Quantifying 3D vegetation structure in wetlands using differently measured airborne laser scanning data

Koma, Zsófia; Zlinszky, András; Bekő, László; Burai, Péter; Seijmonsbergen, A.C.; Kissling, W. Daniel

doi:10.1016/j.ecolind.2021.107752

Cited by 18 publications

(8 citation statements)

References 40 publications

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“…In recent years, point cloud products have provided the possibility to efficiently measure tree biometric variables such as DBH, tree height and crown diameter (Kwong and Fung, 2020;Novotny et al, 2021;Wang et al, 2019). UAV image (Fakhri and Latifi, 2021), mobile laser scanning (MLS) (Vandendaele et al, 2022), terrestrial laser scanning (TLS) (Liang et al, 2016), and airborne laser survey (ALS) (Koma et al, 2021) all showed high accuracy. In the field of urban forestry, there have been notable endeavors that have yielded success in the application of point cloud technology.…”

Section: Introductionmentioning

confidence: 99%

Optimization of unmanned aerial vehicle application for measuring in complex urban green space with rich landscape value

Jin,

Huang,

Wang

et al. 2023

Preprint

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The main tree biometric variables of urban green space can derive indicators of multiple ecological benefit values. Compared with plantations and natural forests, urban green space is usually featured with higher tree richness, more complex landscape design, and a higher degree of spatial heterogeneity. Appropriate designs for flight variable settings in complex urban space can significantly improve the quality of data, and bring large differences in economic and time costs in practical applications. However, current studies have a limited understanding of flight variables setting for UAV applications in complex urban green spaces. We carried out rigorous and practical designs for flight variable settings with high-frequency UAV oblique image measurements. We tested and quantified the effect of the settings of main flight variables (i.e., flight altitude, image overlap, gimbal pitch and solar elevation) on the process data and final data quality in a representative complex urban green space. In the limited range of flight variable settings, the data accuracy is significantly different in the complex urban green space. We found that solar elevation is the most important factor affecting the data quality. Specifically, flight operations with a lower solar elevation provided a higher measurement accuracy and outstanding cost-effectiveness which is significantly different from the solar elevation setting for measuring in plantations. Our results (which are different from the previous study on homogenous green spaces) also suggested to avoid strong sunlight during flight operations and to ensure that the flight altitude is three to four times higher than the tallest tree at least to improve data quality. The settings of the image overlap and the gimbal pitch should take more time cost and economic benefits into consideration. This study demonstrated the feasibility of UAV applications in complex urban green spaces, and the impact and importance of each flight variable on the dataset quality. The systematic analysis, quantitative results, and exact visualizations can facilitate a wider application space (i.e., urban forestry, landscape ecology, urban planning and urban design) and higher application quality of UAV oblique in urban green space.

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Section: Introductionmentioning

confidence: 99%

Optimization of unmanned aerial vehicle application for measuring in complex urban green space with rich landscape value

Jin,

Huang,

Wang

et al. 2023

Preprint

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“…The Air-borne Laser Scanning (ALS) solution uses the time difference between the laser pulse emitted from a sensor in the air and the returning signal from the vegetation (trunk, branch stems, leaves), ground, or other object surface. Based on the travel time of the laser, the angles of the LiDAR platform, and their true coordinates (POS -GNSS + IMU; Position and Orientation System), the coordinates (x,y,z) of the objects can be calculated, obtaining a 3D point cloud, which can be processed (after ground classification) into a raster-based Digital Terrain Model (DTM) approximating the bare ground and the Digital Surface Model (DSM), representing tree canopies, roofs of buildings, and other objects such as ground and roads [43][44][45]. The processing of the next echo's returning by the ground and vegetation most often results in the generation of a Canopy Height Model (CHM), which represents the normalized height of trees and shrubs.…”

Section: Introductionmentioning

confidence: 99%

Monitoring 3D Changes in Urban Forests Using Landscape Metrics Analyses Based on Multi-Temporal Remote Sensing Data

Zięba-Kulawik

Wężyk

2022

Land

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Rapid urbanization is causing changes in green spaces and ecological connectivity. So far, urban ecosystem research has mainly focused on using landscape metrics (LM) in two-dimensional (2D) space. Our study proposes three-dimensional (3D) measures of urban forests (UF) and LM calculations using LiDAR technology. First, we estimated the UF volume of Krakow (Poland) and the distribution of vegetation (low, medium, high) using a voxel-based GEOBIA approach based on the ALS LiDAR point cloud, satellite imagery, and aerial orthophotos at specific timestamps: 2006, 2012, 2017. Then, the appropriate landscape metrics were selected (NP, AREA_MN, CONTIG_MN, LPI, PARA_MN, SPLIT, MESH, PD, DIVISION, LSI) to quantify the differences between the 2D- and 3D-derived vegetation structures and detect changes in the urban landscape. The results showed that areas with low vegetation decreased due to the expansion of built-up areas, while areas with medium and high vegetation increased in Krakow between 2006, 2012, and 2017. We have shown that the lack of information on the vertical features of vegetation, i.e., 2D greenery analysis, leads to an overestimation of landscape connectivity. In the 3D vegetation classes, it was observed that low vegetation was the best connected, followed by high vegetation, while medium vegetation was dispersed in the city space. These results are particularly relevant for the urban environment, where the distribution of green space is crucial for the provision of ecosystem services.

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“…Moreover, aside from reed height, reed extent and reed density, Corti et al proposed the reed frontline geometry metric sinuosity as a health status indicator of the aquatic reed stand [23]. Recently, Koma et al [29] showed the potential of airborne LiDAR to measure reed heights, LAI and biomass from the 3D structure of the vegetation across three Hungarian lakes.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Aquatic Reed Stands from Airborne Photogrammetric 3K Data

et al. 2022

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Aquatic reed beds provide important ecological functions, yet their monitoring by remote sensing methods remains challenging. In this study, we propose an approach of assessing aquatic reed stand status indicators based on data from the airborne photogrammetric 3K-system of the German Aerospace Center (DLR). By a Structure from Motion (SfM) approach, we computed stand surface models of aquatic reeds for each of the 14 areas of interest (AOI) investigated at Lake Chiemsee in Bavaria, Germany. Based on reed heights, we subsequently calculated the reed area, surface structure homogeneity and shape of the frontline. For verification, we compared 3K aquatic reed heights against reed stem metrics obtained from ground-based infield data collected at each AOI. The root mean square error (RMSE) for 1358 reference points from the 3K digital surface model and the field-measured data ranged between 39 cm and 104 cm depending on the AOI. Considering strong object movements due to wind and waves, superimposed by water surface effects such as sun glint altering 3K data, the results of the aquatic reed surface reconstruction were promising. Combining the parameter height, area, density and frontline shape, we finally calculated an indicator for status determination: the aquatic reed status index (aRSI), which is based on metrics, and thus is repeatable and transferable in space and time. The findings of our study illustrate that, even under the adverse conditions given by the environment of the aquatic reed, aerial photogrammetry can deliver appropriate results for deriving objective and reconstructable parameters for aquatic reed status (Phragmites australis) assessment.

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Quantifying 3D vegetation structure in wetlands using differently measured airborne laser scanning data

Cited by 18 publications

References 40 publications

Optimization of unmanned aerial vehicle application for measuring in complex urban green space with rich landscape value

Optimization of unmanned aerial vehicle application for measuring in complex urban green space with rich landscape value

Monitoring 3D Changes in Urban Forests Using Landscape Metrics Analyses Based on Multi-Temporal Remote Sensing Data

Assessment of Aquatic Reed Stands from Airborne Photogrammetric 3K Data

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