.2017.2675963

Cited by 68 publications

(53 citation statements)

References 50 publications

(46 reference statements)

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“…Textural analysis of high resolution satellite or aerial imagery, for example, would also provide an objective secondary indicator of forest density (see Couteron et al, ) that could be used (Kayitakire et al, ). These data sets could also be fused with TLS segmentation in a two‐step process, which might further improve output results (Paris et al, ; Sankey & Glenn, ). Incorporating these secondary data sources would inform scan locations and density between scans, which might greatly improve the variables derived and methods presented in our analysis.…”

Section: Discussionmentioning

confidence: 99%

Examining Forest Structure With Terrestrial Lidar: Suggestions and Novel Techniques Based on Comparisons Between Scanners and Forest Treatments

Donager

Sankey

et al. 2018

Earth and Space Science

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Terrestrial laser scanners (TLSs) provide a tool to assess and monitor forest structure across forest landscapes. We present TLS methods, suggestions, and mapped guidelines for planning TLS acquisitions at varying scales and forest densities. We examined rates of point‐density decline with distance from two TLS that acquire data at relatively high and low point density and found that the rates were nearly identical between scanners (p value <0.01), suggesting that our findings are applicable to a range of TLS types. Using unique, TLS‐adapted processing methods, we determined the relative accuracy of TLS‐derived plot‐scale estimates of tree height, diameter‐at‐breast‐height, height‐to‐canopy, tree counts, as well as treatment‐scale tree density and patch metrics, using both high point density and low point density TLS among thinned and nonthinned forest treatments. The high‐density TLS consistently provides more accurate estimates of plot‐level metrics (R2 = 0.46 to 0.87) than the low‐density TLS (R2 = −0.14 to 0.53). At treatment scales, tree density estimates are similar among scanners (R2 = 0.95 vs. 0.71), as are canopy cover and patch metrics. We develop and present the normalized density‐distance index (NDDI), which can account for up to 59% of the variance in estimate error and can be used to guide TLS‐data acquisition plans. This index indicates whether a given location has generally higher point density (higher NDDI) relative to the distance from the scanner and can be used as a proxy for uncertainty. Using NDDI as a guide for fair comparison between scanners, both plot‐ and treatment‐scale estimates improved.

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Section: Discussionmentioning

confidence: 99%

Examining Forest Structure With Terrestrial Lidar: Suggestions and Novel Techniques Based on Comparisons Between Scanners and Forest Treatments

Donager

Sankey

et al. 2018

Earth and Space Science

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“…size, shape and orientation) of the individuals of the community are available. Measuring these variables in a fully mapped community could appear as a challenge but the ever-growing development of remote sensing technologies such as LIDAR and digital photogrammetry (Lefsky, Cohen, Parker, & Harding, 2002;Morsdorf et al, 2004;Paris, Kelbe, van Aardt, & Bruzzone, 2017) or terrestrial laser scanning (Hess, Härdtle, Kunz, Fichtner, & von Oheimb, 2018) that enable to map the species canopy would render this a routine task in the near future. In addition, although a high number of simulations has been suggested to be necessary to get reliable inference in Monte Carlo tests (Ruxton & Neuhäuser, 2013), our OAA test could attain enough statistical power in most situations with just 199 simulations.…”

Section: Discussionmentioning

confidence: 99%

The shape is more important than we ever thought: Plant to plant interactions in a high mountain community

et al. 2019

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Plant to plant interactions are probably the most important driver of species coexistence at fine spatial scales, but their detection represents a challenge in Ecology. Spatial point pattern analysis (SPPA) is likely the approach most used to identify them, however, it suffers from some limitations related to the over‐simplification of individuals to points. Here, we propose a new approach called Overlapping Area Analysis (OAA) to test whether the consideration of the shape and orientation of the individuals reveal signs of interactions between species that would remain undetected with SPPA. We used this approach to analyse a fully mapped cryophilic grassland in the Sierra de Guadarrama National Park (Spain), where the crown of each individual plant (i.e. the species canopy) was approximated by a polygon. We then computed and compared the total overlapping area between the canopy of a focal species and that of any other species in the community with the expectations of a null model of random rotation of each plant around its centroid. We complemented the results of our new approach by comparing with that of SPPA of plants’ centroids. Results of OAA showed that up to 41% of species pairs had less canopy overlap than expected, suggesting that many interspecific canopy associations in this plant community were significantly negative at the finest spatial scale. Contrarily, SPPA estimated that 12% of species pairs were positively associated at spatial scales up to 20 cm, confirming the facilitative effect displayed by the main engineer in the community (Festuca curvifolia Lag.) and by some other dominant species. Our new approach quantifying canopy associations provides new insights into the processes guiding community assembly. While the results of SPPA suggested the prevalence of traditional ‘stress gradient hypothesis’ (i.e. prevalence of positive interactions under stressful abiotic conditions), OAA revealed that many interspecific canopy associations were significantly negative. Overall, most facilitated species optimized this positive effect by placing their centroids as close to the benefactor species as their foraging behaviour allowed while avoiding crown overlap. The method proposed is available in a dedicated r‐package that will facilitate its application by other ecologists.

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“…Thus, it could be beneficial to integrate both methods to produce more accurate data. Point clouds fusion and assimilation by ALS and TLS could be done by using same point references 39,40 or assigning multiple TLS point clouds to ALS point clouds 41 . Detail study need to be done since the ALS and TLS are varied in terms of scanning mechanism, data capture mode, typical project size and obtainable accuracy and resolution.…”

Section: =mentioning

confidence: 99%

Application of Ground-Based LiDAR for Analysing Oil Palm Canopy Properties on the Occurrence of Basal Stem Rot (BSR) Disease

Husin

Khairunniza-Bejo

Abdullah

et al. 2020

Sci Rep

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Ground-based LiDAR also known as terrestrial Laser Scanning (tLS) technology is an active remote sensing imaging method said to be one of the latest advances and innovations for plant phenotyping. Basal Stem Rot (BSR) is the most destructive disease of oil palm in Malaysia that is caused by whiterot fungus Ganoderma boninense, the symptoms of which include flattening and hanging-down of the canopy, shorter leaves, wilting green fronds and smaller crown size. therefore, until now there is no critical investigation on the characterisation of canopy architecture related to this disease using tLS method was carried out. This study proposed a novel technique of BSR classification at the oil palm canopy analysis using the point clouds data taken from the TLS. A total of 40 samples of oil palm trees at the age of nine-years-old were selected and 10 trees for each health level were randomly taken from the same plot. The trees were categorised into four health levels -T0, T1, T2 and T3, which represents the healthy, mildly infected, moderately infected and severely infected, respectively. the tLS scanner was mounted at a height of 1 m and each palm was scanned at four scan positions around the tree to get a full 3D image. Five parameters were analysed: S200 (canopy strata at 200 cm from the top), S850 (canopy strata at 850 cm from the top), crown pixel (number of pixels inside the crown), frond angle (degree of angle between fronds) and frond number. the results taken from statistical analysis revealed that frond number was the best single parameter to detect BSR disease as early as T1. In classification models, a linear model with a combination of parameters, ABD -A (frond number), B (frond angle) and D (S200), delivered the highest average accuracy for classification of healthy-unhealthy trees with an accuracy of 86.67 per cent. It also can classify the four severity levels of infection with an accuracy of 80 per cent. This model performed better when compared to the severity classification using frond number. the novelty of this research is therefore on the development of new approach to detect and classify BSR using point clouds data of tLS.LiDAR (Light detection and ranging) is an active remote sensing technology similar to Radar (Radio detection and ranging) but which uses laser light. LiDAR measures the distance or range to a target by illuminating the target with a pulsed laser light and measuring the reflected pulses with a sensor. It can directly represent external structures and carry out profiling for objects or trees. Laser Scanning (LS) profiling systems consist of a measuring instrument that can measure vertical angles, horizontal angles, and distances with a high standard of accuracy and speed by means of a mobile mirror or prism system allowing the mapping of morphological features of targets 1 .Research and field site works used extensive biometric data in estimating tree properties while offering the possibility of reducing inventory costs. Previous studies have demonstrated that LiDAR could be used to ...

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A Novel Automatic Method for the Fusion of ALS and TLS LiDAR Data for Robust Assessment of Tree Crown Structure

Cited by 68 publications

References 50 publications

Examining Forest Structure With Terrestrial Lidar: Suggestions and Novel Techniques Based on Comparisons Between Scanners and Forest Treatments

Examining Forest Structure With Terrestrial Lidar: Suggestions and Novel Techniques Based on Comparisons Between Scanners and Forest Treatments

The shape is more important than we ever thought: Plant to plant interactions in a high mountain community

Application of Ground-Based LiDAR for Analysing Oil Palm Canopy Properties on the Occurrence of Basal Stem Rot (BSR) Disease

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