scholarly journals Estimating Ground Elevation and Vegetation Characteristics in Coastal Salt Marshes Using UAV-Based LiDAR and Digital Aerial Photogrammetry

2021 ◽  
Vol 13 (22) ◽  
pp. 4506
Author(s):  
Daniele Pinton ◽  
Alberto Canestrelli ◽  
Benjamin Wilkinson ◽  
Peter Ifju ◽  
Andrew Ortega
Keyword(s):  
Salt Marsh ◽  
High Resolution ◽  
Salt Marshes ◽  
Point Cloud ◽  
Point Clouds ◽  
Vegetation Density ◽  
Marsh Vegetation ◽  
Vegetation Height ◽  
Aerial Photogrammetry ◽  
Vegetation Characteristics

This study evaluates the skills of two types of drone-based point clouds, derived from LiDAR and photogrammetric techniques, in estimating ground elevation, vegetation height, and vegetation density on a highly vegetated salt marsh. The proposed formulation is calibrated and tested using data measured on a Spartina alterniflora-dominated salt marsh in Little Sapelo Island, USA. The method produces high-resolution (ground sampling distance = 0.40 m) maps of ground elevation and vegetation characteristics and captures the large gradients in the proximity of tidal creeks. Our results show that LiDAR-based techniques provide more accurate reconstructions of marsh vegetation (height: MAEVH = 12.6 cm and RMSEVH = 17.5 cm; density: MAEVD = 6.9 stems m−2 and RMSEVD = 9.4 stems m−2) and morphology (MAEM = 4.2 cm; RMSEM = 5.9 cm) than Digital Aerial Photogrammetry (DAP) (MAEVH = 31.1 cm; RMSEVH = 38.1 cm; MAEVD = 12.7 stems m−2; RMSEVD = 16.6 stems m−2; MAEM = 11.3 cm; RMSEM = 17.2 cm). The accuracy of the classification procedure for vegetation calculation negligibly improves when RGB images are used as input parameters together with the LiDAR-UAV point cloud (MAEVH = 6.9 cm; RMSEVH = 9.4 cm; MAEVD = 10.0 stems m−2; RMSEVD = 14.0 stems m−2). However, it improves when used together with the DAP-UAV point cloud (MAEVH = 21.7 cm; RMSEVH = 25.8 cm; MAEVD = 15.2 stems m−2; RMSEVD = 18.7 stems m−2). Thus, we discourage using DAP-UAV-derived point clouds for high-resolution vegetation mapping of coastal areas, if not coupled with other data sources.

scholarly journals NATURE-BASED COASTAL PROTECTION: WAVE DAMPING BY FLEXIBLE SALT MARSH VEGETATION

2020 ◽  
pp. 9
Author(s):  
Thomas J van Veelen ◽  
Harshinie Karunarathna ◽  
William G Bennett ◽  
Tom P Fairchild ◽  
Dominic E Reeve
Keyword(s):  
Salt Marsh ◽  
Salt Marshes ◽  
Large Scale ◽  
Coastal Vegetation ◽  
Coastal Protection ◽  
Coastal Zones ◽  
Wave Damping ◽  
Marsh Vegetation ◽  
Efficient Manner ◽  
Wave Energy Dissipation

The ability of coastal vegetation to attenuate waves has been well established (Moller et al., 2014). Salt marshes are vegetated coastal wetlands that can act as nature- based coastal defenses. They exhibit a range of plant species, which have been shown to differ in the amount of wave damping they provide (Mullarney & Henderson, 2018). Recent studies have shown that plant flexibility is a key parameter that controls wave energy dissipation (Paul et al., 2016). Yet, no model exists that includes plant flexibility in computationally efficient manner for large-scale coastal zones. Therefore, we have developed a new model for flexible vegetation based on the key mechanisms in the wave-vegetation interaction and applied it to an estuary with diverse salt marsh vegetation.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/AjnFx3aFSzs

Coastal salt-marshes plant communities of the Salicornietea fruticosae class in Apulia (Italy)

Biologia ◽  
2014 ◽  
Vol 69 (1) ◽  
Author(s):  
Saverio Sciandrello ◽  
Valeria Tomaselli
Keyword(s):  
Salt Marsh ◽  
Plant Communities ◽  
Salt Marshes ◽  
Field Work ◽  
Salt Marsh Vegetation ◽  
Marsh Vegetation ◽  
Apulia Region ◽  
Coastal Salt Marshes ◽  
Ecological Features ◽  
Halocnemum Strobilaceum

AbstractAn overview of the salt-marsh herbland and scrub vegetation belonging to the class Salicornietea fruticosae Br.-Bl. et Tx. ex A. Bolòs y Vayreda 1950 in Apulia is presented. Data available from literature have been supplemented with original relevés performed in different locations of the Apulia region. On the basis of a total of 297 relevés, fifteen communities have been defined, according to the traditional phytosociological system based on dominant and/or diagnostic taxa. For comparison purposes, the salt-marsh vegetation has been classified using numerical methods. The results obtained show that most of the clusters correspond to specific associations, and confirm the division into vegetation alliances and orders. Numerical analysis also allowed us to assign the proper allocation of some associations and plant communities drawn from literature. Five alliances, with plant communities characterized by specific ecological features, have been discriminated: Sarcocornion alpini and Arthrocnemion glauci (lower marshes), Salicornion fruticosae (middle marshes), Inulion crithmoidis and Suaedion brevofoliae (upper marshes). In addition, during the field work, a population of Halocnemum strobilaceum (Arthrocnemo-Halocnemetum strobilacei), new record for the Apulia region, has been found.

scholarly journals Combined Use of Terrestrial Laser Scanning and UAV Photogrammetry in Mapping Alpine Terrain

2019 ◽  
Vol 11 (18) ◽  
pp. 2154 ◽  
Author(s):  
Ján Šašak ◽  
Michal Gallay ◽  
Ján Kaňuk ◽  
Jaroslav Hofierka ◽  
Jozef Minár
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Mutual Orientation ◽  
Close Range Photogrammetry ◽  
Combined Use ◽  
Wide Range ◽  
Close Range

Airborne and terrestrial laser scanning and close-range photogrammetry are frequently used for very high-resolution mapping of land surface. These techniques require a good strategy of mapping to provide full visibility of all areas otherwise the resulting data will contain areas with no data (data shadows). Especially, deglaciated rugged alpine terrain with abundant large boulders, vertical rock faces and polished roche-moutones surfaces complicated by poor accessibility for terrestrial mapping are still a challenge. In this paper, we present a novel methodological approach based on a combined use of terrestrial laser scanning (TLS) and close-range photogrammetry from an unmanned aerial vehicle (UAV) for generating a high-resolution point cloud and digital elevation model (DEM) of a complex alpine terrain. The approach is demonstrated using a small study area in the upper part of a deglaciated valley in the Tatry Mountains, Slovakia. The more accurate TLS point cloud was supplemented by the UAV point cloud in areas with insufficient TLS data coverage. The accuracy of the iterative closest point adjustment of the UAV and TLS point clouds was in the order of several centimeters but standard deviation of the mutual orientation of TLS scans was in the order of millimeters. The generated high-resolution DEM was compared to SRTM DEM, TanDEM-X and national DMR3 DEM products confirming an excellent applicability in a wide range of geomorphologic applications.

scholarly journals Exploring the contributions of vegetation and dune size to early dune development using unmanned aerial vehicle (UAV) imaging

2017 ◽  
Vol 14 (23) ◽  
pp. 5533-5549 ◽  
Author(s):  
Marinka E. B. van Puijenbroek ◽  
Corjan Nolet ◽  
Alma V. de Groot ◽  
Juha M. Suomalainen ◽  
Michel J. P. M. Riksen ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Vegetation Type ◽  
Grass Species ◽  
Surface Model ◽  
Maximum Height ◽  
Vegetation Density ◽  
Vegetation Height ◽  
Erosion Processes ◽  
Aerial Vehicle ◽  
Vegetation Characteristics

Abstract. Dune development along highly dynamic land–sea boundaries is the result of interaction between vegetation and dune size with sedimentation and erosion processes. Disentangling the contribution of vegetation characteristics from that of dune size would improve predictions of nebkha dune development under a changing climate, but has proven difficult due to the scarcity of spatially continuous monitoring data. This study explored the contributions of vegetation and dune size to dune development for locations differing in shelter from the sea. We monitored a natural nebkha dune field of 8 ha, along the coast of the island Texel, the Netherlands, for 1 year using an unmanned aerial vehicle (UAV) with camera. After constructing a digital surface model and orthomosaic we derived for each dune (1) vegetation characteristics (species composition, vegetation density, and maximum vegetation height), (2) dune size (dune volume, area, and maximum height), (3) degree of shelter (proximity to other nebkha dunes and the sheltering by the foredune). Changes in dune volume over summer and winter were related to vegetation, dune size and degree of shelter. We found that a positive change in dune volume (dune growth) was linearly related to initial dune volume over summer but not over winter. Big dunes accumulated more sand than small dunes due to their larger surface area. Exposed dunes increased more in volume (0.81 % per dune per week) than sheltered dunes (0.2 % per dune per week) over summer, while the opposite occurred over winter. Vegetation characteristics did not significantly affect dune growth in summer, but did significantly affect dune growth in winter. Over winter, dunes dominated by Ammophila arenaria, a grass species with high vegetation density throughout the year, increased more in volume than dunes dominated by Elytrigia juncea, a grass species with lower vegetation density (0.43 vs. 0.42 (m3 m−3) week−1). The effect of species was irrespective of dune size or distance to the sea. Our results show that dune growth in summer is mainly determined by dune size, whereas in winter dune growth was determined by vegetation type. In our study area the growth of exposed dunes was likely restricted by storm erosion, whereas growth of sheltered dunes was restricted by sand supply. Our results can be used to improve models predicting coastal dune development.

Data from: Modeling salt marsh vegetation height using Unoccupied Aircraft Systems and Structure from Motion

2020 ◽  
Author(s):  
Clara N. Bird ◽  
Justin T. Ridge ◽  
David W. Johnston ◽  
Kelly Dobroski ◽  
Alexandra E. DiGiacomo ◽  
...  
Keyword(s):  
Salt Marsh ◽  
Structure From Motion ◽  
Salt Marsh Vegetation ◽  
Marsh Vegetation ◽  
Vegetation Height ◽  
Aircraft Systems

scholarly journals AUTOMATIC GENERATION OF BUILDING MAPPING USING DIGITAL, VERTICAL AND AERIAL HIGH RESOLUTION PHOTOGRAPHS AND LIDAR POINT CLOUDS

2016 ◽  
Vol XLI-B7 ◽  
pp. 171-176 ◽  
Author(s):  
W. Barragán ◽  
A. Campos ◽  
G. Sanchez
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
Spectral Band ◽  
Point Clouds ◽  
Automatic Generation ◽  
Aerial Photographs ◽  
Band Combination ◽  
Segmentation Algorithms ◽  
Digital Processes ◽  
Overall Effectiveness

The objective of this research is automatic generation of buildings in the interest areas. This research was developed by using high resolution vertical aerial photographs and the LIDAR point cloud through radiometric and geometric digital processes. The research methodology usesknown building heights and various segmentation algorithms and spectral band combination. The overall effectiveness of the algorithm is 97.2% with the test data.

scholarly journals Changes in salt-marsh vegetation weakly affect top consumers of aquatic food webs

2020 ◽  
Author(s):  
Lafage Denis ◽  
Carpentier Alexandre ◽  
Sylvain Duhamel ◽  
Christine Dupuy ◽  
Eric Feunteun ◽  
...  
Keyword(s):  
Stable Isotopes ◽  
Salt Marsh ◽  
Salt Marshes ◽  
Vegetation Type ◽  
Site Effect ◽  
Salt Marsh Vegetation ◽  
Gut Content ◽  
Marsh Vegetation ◽  
Nitrogen Inputs

AbstractSalt marshes are under high, and increasing, anthropogenic pressures that have notably been reported to affect the diet of several fish species, probably resulting in nursery function alterations. Most of the previous studies in Europe were yet based on gut content analysis of fish, which can be considered a snapshot of immediate impacts of salt-marsh changes, and hardly of long-term effects of disturbances. In this study, we investigated the impact of vegetation type (resulting from both plant invasion and sheep grazing) by assessing trophic network (and especially fish diet and position) of different salt-marsh conditions. Replicated samples of basic sources (particular organic matter and microphytobenthos), dominant vegetation, potential aquatic and terrestrial prey and fish of 3 main species were taken during summer 2010 in two bays from Western France (Mont -Saint-Michel Bay and Seine Estuary) and analysed using C and N stable isotope compositions. All response variables tested (overall trophic organization, trophic niche and trophic position) provided consistent results, i.e. a dominant site effect and a weaker effect of vegetation type. Site effect was attributed to differences in anthropogenic Nitrogen inputs and tidal regime between the two bays, with more marine signatures associated with a higher frequency of flooding events. A second hypothesis is that E. acuta, which has recently totally replaced typical salt-marsh vegetation in Mont Saint-Michel Bay strongly impacted the nursery function. The trophic status of dominant fish species was unchanged by local salt-marsh vegetation, and considered consistent with their diet, i.e. high for predatory species (the sea bass Dicentrarchus labrax and the common goby Pomatoschistus microps) and lower for biofilm grazing species (the thinlip mullet Chelon ramada). This study finally highlights the relevance of stable isotopes analyses for assessing long-term and integrative effects of changes in vegetation resulting from human disturbances in salt marshes.HighlightsCross-ecosystem subsidies are of high functional importance, notably in salt marshesFish are vectors of exchanges, most European studies being based on their gut contentUsing stable isotopes we analysed the effect of surrounding vegetation on food websSurprisingly we found weak vegetation and strong site effects on all metricsNitrogen inputs, site accessibility and loss of nursery function can explain this factAbstract Figure

scholarly journals FAST PROBABILISTIC FUSION OF 3D POINT CLOUDS VIA OCCUPANCY GRIDS FOR SCENE CLASSIFICATION

2016 ◽  
Vol III-3 ◽  
pp. 325-332
Author(s):  
Andreas Kuhn ◽  
Hai Huang ◽  
Martin Drauschke ◽  
Helmut Mayer
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
State Of The Art ◽  
Point Clouds ◽  
Automatic Generation ◽  
Scene Classification ◽  
Semantic Classification ◽  
3D Point Clouds ◽  
Occupancy Grids ◽  
High Scalability

High resolution consumer cameras on Unmanned Aerial Vehicles (UAVs) allow for cheap acquisition of highly detailed images, e.g., of urban regions. Via image registration by means of Structure from Motion (SfM) and Multi View Stereo (MVS) the automatic generation of huge amounts of 3D points with a relative accuracy in the centimeter range is possible. Applications such as semantic classification have a need for accurate 3D point clouds, but do not benefit from an extremely high resolution/density. In this paper, we, therefore, propose a fast fusion of high resolution 3D point clouds based on occupancy grids. The result is used for semantic classification. In contrast to state-of-the-art classification methods, we accept a certain percentage of outliers, arguing that they can be considered in the classification process when a per point belief is determined in the fusion process. To this end, we employ an octree-based fusion which allows for the derivation of outlier probabilities. The probabilities give a belief for every 3D point, which is essential for the semantic classification to consider measurement noise. For an example point cloud with half a billion 3D points (cf. Figure 1), we show that our method can reduce runtime as well as improve classification accuracy and offers high scalability for large datasets.

scholarly journals Classification of Photogrammetric and Airborne LiDAR Point Clouds Using Machine Learning Algorithms

Drones ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 104
Author(s):  
Zaide Duran ◽  
Kubra Ozcan ◽  
Muhammed Enes Atik
Keyword(s):  
Machine Learning ◽  
Point Cloud ◽  
Point Clouds ◽  
Machine Learning Algorithms ◽  
Airborne Lidar ◽  
Aerial Photogrammetry ◽  
Feature Spaces ◽  
Wide Range ◽  
Extract Information

With the development of photogrammetry technologies, point clouds have found a wide range of use in academic and commercial areas. This situation has made it essential to extract information from point clouds. In particular, artificial intelligence applications have been used to extract information from point clouds to complex structures. Point cloud classification is also one of the leading areas where these applications are used. In this study, the classification of point clouds obtained by aerial photogrammetry and Light Detection and Ranging (LiDAR) technology belonging to the same region is performed by using machine learning. For this purpose, nine popular machine learning methods have been used. Geometric features obtained from point clouds were used for the feature spaces created for classification. Color information is also added to these in the photogrammetric point cloud. According to the LiDAR point cloud results, the highest overall accuracies were obtained as 0.96 with the Multilayer Perceptron (MLP) method. The lowest overall accuracies were obtained as 0.50 with the AdaBoost method. The method with the highest overall accuracy was achieved with the MLP (0.90) method. The lowest overall accuracy method is the GNB method with 0.25 overall accuracy.

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