Airborne lidar remote sensing applications in non-forested short stature environments: a review

Kulawardhana, R. W.; Popescu, Sorin C.; Feagin, Rusty A.

doi:10.15287/afr.2016.719

Cited by 15 publications

(4 citation statements)

References 81 publications

(211 reference statements)

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“…LiDAR provides promising applications for the 3D characterization of the earth's surface [66]. It has distinctive advantages for collecting high-density data containing both vertical and horizontal information for natural and man-made structures and to show their relationships [67].…”

Section: Lidar-derived Dsm Samplesmentioning

confidence: 99%

Between 2D and 3D: Studying Structural Complexity of Urban Fabric Using Voxels and LiDAR-Derived DSMs

2021

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Cities are complex systems and their physical forms are the manifestation of cultural, social and economic processes shaped by the geometry of natural and man-made elements. Digital Surface Models (DSM) using LiDAR provide an efficient volumetric transformation of urban fabric including all built and natural elements which allows the study of urban complexity through the lens of fractal dimension (D). Founded on the “box-counting” method, we reveal a voxelization technique developed in GIS (Geographic Information System) to estimate D values of ten DSM samples across central Melbourne. Estimated D values of surface models (between 2 and 3) provide a measure to interpret the structural complexity of different urban characters defined by the pattern of developments and densities. The correlations between D values with other DSM properties such as elevation, volume, solar radiation and surface roughness, showed a strong relationship between DSM volume and mean elevation. Lower strength correlations were recorded with solar radiation and surface roughness. The proposed method provides opportunities for fractal research to study pressing issues in complex urban environments such as declining physical fitness, mental health and urban biodiversity.

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Section: Lidar-derived Dsm Samplesmentioning

confidence: 99%

Between 2D and 3D: Studying Structural Complexity of Urban Fabric Using Voxels and LiDAR-Derived DSMs

2021

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“…Hence, semi-arid ecosystems greatly impact global carbon dynamics, productivity, and habitat quality (Poulter et al, 2015). Structure-functioning relationships in frequently disturbed semi-arid ecosystems are unclear, largely due to gaps in spatially continuous data and the weak response of sparse and short height vegetation in optical remote sensing (Kulawardhana et al, 2017;Stavros et al, 2017). In particular, understanding semi-arid ecosystem responses to global change is challenging due to the complex and dynamic interactions among multiple ecosystem functions.…”

Section: Introductionmentioning

confidence: 99%

Airborne and Spaceborne Lidar Reveal Trends and Patterns of Functional Diversity in a Semi-Arid Ecosystem

Ilangakoon

Glenn

Schneider

et al. 2021

Front. Remote Sens.

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Assessing functional diversity and its abiotic controls at continuous spatial scales are crucial to understanding changes in ecosystem processes and services. Semi-arid ecosystems cover large portions of the global terrestrial surface and provide carbon cycling, habitat, and biodiversity, among other important ecosystem processes and services. Yet, the spatial trends and patterns of functional diversity in semi-arid ecosystems and their abiotic controls are unclear. The objectives of this study are two-fold. We evaluated the spatial pattern of functional diversity as estimated from small footprint airborne lidar (ALS) with respect to abiotic controls and fire in a semi-arid ecosystem. Secondly, we used our results to understand the capabilities of large footprint spaceborne lidar (GEDI) for future applications to semi-arid ecosystems. Overall, our findings revealed that functional diversity in this ecosystem is mainly governed by elevation, soil, and water availability. In burned areas, the ALS data show a trend of functional recovery with time since fire. With 16 months of data (April 2019-August 2020), GEDI predicted functional traits showed a moderate correlation (r = 41–61%) with the ALS predicted traits except for the plant area index (PAI) (r = 11%) of low height vegetation (<5 m). We found that the number of GEDI footprints relative to the size of the fire-disturbed areas (=< 2 km2) limited the ability to estimate the full effects of fire disturbance. However, the consistency of diversity trends between ALS and GEDI across our study area demonstrates GEDI’s potential of capturing functional diversity in similar semi-arid ecosystems. The capability of spaceborne lidar to map trends and patterns of functional diversity in this semi-arid ecosystem demonstrates its exciting potential to identify critical biophysical and ecological shifts. Furthermore, opportunities to fuse GEDI with complementary spaceborne data such as ICESat-2 or the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR), and fine scale airborne data will allow us to fill gaps across space and time. For the first time, we have the potential to monitor carbon cycle dynamics, habitats and biodiversity across the globe in semi-arid ecosystems at fine vertical scales.

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“…Airborne laser scanning (ALS) [1][2][3][4] utilizes LiDAR (light detection and ranging) [5][6][7][8] for remote sensing of landscapes. In addition to many other applications, ALS is used to make archaeological discoveries in areas concealed by trees [9][10][11], to support forestry in forest inventory and ecology [12], and to acquire precise digital terrain models (DTMs) [13,14].…”

Section: Introductionmentioning

confidence: 99%

Airborne Optical Sectioning

2018

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Drones are becoming increasingly popular for remote sensing of landscapes in archeology, cultural heritage, forestry, and other disciplines. They are more efficient than airplanes for capturing small areas, of up to several hundred square meters. LiDAR (light detection and ranging) and photogrammetry have been applied together with drones to achieve 3D reconstruction. With airborne optical sectioning (AOS), we present a radically different approach that is based on an old idea: synthetic aperture imaging. Rather than measuring, computing, and rendering 3D point clouds or triangulated 3D meshes, we apply image-based rendering for 3D visualization. In contrast to photogrammetry, AOS does not suffer from inaccurate correspondence matches and long processing times. It is cheaper than LiDAR, delivers surface color information, and has the potential to achieve high sampling resolutions. AOS samples the optical signal of wide synthetic apertures (30-100 m diameter) with unstructured video images recorded from a low-cost camera drone to support optical sectioning by image integration. The wide aperture signal results in a shallow depth of field and consequently in a strong blur of out-of-focus occluders, while images of points in focus remain clearly visible. Shifting focus computationally towards the ground allows optical slicing through dense occluder structures (such as leaves, tree branches, and coniferous trees), and discovery and inspection of concealed artifacts on the surface.

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Airborne lidar remote sensing applications in non-forested short stature environments: a review

Cited by 15 publications

References 81 publications

Between 2D and 3D: Studying Structural Complexity of Urban Fabric Using Voxels and LiDAR-Derived DSMs

Between 2D and 3D: Studying Structural Complexity of Urban Fabric Using Voxels and LiDAR-Derived DSMs

Airborne and Spaceborne Lidar Reveal Trends and Patterns of Functional Diversity in a Semi-Arid Ecosystem

Airborne Optical Sectioning

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