scholarly journals A new approach to study terrestrial yardang geomorphology based on high-resolution data acquired by unmanned aerial vehicles (UAVs): A showcase of whaleback yardangs in Qaidam Basin, NW China

2018 ◽  
Vol 2 (5) ◽  
pp. 398-405 ◽  
Author(s):  
Xiao Xiao ◽  
◽  
Jiang Wang ◽  
Jun Huang ◽  
Binlong Ye
Author(s):  
L. Pádua ◽  
T. Adão ◽  
N. Guimarães ◽  
A. Sousa ◽  
E. Peres ◽  
...  

<p><strong>Abstract.</strong> In recent years unmanned aerial vehicles (UAVs) have been used in several applications and research studies related to environmental monitoring. The works performed have demonstrated the suitability of UAVs to be employed in different scenarios, taking advantage of its capacity to acquire high-resolution data from different sensing payloads, in a timely and flexible manner. In forestry ecosystems, UAVs can be used with accuracies comparable with traditional methods to retrieve different forest properties, to monitor forest disturbances and to support disaster monitoring in fire and post-fire scenarios. In this study an area recently affected by a wildfire was surveyed using two UAVs to acquire multi-spectral data and RGB imagery at different resolutions. By analysing the surveyed area, it was possible to detect trees, that were able to survive to the fire. By comparing the ground-truth data and the measurements estimated from the UAV-imagery, it was found a positive correlation between burned height and a high correlation for tree height. The mean NDVI value was extracted used to create a three classes map. Higher NDVI values were mostly located in trees that survived that were not/barely affected by the fire. The results achieved by this study reiterate the effectiveness of UAVs to be used as a timely, efficient and cost-effective data acquisition tool, helping for forestry management planning and for monitoring forest rehabilitation in post-fire scenarios.</p>


2020 ◽  
Vol 12 (11) ◽  
pp. 1711 ◽  
Author(s):  
Efstratios Karantanellis ◽  
Vassilis Marinos ◽  
Emmanuel Vassilakis ◽  
Basile Christaras

The increased development of computer vision technology combined with the increased availability of innovative platforms with ultra-high-resolution sensors, has generated new opportunities and fields for investigation in the engineering geology domain in general and landslide identification and characterization in particular. During the last decade, the so-called Unmanned Aerial Vehicles (UAVs) have been evaluated for diverse applications such as 3D terrain analysis, slope stability, mass movement hazard and risk management. Their advantages of detailed data acquisition at a low cost and effective performance identifies them as leading platforms for site-specific 3D modelling. In this study, the proposed methodology has been developed based on Object-Based Image Analysis (OBIA) and fusion of multivariate data resulted from UAV photogrammetry processing in order to take full advantage of the produced data. Two landslide case studies within the territory of Greece, with different geological and geomorphological characteristics, have been investigated in order to assess the developed landslide detection and characterization algorithm performance in distinct scenarios. The methodology outputs demonstrate the potential for an accurate characterization of individual landslide objects within this natural process based on ultra high-resolution data from close range photogrammetry and OBIA techniques for landslide conceptualization. This proposed study shows that UAV-based landslide modelling on the specific case sites provides a detailed characterization of local scale events in an automated sense with high adaptability on the specific case site.


EDIS ◽  
2019 ◽  
Vol 2019 (6) ◽  
pp. 6
Author(s):  
Sri Charan Kakarla ◽  
Yiannis Ampatzidis

Remote sensing applications for agriculture often require periodically collected high-resolution data, which are difficult to obtain by manned flights or satellite imagery. This 6-page document provides guidance on the use of post-processing software to visualize data collected by unmanned aerial vehicles (UAVs) for agriculturalapplications. It provides step-by-step instructions for using the data collected from a UAV flight to create several types of maps and indices. Written by Sri Charan Kakarla and Yiannis Ampatzidis, and published by the UF/IFAS Department of Agricultural and Biological Engineering, October 2019.


2009 ◽  
Vol 474 (1-2) ◽  
pp. 271-284 ◽  
Author(s):  
L. Tosi ◽  
P. Teatini ◽  
L. Carbognin ◽  
G. Brancolini

2021 ◽  
Author(s):  
Kyalo Richard ◽  
Elfatih M. Abdel-Rahman ◽  
Sevgan Subramanian ◽  
Johnson O. Nyasani ◽  
Michael Thiel ◽  
...  

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