scholarly journals Monitoring Dynamic Braided River Habitats: Applicability and Efficacy of Aerial Photogrammetry from Manned Aircraft versus Unmanned Aerial Systems

Drones ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 39
Author(s):  
M Saif I. Khan ◽  
Ralf Ohlemüller ◽  
Richard F. Maloney ◽  
Philip J. Seddon
Keyword(s):  
Unmanned Aerial Systems ◽  
Data Envelopment ◽  
Image Capture ◽  
Research Personnel ◽  
Frontier Analysis ◽  
Braided Rivers ◽  
Aerial Photogrammetry ◽  
Efficiency Measures ◽  
Efficacy Assessment ◽  
Aerial Systems

Despite growing interest in using lightweight unmanned aerial systems (UASs) for ecological research and conservation, review of the operational aspects of these evolving technologies is limited in the scientific literature. To derive an objective framework for choosing among technologies we calculated efficiency measures and conducted a data envelopment productivity frontier analysis (DEA) to compare the efficacy of using manned aircraft (Cessna with Aviatrix triggered image capture using a 50 mm lens) and UAS (Mavic Pro 2) for photogrammetric monitoring of restoration efforts in dynamic braided rivers in Southern New Zealand. Efficacy assessment was based on the technological, logistical, administrative, and economic requirements of pre (planning), peri (image acquiring) and post (image processing) phases. The results reveal that the technological and logistic aspects of UASs were more efficient than manned aircraft flights. Administratively, the first deployment of UASs is less efficient but was very flexible for subsequent deployment. Manned aircraft flights were more productive in terms of the number of acquired images, but the ground resolution of those images was lower compared with those from UASs. Frontier analysis confirmed that UASs would be economical for regular monitoring of habitats—and even more so if research personnel are trained to fly the UASs.

A comparative approach of stochastic frontier analysis and data envelopment analysis estimators: evidence from banking system

2020 ◽  
Vol 47 (7) ◽  
pp. 1787-1810
Author(s):  
Kekoura Sakouvogui
Keyword(s):  
Data Envelopment Analysis ◽  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Data Envelopment ◽  
Content Type ◽  
Frontier Analysis ◽  
Efficiency Measures ◽  
Clustering Approach ◽  
Over Time

PurposeThe consistency of stochastic frontier analysis (SFA) and data envelopment analysis (DEA) cost efficiency measures using a sample of 650 commercial and domestic banks in the United States is investigated based on cluster analysis while accounting for the yearly variation in banks.Design/methodology/approachDue to the importance of efficiency measures for policy and managerial decision-making, the cost efficiency measures of SFA and DEA estimators are examined according to four criteria: levels, rankings, stability over time and stability over clustering groups. In this paper, we present two clustering methods, Gap Statistic and Dindex, that involve SFA and DEA cost efficiency measures. The clustering approach creates homogeneous groups of banks offering a similar mix of efficiency levels. Hence, each evaluated bank knows the cluster to which it belongs. Furthermore, this paper provides nonparametric statistical tests of SFA and DEA cost efficiency measures estimated with and without a clustering approach.FindingsThe results suggest that the clustering approach plays a considerable role in the rankings of US banks. Furthermore, the average SFA and DEA cost efficiency measures over time of the homogeneous US banks are substantially higher than those of the heterogeneous US banks.Originality/valueThis research is the first to provide comparative efficiency measures needed for desirable policy conclusions of heterogeneous and homogeneous US banks.

scholarly journals Assessing the Ability of Image Based Point Clouds Captured from a UAV to Measure the Terrain in the Presence of Canopy Cover

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 284 ◽  
Author(s):  
Luke Wallace ◽  
Chris Bellman ◽  
Bryan Hally ◽  
Jaime Hernandez ◽  
Simon Jones ◽  
...  
Keyword(s):  
Ground Surface ◽  
Canopy Cover ◽  
Weather Conditions ◽  
Point Clouds ◽  
Unmanned Aerial Systems ◽  
Image Capture ◽  
Terrain Model ◽  
Processing Strategies ◽  
Aerial Systems

Point clouds captured from Unmanned Aerial Systems are increasingly relied upon to provide information describing the structure of forests. The quality of the information derived from these point clouds is dependent on a range of variables, including the type and structure of the forest, weather conditions and flying parameters. A key requirement to achieve accurate estimates of height based metrics describing forest structure is a source of ground information. This study explores the availability and reliability of ground surface points available within point clouds captured in six forests of different structure (canopy cover and height), using three image capture and processing strategies, consisting of nadir, oblique and composite nadir/oblique image networks. The ground information was extracted through manual segmentation of the point clouds as well as through the use of two commonly used ground filters, LAStools lasground and the Cloth Simulation Filter. The outcomes of these strategies were assessed against ground control captured with a Total Station. Results indicate that a small increase in the number of ground points captured (between 0 and 5% of a 10 m radius plot) can be achieved through the use of a composite image network. In the case of manually identified ground points, this reduced the root mean square error (RMSE) error of the terrain model by between 1 and 11 cm, with greater reductions seen in plots with high canopy cover. The ground filters trialled were not able to exploit the extra information in the point clouds and inconsistent results in terrain RMSE were obtained across the various plots and imaging network configurations. The use of a composite network also provided greater penetration into the canopy, which is likely to improve the representation of mid-canopy elements.

scholarly journals Evaluation of Ground Surface Models Derived from Unmanned Aerial Systems with Digital Aerial Photogrammetry in a Disturbed Conifer Forest

2019 ◽  
Vol 11 (1) ◽  
pp. 84 ◽  
Author(s):  
Alexander Graham ◽  
Nicholas Coops ◽  
Michael Wilcox ◽  
Andrew Plowright
Keyword(s):  
Canopy Cover ◽  
Point Clouds ◽  
Unmanned Aerial Systems ◽  
Optimal Parameters ◽  
Conifer Forest ◽  
Terrain Modeling ◽  
Ground Truth Data ◽  
Aerial Photogrammetry ◽  
Terrain Slope ◽  
Aerial Systems

Detailed vertical forest structure information can be remotely sensed by combining technologies of unmanned aerial systems (UAS) and digital aerial photogrammetry (DAP). A key limitation in the application of DAP methods, however, is the inability to produce accurate digital elevation models (DEM) in areas of dense vegetation. This study investigates the terrain modeling potential of UAS-DAP methods within a temperate conifer forest in British Columbia, Canada. UAS-acquired images were photogrammetrically processed to produce high-resolution DAP point clouds. To evaluate the terrain modeling ability of DAP, first, a sensitivity analysis was conducted to estimate optimal parameters of three ground-point classification algorithms designed for airborne laser scanning (ALS). Algorithms tested include progressive triangulated irregular network (TIN) densification (PTD), hierarchical robust interpolation (HRI) and simple progressive morphological filtering (SMRF). Points were classified as ground from the ALS and served as ground-truth data to which UAS-DAP derived DEMs were compared. The proportion of area with root mean square error (RMSE) <1.5 m were 56.5%, 51.6% and 52.3% for the PTD, HRI and SMRF methods respectively. To assess the influence of terrain slope and canopy cover, error values of DAP-DEMs produced using optimal parameters were compared to stratified classes of canopy cover and slope generated from ALS point clouds. Results indicate that canopy cover was approximately three times more influential on RMSE than terrain slope.

scholarly journals Validating UAS-Based Photogrammetry with Traditional Topographic Methods for Surveying Dune Ecosystems in the Spanish Mediterranean Coast

2019 ◽  
Vol 7 (9) ◽  
pp. 297 ◽  
Author(s):  
Luis Bañón ◽  
José Ignacio Pagán ◽  
Isabel López ◽  
Carlos Banon ◽  
Luis Aragonés
Keyword(s):  
Low Cost ◽  
Temporal Frequency ◽  
Satellite System ◽  
Mean Value ◽  
Mediterranean Coast ◽  
Unmanned Aerial Systems ◽  
Aerial Photogrammetry ◽  
The One ◽  
Global Navigation Satellite ◽  
Aerial Systems

In the past few years, unmanned aerial systems (UAS) have achieved great popularity for civil uses. One of the present main uses of these devices is low-cost aerial photogrammetry, being especially useful in coastal environments. In this work, a high-resolution 3D model of a beach section in Guardamar del Segura (Spain) has been produced by employing a low maximum takeoff mass (MTOM) UAS, in combination with the use of structure-from-motion (SfM) techniques. An unprecedented extensive global navigation satellite system (GNSS) survey was simultaneously carried out to statistically validate the model by employing 1238 control points for that purpose. The results show good accuracy, obtaining a vertical root mean square error (RMSE) mean value of 0.121 m and a high point density, close to 30 pt/m2, with similar or even higher quality than most coastal surveys performed with classical techniques. UAS technology permits the acquisition of topographic data with low time-consuming surveys at a high temporal frequency. Coastal managers can implement this methodology into their workflow to study the evolution of complex, highly anthropized dune-beach systems such as the one presented in this study, obtaining more accurate surveys at lower costs.

Assessing the status of forest regeneration using digital aerial photogrammetry and unmanned aerial systems

2017 ◽  
Vol 39 (15-16) ◽  
pp. 5246-5264 ◽  
Author(s):  
Tristan R.H Goodbody ◽  
Nicholas C Coops ◽  
Txomin Hermosilla ◽  
Piotr Tompalski ◽  
Patrick Crawford
Keyword(s):  
Forest Regeneration ◽  
Unmanned Aerial Systems ◽  
Aerial Photogrammetry ◽  
The Status ◽  
Aerial Systems

scholarly journals A Two-stage Panel Data Envelopment Analysis Models: Wallace-Hussain, Amemiya and Swamy-Arora

2020 ◽  
Author(s):  
Saleem Shaik
Keyword(s):  
Data Envelopment Analysis ◽  
Panel Data ◽  
Stochastic Frontier Analysis ◽  
Random Effect ◽  
Data Envelopment ◽  
Efficiency Measure ◽  
Two Stage ◽  
Frontier Analysis ◽  
Efficiency Measures ◽  
Dea Models

Abstract This research presents two-stage panel data envelopment analysis (DEA) models for the estimation of efficiency measures. In the first stage, the variances of normal errors, v used in the transformation of the variables are recovered from pooled (Wallace-Hussain in 1969); within (Amemiya in 1971); or within, cross-sectional and time-series (Swamy-Arora in 1972) stochastic frontier analysis (SFA) models. The second stage involves estimating panel DEA efficiency measures using transformed data based on alternative two-way random effect econometric estimators in the first stage. The alternative panel DEA models might over- or under-estimate the pooled DEA model estimated efficiency measure due to the non-existence or existence of the spatial and temporal variations. An empirical application to 48 U.S. states from 1960 to 2004 suggests differences in the efficiency measure estimated by the pooled and panel DEA models. In addition, the efficiency measure estimated by the Swamy-Arora panel estimator is statistically different compared to the Wallace-Hussain and Amemiya panel estimator.

LIGHTER-THAN-AIR (LTA) UNMANNED AERIAL SYSTEM (UAS) CARRIER CONCEPT FOR SURVAILLANCE AND DISASTER MANAGEMENT

2019 ◽  
Vol 3 ◽  
pp. 1255
Author(s):  
Ahmad Salahuddin Mohd Harithuddin ◽  
Mohd Fazri Sedan ◽  
Syaril Azrad Md Ali ◽  
Shattri Mansor ◽  
Hamid Reza Jifroudi ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Disaster Management ◽  
Unmanned Aerial Systems ◽  
Unmanned Aerial System ◽  
Border Control ◽  
Aerial Vehicles ◽  
Operational Safety ◽  
In Situ Methods ◽  
Aerial Systems

Unmanned aerial systems (UAS) has many advantages in the fields of SURVAILLANCE and disaster management compared to space-borne observation, manned missions and in situ methods. The reasons include cost effectiveness, operational safety, and mission efficiency. This has in turn underlined the importance of UAS technology and highlighted a growing need in a more robust and efficient unmanned aerial vehicles to serve specific needs in SURVAILLANCE and disaster management. This paper first gives an overview on the framework for SURVAILLANCE particularly in applications of border control and disaster management and lists several phases of SURVAILLANCE and service descriptions. Based on this overview and SURVAILLANCE phases descriptions, we show the areas and services in which UAS can have significant advantage over traditional methods.

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