Estimating number of trees, tree height and crown width using Lidar data

Unger, Daniel; Hung, I‐Kuai; Brooks, Robert C.; Williams, Hans M.

doi:10.1080/15481603.2014.909107

Cited by 37 publications

(13 citation statements)

References 16 publications

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“…The application of airborne LiDAR and high spatial resolution satellite data are limited due to their high cost as well as small coverage (e.g., swath width of Quickbird, Ikonos, Worldview 1, Worldview 2, and Worldview 3 are 16.8 km, 11.3 km, 17.6 km, 16.4 km, and 13.1 km, respectively), though they are promising in certain applications. For instance, LiDAR was reported to provide promising estimates of forest biomass [26][27][28], tree height [29][30][31], and detection of individual tree crowns [32][33][34]. In comparison, the other optical multispectral satellite data of lower spatial resolution had a relatively large coverage area (e.g., the swath width at the nadir of RapidyEye, SPOT-5, Landsat and MODIS is 77 km, 60 km, 185 km, and 2330 km, respectively), which reduced the cost per unit area.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Forest Structural Diversity Using the Spectral and Textural Information Derived from SPOT-5 Satellite Images

Meng

Wang

et al. 2016

Remote Sensing

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Uneven-aged forest management has received increasing attention in the past few years. Compared with even-aged plantations, the complex structure of uneven-aged forests complicates the formulation of management strategies. Forest structural diversity is expected to provide considerable significant information for uneven-aged forest management planning. In the present study, we investigated the potential of using SPOT-5 satellite images for extracting forest structural diversity. Forest stand variables were calculated from the field plots, whereas spectral and textural measures were derived from the corresponding satellite images. We firstly employed Pearson's correlation analysis to examine the relationship between the forest stand variables and the image-derived measures. Secondly, we performed all possible subsets multiple linear regression to produce models by including the image-derived measures, which showed significant correlations with the forest stand variables, used as independent variables. The produced models were evaluated with the adjusted coefficient of determination (R 2 adj ) and the root mean square error (RMSE). Furthermore, a ten-fold cross-validation approach was used to validate the best-fitting models (R 2 adj > 0.5). The results indicated that basal area, stand volume, the Shannon index, Simpson index, Pielou index, standard deviation of DBHs, diameter differentiation index and species intermingling index could be reliably predicted using the spectral or textural measures extracted from SPOT-5 satellite images.

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Section: Introductionmentioning

confidence: 99%

Estimation of Forest Structural Diversity Using the Spectral and Textural Information Derived from SPOT-5 Satellite Images

Meng

Wang

et al. 2016

Remote Sensing

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“…Other recent studies have also reported using high-resolution LiDAR for accurately and efficiently obtaining data on road position (White et al 2010, Craven & Wing 2014. Using this technology, forest managers can reduce the necessity for field-based investigations focused on this essential parameter, the obtained data being also useful for many other forest inven-3D display of the present forested area with the ancient underground defensive structures of the Roman Empire Frontiers from Moigrad-Porolissum tory operations (Popescu et al 2003, Unger et al 2014.…”

Section: Discussionmentioning

confidence: 99%

“…However, the transdisciplinary use of LiDAR data available from a particular area has rarely been accomplished (Harpold et al 2015). In addition to ancient structures mapping, LiDAR provides accurate measurements of numerous forest inventory attributes at a level of detail that is unavailable to traditional forestry measurements (Popescu & Wynne 2004, Wulder et al 2008, Unger et al 2014, facilitates forest road network mapping (White et al 2010, Azizi et al 2014, and the delineation of forest creeks and streams (Wulder et al 2008, Roman et al 2015. The detailed forest road network map provides essential information for forestry practices such as forest management, fire protection, transport of forest products and prevention of smuggling, but also for travel, recreation and education (White et al 2010, Abdi et al 2012.…”

Section: Introductionmentioning

confidence: 99%

An integrated airborne laser scanning approach to forest management and cultural heritage issues: a case study at Porolissum, Romania

et al. 2017

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Abstract. This paper explores the opportunities that arise where forest ecosystem management and cultural heritage monuments protection converge. The case study area for our analysis was the landscape surrounding the Moigrad-Porolissum Archaeological site. We emphasize that an Airborne Laser Scanning (ALS or LiDAR-Light Detection and Ranging) approach to both forest management and cultural heritage conservation is an outstanding tool, assisting policy-makers and conservationists in decision making for integrated planning and management of the environment. LiDAR-derived surface models enabled a synoptic, never-seen-before view of the ancient Roman frontiers defensive systems while also revealing the present forest road network. The thorough and accurate road inventory data are very useful for updating and modifying forest base maps and registries and also for identifying the priority sectors for archaeological discharge. The ability to identify and determine optimal routes for forest management and to locate previously unmapped ancient archaeological remains aids in reducing costs and creating operational efficiencies as well as in complying with the legislation and avoiding infringements. The potential of LiDAR to demonstrate the long-term and comprehensive human impact on wooded areas is discussed. We identified a significant historical landscape change, consisting of a deforestation period, spanning over more than 160 years, during the Roman Period in Dacia (106-271 AD). The transdisciplinary analysis of the LiDAR data provides the base for combining knowledge from archaeology, forestry and environmental history in order to achieve a thorough analysis of the landscape changes and history. In the "nature versus culture" dichotomy, the landscape, outfield areas and forests are primarily perceived as nature, while in reality they are often heavily marked by human impact. LiDAR offers an efficient method for broadening our knowledge regarding the character and extent of human interaction with landscapes -forested or otherwise.

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“…Parameters of individual trees, such as tree location, tree species, tree height, diameter at breast height (DBH), and crown diameter, are vital for sustainable and precise forest management [4][5][6]. These individual tree-related properties can also be utilized to estimate forest parameters at stand level, such as tree species composition, mean tree height, timber volume, canopy density, and mean basal area [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

A Region-Based Hierarchical Cross-Section Analysis for Individual Tree Crown Delineation Using ALS Data

et al. 2017

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Abstract:In recent years, airborne Light Detection and Ranging (LiDAR) that provided three-dimensional forest information has been widely applied in forest inventory and has shown great potential in automatic individual tree crown delineation (ITCD). Usually, ITCD algorithms include treetop detection and crown boundary delineation procedures. In this study, we proposed a novel method called region-based hierarchical cross-section analysis (RHCSA), which combined the two procedures together based on a canopy height model (CHM) derived from airborne LiDAR data for ITCD. This method considers the CHM as a three-dimensional topological surface, simulates stereoscopic scanning from top to bottom using an iterative process, and utilizes the individual crown and vertical structure of crowns to progressively detect individual treetops and delineate crown boundaries. The proposed method was tested in natural forest stands with high canopy densities in Liangshui National Nature Reserve and Maoershan Forest Farm, Heilongjiang Province, China. Its performance was evaluated by an accuracy procedure that considered both the relative position of treetops and overlapped area of crowns. The average overall accuracy achieved was 85.12% for coniferous plots, 83.86% for deciduous plots and 86.44% for coniferous and broad-leaved mixed forest plots. The results revealed that the RHCSA method can detect and delineate individual tree crowns with little influence from forest types and crown size. It could provide technical support for individual tree crown delineation in coniferous, deciduous and mixed forests with high canopy densities.

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Estimating number of trees, tree height and crown width using Lidar data

Cited by 37 publications

References 16 publications

Estimation of Forest Structural Diversity Using the Spectral and Textural Information Derived from SPOT-5 Satellite Images

Estimation of Forest Structural Diversity Using the Spectral and Textural Information Derived from SPOT-5 Satellite Images

An integrated airborne laser scanning approach to forest management and cultural heritage issues: a case study at Porolissum, Romania

A Region-Based Hierarchical Cross-Section Analysis for Individual Tree Crown Delineation Using ALS Data

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