Figure 5 - uploaded by Stefan Lang
Content may be subject to copyright.
Resulting height standard deviation based on moving windows at three different scales on laser point raw data. Window sizes are 5m (upper left), 10m (upper right), 20m (lower left). Dark colours indicate higher values. Lower right picture represents a multispectral image of the same area. (From Blaschke et al., 2004)
Source publication
In Austria about half of the entire area (46 %) is covered by forests. The majority of these are highly managed and controlled in growth. But besides timber production forest ecosystems play a multifunctional role including climate control, habitat provision and, especially in Austria, protection of settlements. The interrelationships among climati...
Context in source publication
Context 1
... statistics (like mean, standard deviation, and variation coefficient) were calculated in a moving window approach. An increasing window size from 5 m to 40 m reflected different scales and levels of aggregation (see figure 5). This kind of upscaling was performed by differentiating between tree types, i.e. deciduous, coniferous, and dead trees. ...
Similar publications
In Austria about half of the entire area (46 %) is covered by forests. The majority of these forests are highly managed and controlled in growth. Besides timber production, forest ecosystems play a multifunctional role including climate control, habitat provision and, especially in Austria, protection of settlements. The interrelationships among cl...
Citations
... The capability of LiDAR to pass through vegetation has attracted remarkable concern from the field of natural resource management (Gaulton, et al., 2010, Hudak, et al., 2009, Liang, et al., 2007). From a forest management stand-point, LiDAR has been used to define information about trees (Coops et al., 2007, Brolly, et al., 2013, Lang, et al., 2006), measure carbon stocks (Patenaude et al., 2004), compute fuel quantity (Seielstad and Queen, 2003) and create habitat models (Vierling, et al., 2008), develop forest inventories (Zhang, C., 2010, Woods, et al., 2008). Even though considerable research has been carried out regarding LiDAR applications in forestry, its usage in the study of urban trees has been limited. ...
Timely and accurate acquisition of information on the condition and structural changes of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting tree features include; ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraint, such as labour intensive field work, a lot of financial requirement, influences by weather condition and topographical covers which can be overcome by means of integrated airborne based LiDAR and very high resolution digital image datasets. This study presented a semi-automated approach for extracting urban trees from integrated airborne based LIDAR and multispectral digital image datasets over Istanbul city of Turkey. The above scheme includes detection and extraction of shadow free vegetation features based on spectral properties of digital images using shadow index and NDVI techniques and automated extraction of 3D information about vegetation features from the integrated processing of shadow free vegetation image and LiDAR point cloud datasets. The ability of the developed algorithms shows a promising result as an automated and cost effective approach to estimating and delineated 3D information of urban trees. The research also proved that integrated datasets is a suitable technology and a viable source of information for city managers to be used in urban trees management.
... Even though considerable research has been carried out regarding LiDAR applications in forestry (e.g. Brolly, et al. 2013, Lang, et al. 2006, Hyypa, et al. 2008, Hyypa, et al. 2009), its usage in the study of urban trees has been limited. As LiDAR applications in urban trees mapping expand, therefore, automated approach for tree detection technique is most likely to increase (Heinzel, et al. 2008). ...
Mapping of trees plays an important role in modern urban spatial data management, as many benefits and applications inherit from this detailed up-to-date data sources. Timely and accurate acquisition of information on the condition of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting trees include ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraints, such as labour intensive field work and a lot of financial requirement which can be overcome by means of integrated LiDAR and digital image datasets. Compared to predominant studies on trees extraction mainly in purely forested areas, this study concentrates on urban areas, which have a high structural complexity with a multitude of different objects. This paper presented a workflow about semi-automated approach for extracting urban trees from integrated processing of airborne based LiDAR point cloud and multispectral digital image datasets over Istanbul city of Turkey. The paper reveals that the integrated datasets is a suitable technology and viable source of information for urban trees management. As a conclusion, therefore, the extracted information provides a snapshot about location, composition and extent of trees in the study area useful to city planners and other decision makers in order to understand how much canopy cover exists, identify new planting, removal, or reforestation opportunities and what locations have the greatest need or potential to maximize benefits of return on investment. It can also help track trends or changes to the urban trees over time and inform future management decisions.
... Em período recente, dados LIDAR (Light Detection and Ranging) são cada vez mais utilizados no espaço da comunidade florestal, sobretudo para prover informações acerca de mensurações tri-dimensionais da estrutura florestal (LIM et al., 2003;LOOS e NIEMANN, 2006;LANG et al. (2006). O espectro de aplicação é cada vez mais diversificado, desde a identificação de espécies de árvores (HOLMGREN e PERSSON, 2004), até a verificação de qualquer tipo de degradação em ambientes florestados, como a aplicabilidade em manguezais relatados por Zhang et al. (2006). ...
The technological tools of Remote Sensing (RS) and Geographic Information Systems (GIS) are very important to map, inventory and monitor the forest resources, contributing to more effective planning and control procedures of
The street trees in the urban areas provide an comfortable environment to the pedestrians and drivers and play important roles to absorb the carbons. Therefore, it is necessary to acquire and manage efficiently the location, height, and crown width of street trees. This study suggests a methodology to provide quantitative information of the street trees in urban areas including the quantity, location, height, and crown width of the trees. Therefore, it is more appropriate to add functionality of changing size of the crown width of the trees in the method. In addition, the positions of the street trees were selected using the fact that street trees are generally planted along the road in a straight line. An experiment on extracting street trees was conducted in parts of Osan-si, Gyeonggi-do and the suitability of the suggested methodology was evaluated by comparing the results to a 1/1,000 digital map. Through the experimental results, the minimum, maximum, and the root mean square errors of the position of street trees were 0.5m, 1.9m, and approximately ?0.4m, respectively.
In situation that carbon dioxide emissions are being increased as urbanization, urban green space is being promoted as an alternative to find solution for these problems. In urban areas, trees have the ability to reduce carbon dioxide as well as to be aesthetic effect. In this study, we proposed the methodology which uses only LIDAR data in order to extract these trees information effectively. To improve the operational efficiency according to the extraction of trees, the proposed methodology was carried out using multiple data processing such as point, polygon and raster. Because the existing NDSM(Normalized Digital Surface Model) contains both the building and tree information, it has the problems of high complexity of data processing for extracting trees. Therefore, in order to improve these problems, this study used modified NDSM which was removed estimate regions of building. To evaluate the performance of the proposed methodology, three different zones which coexist buildings and trees within urban areas were selected and the accuracy of extracted trees was compared with the image taken by digital camera.
Light Detection and Ranging (lidar) has been widely applied to characterize the 3-dimensional (3D) structure of forests as it can generate 3D point data with high spatial resolution and accuracy. Individual tree segmentations, usually derived from the canopy height model, are used to derive individual tree structural attributes such as tree height, crown diame-ter, canopy-based height, and others. In this study, we develop a new algorithm to segment individual trees from the small footprint discrete return airborne lidar point cloud. We experimentally applied the new algorithm to segment trees in a mixed conifer forest in the Sierra Nevada Moun-tains in California. The results were evaluated in terms of recall, precision, and F-score, and show that the algorithm detected 86 percent of the trees ("recall"), 94 percent of the segmented trees were correct ("precision"), and the overall F-score is 0.9. Our results indicate that the proposed algorithm has good potential in segmenting individual trees in mixed conifer stands of similar structure using small footprint, discrete return lidar data.
