Airborne LiDAR remote sensing and its applications

2012 ◽  
pp. 33-68 ◽  
Author(s):  
Keqi Zhang ◽  
Zheng Cui ◽  
Patricia Houle
Keyword(s):  
Remote Sensing ◽  
Airborne Lidar

scholarly journals Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

2021 ◽  
Vol 13 (3) ◽  
pp. 507
Author(s):  
Tasiyiwa Priscilla Muumbe ◽  
Jussi Baade ◽  
Jenia Singh ◽  
Christiane Schmullius ◽  
Christian Thau
Keyword(s):  
Remote Sensing ◽  
Vegetation Structure ◽  
Laser Scanning ◽  
Spatial Scales ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Parameter Extraction ◽  
Airborne Lidar ◽  
Special Focus ◽  
Vegetation Parameter

Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome.

scholarly journals Remote Sensing Is Changing Our View of the Coast: Insights from 40 Years of Monitoring at Narrabeen-Collaroy, Australia

2018 ◽  
Vol 10 (11) ◽  
pp. 1744 ◽  
Author(s):  
Kristen Splinter ◽  
Mitchell Harley ◽  
Ian Turner
Keyword(s):  
Remote Sensing ◽  
Data Collection ◽  
Temporal Resolution ◽  
Monitoring Program ◽  
Google Earth ◽  
Airborne Lidar ◽  
Data Collection Program ◽  
Insight Into ◽  
Collection Program

Narrabeen-Collaroy Beach, located on the Northern Beaches of Sydney along the Pacific coast of southeast Australia, is one of the longest continuously monitored beaches in the world. This paper provides an overview of the evolution and international scientific impact of this long-term beach monitoring program, from its humble beginnings over 40 years ago using the rod and tape measure Emery field survey method; to today, where the application of remote sensing data collection including drones, satellites and crowd-sourced smartphone images, are now core aspects of this continuing and much expanded monitoring effort. Commenced in 1976, surveying at this beach for the first 30 years focused on in-situ methods, whereby the growing database of monthly beach profile surveys informed the coastal science community about fundamental processes such as beach state evolution and the role of cross-shore and alongshore sediment transport in embayment morphodynamics. In the mid-2000s, continuous (hourly) video-based monitoring was the first application of routine remote sensing at the site, providing much greater spatial and temporal resolution over the traditional monthly surveys. This implementation of video as the first of a now rapidly expanding range of remote sensing tools and techniques also facilitated much wider access by the international research community to the continuing data collection program at Narrabeen-Collaroy. In the past decade the video-based data streams have formed the basis of deeper understanding into storm to multi-year response of the shoreline to changing wave conditions and also contributed to progress in the understanding of estuary entrance dynamics. More recently, ‘opportunistic’ remote sensing platforms such as surf cameras and smartphones have also been used for image-based shoreline data collection. Commencing in 2011, a significant new focus for the Narrabeen-Collaroy monitoring program shifted to include airborne lidar (and later Unmanned Aerial Vehicles (UAVs)), in an enhanced effort to quantify the morphological impacts of individual storm events, understand key drivers of erosion, and the placing of these observations within their broader regional context. A fixed continuous scanning lidar installed in 2014 again improved the spatial and temporal resolution of the remote-sensed data collection, providing new insight into swash dynamics and the often-overlooked processes of post-storm beach recovery. The use of satellite data that is now readily available to all coastal researchers via Google Earth Engine continues to expand the routine data collection program and provide key insight into multi-decadal shoreline variability. As new and expanding remote sensing technologies continue to emerge, a key lesson from the long-term monitoring at Narrabeen-Collaroy is the importance of a regular re-evaluation of what data is most needed to progress the science.

scholarly journals An investigation into remote sensing techniques and field observations for modeling of dynamic hydraulic roughness from riparian vegetation

2021 ◽  
Author(s):  
Smriti Chaulagain ◽  
Mark Stone ◽  
Daniel Dombroski ◽  
Tyler Gillihan ◽  
Li Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hydrodynamic Model ◽  
Riparian Vegetation ◽  
Airborne Lidar ◽  
Calibration Data ◽  
Local Flow ◽  
Hydraulic Roughness ◽  
Dynamic Roughness ◽  
Spatially Distributed ◽  
Vegetation Parameters

Riparian vegetation provides many noteworthy functions in river and floodplain systems including its influence on hydrodynamic processes. Traditional methods for predicting hydrodynamic characteristics in the presence of vegetation involve the application of static roughness ( n) values, which neglect changes in roughness due to local flow characteristics. The objectives of this study were to: (1) implement numerical routines for simulating dynamic hydraulic roughness ( n) in a two-dimensional (2D) hydrodynamic model; (2) evaluate the performance of two dynamic roughness approaches; and (3) compare vegetation parameters and hydrodynamic model results based on field-based and remote sensing acquisition methods. A coupled vegetation-hydraulic solver was developed for a 2D hydraulics model using two dynamic approaches, which required vegetation parameters to calculate spatially distributed, dynamic roughness coefficients. Vegetation parameters were determined by field survey and using airborne LiDAR data. Water surface elevations modeled using conventional and the proposed dynamic approaches produced similar profiles. The method demonstrates the suitability in modeling the system where there is no calibration data. Substantial spatial variations in both n and hydraulic parameters were observed when comparing the static and dynamic approaches. Thus, the method proposed here is beneficial for describing the hydraulic conditions for the area having huge variation of vegetation. The proposed methods have the potential to improve our ability to simulate the spatial and temporal heterogeneity of vegetated floodplain surfaces with an approach that is more physically-based and reproducible than conventional “look up” approaches. However, additional research is needed to quantify model performance with respect to spatially distributed flow properties and parameterization of vegetation characteristics.

Estimating local CH4 emissions in the Upper Silesian Coal Basin using inverse modelling

2021 ◽  
Author(s):  
Sebastian Wolff ◽  
Friedemann Reum ◽  
Christoph Kiemle ◽  
Gerhard Ehret ◽  
Mathieu Quatrevalet ◽  
...  
Keyword(s):  
Remote Sensing ◽  
A Priori ◽  
Point Sources ◽  
Airborne Lidar ◽  
Inverse Modelling ◽  
Emission Rates ◽  
Coal Basin ◽  
Upper Silesian Coal Basin ◽  
The Individual ◽  
Modelling Approach

<p>Methane (CH<sub>4</sub>) is the second most important anthropogenic greenhouse gas (GHG) with respect to radiative forcing. Since pre-industrial times, the globally averaged CH<sub>4</sub> concentration in the atmosphere has risen by a factor of 2.5. A large fraction of global anthropogenic CH<sub>4</sub> emissions originates from localized point sources, e.g. coal mine ventilation shafts. International treaties foresee GHG emission reductions, entailing independent monitoring and verification support capacities. Considering the spatially widespread distribution of point sources, remote sensing approaches are favourable, in order to enable rapid survey of larger areas. In this respect, active remote sensing by airborne lidar is promising, such as provided by the integrated-path differential-absorption lidar CHARM-F operated by DLR. Installed onboard the German research aircraft HALO, CHARM-F serves as a demonstrator for future satellite missions, e.g. MERLIN. CHARM-F simultaneously measures weighted vertical column mixing ratios of CO<sub>2</sub> and CH<sub>4</sub> below the aircraft. In spring 2018, during the CoMet field campaign, measurements were taken in the Upper Silesian Coal Basin (USCB) in Poland. The USCB is considered to be a European hotspot of CH<sub>4</sub> emissions, covering an area of approximately 50 km × 50 km. Due to the high number of coal mines and density of ventilation shafts in the USCB, individual CH<sub>4</sub> exhaust plumes can overlap. This makes simple approaches to determine the emission rates of single shafts, i.e. the cross-sectional flux method, difficult. Therefore, we use an inverse modelling approach to obtain an estimate of the individual emission rates. Specifically, we employ the Weather Research and Forecast Model (WRF) coupled to the CarbonTracker Data Assimilation Shell (CTDAS), an Ensemble Kalman Filter. CTDAS-WRF propagates an ensemble realization of the a priori CH<sub>4</sub> emissions forward in space and time, samples the simulated CH<sub>4</sub> concentrations along the measurement’s flight path, and scales the a priori emission rates to optimally fit the measured values, while remaining tied to the prior. Hereby, we obtain a regularized a posteriori best emission estimate for the individual ventilation shafts. Here, we report on the results of this inverse modelling approach, including individual and aggregated emission estimates, their uncertainties, and to which extent the data are able to constrain individual emitters independently.</p>

scholarly journals Airborne Hyperspectral Imaging for Submerged Archaeological Mapping in Shallow Water Environments

2019 ◽  
Vol 11 (19) ◽  
pp. 2237 ◽  
Author(s):  
Alexandre Guyot ◽  
Marc Lennon ◽  
Nicolas Thomas ◽  
Simon Gueguen ◽  
Tristan Petit ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Shallow Water ◽  
Water Column ◽  
Sea Level ◽  
Hyperspectral Imagery ◽  
Airborne Lidar ◽  
Radiative Transfer Model ◽  
Invasive Technique ◽  
Transfer Model ◽  
Water Bottom

Nearshore areas around the world contain a wide variety of archeological structures, including prehistoric remains submerged by sea level rise during the Holocene glacial retreat. While natural processes, such as erosion, rising sea level, and exceptional climatic events have always threatened the integrity of this submerged cultural heritage, the importance of protecting them is becoming increasingly critical with the expanding effects of global climate change and human activities. Aerial archaeology, as a non-invasive technique, contributes greatly to documentation of archaeological remains. In an underwater context, the difficulty of crossing the water column to reach the bottom and its potential archaeological information usually requires active remote-sensing technologies such as airborne LiDAR bathymetry or ship-borne acoustic soundings. More recently, airborne hyperspectral passive sensors have shown potential for accessing water-bottom information in shallow water environments. While hyperspectral imagery has been assessed in terrestrial continental archaeological contexts, this study brings new perspectives for documenting submerged archaeological structures using airborne hyperspectral remote sensing. Airborne hyperspectral data were recorded in the Visible Near Infra-Red (VNIR) spectral range (400–1000 nm) over the submerged megalithic site of Er Lannic (Morbihan, France). The method used to process these data included (i) visualization of submerged anomalous features using a minimum noise fraction transform, (ii) automatic detection of these features using Isolation Forest and the Reed–Xiaoli detector and (iii) morphological and spectral analysis of archaeological structures from water-depth and water-bottom reflectance derived from the inversion of a radiative transfer model of the water column. The results, compared to archaeological reference data collected from in-situ archaeological surveys, showed for the first time the potential of airborne hyperspectral imagery for archaeological mapping in complex shallow water environments.

scholarly journals Geomorphological evolution of landslides near an active normal fault in northern Taiwan, as revealed by lidar and unmanned aircraft system data

2018 ◽  
Vol 18 (3) ◽  
pp. 709-727 ◽  
Author(s):  
Kuo-Jen Chang ◽  
Yu-Chang Chan ◽  
Rou-Fei Chen ◽  
Yu-Chung Hsieh
Keyword(s):  
Remote Sensing ◽  
Normal Fault ◽  
Unmanned Aircraft ◽  
Airborne Lidar ◽  
Reconstruction Method ◽  
Remote Sensing Techniques ◽  
Aircraft System ◽  
Geomorphological Evolution ◽  
Northern Taiwan ◽  
Landslide Morphology

Abstract. Several remote sensing techniques, namely traditional aerial photographs, an unmanned aircraft system (UAS), and airborne lidar, were used in this study to decipher the morphological features of obscure landslides in volcanic regions and how the observed features may be used for understanding landslide occurrence and potential hazard. A morphological reconstruction method was proposed to assess landslide morphology based on the dome-shaped topography of the volcanic edifice and the nature of its morphological evolution. Two large-scale landslides in the Tatun volcano group in northern Taiwan were targeted to more accurately characterize the landslide morphology through airborne lidar and UAS-derived digital terrain models and images. With the proposed reconstruction method, the depleted volume of the two landslides was estimated to be at least 820 ± 20  ×  106 m3. Normal faulting in the region likely played a role in triggering the two landslides, because there are extensive geological and historical records of an active normal fault in this region. The subsequent geomorphological evolution of the two landslides is thus inferred to account for the observed morphological and tectonic features that are indicative of resulting in large and life-threatening landslides, as characterized using the recent remote sensing techniques.

Numerical modeling of mesospheric mountain wave propagation observed in Southern Argentina during the SOUTHTRAC campaign

2020 ◽  
Author(s):  
Tyler Mixa ◽  
Andreas Dörnbrack ◽  
Bernd Kaifler ◽  
Markus Rapp
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Numerical Models ◽  
Airborne Lidar ◽  
Tierra Del Fuego ◽  
Polar Night ◽  
Research Aircraft ◽  
Complex Propagation ◽  
The Antarctic

<p>We present numerical simulations of a deep orographic gravity wave (GW) event observed by the ALIMA airborne lidar on 11-12 September 2019 over Southern Argentina. The measurements are taken from the 2019 SOUTHTRAC Campaign, employing a comprehensive suite of remote sensing and in-situ instruments onboard the HALO research aircraft to study the stratospheric GW hotspot over Tierra del Fuego and the Antarctic Peninsula. Wind conditions on 11-12 September exhibit local and large-scale directional shear from the ground to the polar night jet, creating a complex propagation environment supporting multiple orientations of GW propagation and strong potential for local GW breaking and secondary GW generation. Using high resolution numerical models, we simulate the 3D evolution of the orographic GW field to analyze<span> the remote sensing and in-situ measurements from the event.</span></p>

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