Unmanned aerial vehicles as innovative remote sensing platforms for high-resolution infrared imagery to support restoration monitoring in cut-over bogs

2013 ◽  
Vol 16 (3) ◽  
pp. 509-517 ◽  
Author(s):  
Christian Knoth ◽  
Birte Klein ◽  
Torsten Prinz ◽  
Till Kleinebecker
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Unmanned Aerial Vehicles ◽  
Infrared Imagery ◽  
Aerial Vehicles ◽  
Sensing Platforms ◽  
Restoration Monitoring

scholarly journals Drone brings new advance of geological mapping in Mongolia: Opportunities and challenges

2018 ◽  
pp. 53-57
Author(s):  
Otgonbayar Dandar ◽  
Atsushi Okamoto ◽  
Masaoki Uno ◽  
Undarmaa Batsaikhan ◽  
Burenjargal Ulziiburen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
High Altitude ◽  
Unmanned Aerial Vehicles ◽  
Geological Mapping ◽  
Field Techniques ◽  
Aerial Vehicles ◽  
Technological Developments ◽  
Geological Map ◽  
Remote Sensing Methods

Unmanned aerial vehicles (UAVs) or drones have revolutionized scientific research in multiple fields. Drones provide us multiple advantages over conventional geological mapping or high-altitude remote sensing methods, in which they allow us to acquire data more rapidly of inaccessible or risky outcrops, and can connect the spatial scale gap in mapping between manual field techniques and airborne, high-altitude remote sensing methods. Despite the decreased cost and technological developments of platforms, sensors and software, the use of drones for geological mapping in Mongolia has not yet been utilized. In this study, we present using of drone in two areas: the Chandman area in which eclogite is exposed and the Naran massif of the Khantaishir ophiolite in the Altai area. Drone yields images with high resolution that is reliable to use and reveals that it is possible to make better formulation of geological mapping. Our suggestion is that (1) Mongolian geoscientists are encouraged to add drones to their geologic toolboxes and (2) drone could open new advance of geological mapping in Mongolia in which geological map will be created in more effective and more detailed way combined with conventional geological survey on ground.

Using unmanned aerial vehicles for high-resolution remote sensing to map invasive Phragmites australis in coastal wetlands

2016 ◽  
Vol 38 (8-10) ◽  
pp. 2199-2217 ◽  
Author(s):  
Sathishkumar Samiappan ◽  
Gray Turnage ◽  
Lee Hathcock ◽  
Luan Casagrande ◽  
Preston Stinson ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Unmanned Aerial Vehicles ◽  
Phragmites Australis ◽  
Coastal Wetlands ◽  
Aerial Vehicles

scholarly journals Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects

2020 ◽  
Vol 12 (6) ◽  
pp. 948 ◽  
Author(s):  
Clare Gaffey ◽  
Anshuman Bhardwaj
Keyword(s):  
Remote Sensing ◽  
Data Acquisition ◽  
Unmanned Aerial Vehicles ◽  
Regional Climate ◽  
Airborne Remote Sensing ◽  
Aerial Vehicles ◽  
Holistic Review ◽  
Sensing Platform ◽  
Sensing Platforms ◽  
Data Acquisition And Processing

Owing to usual logistic hardships related to field-based cryospheric research, remote sensing has played a significant role in understanding the frozen components of the Earth system. Conventional spaceborne or airborne remote sensing platforms have their own merits and limitations. Unmanned aerial vehicles (UAVs) have emerged as a viable and inexpensive option for studying the cryospheric components at unprecedented spatiotemporal resolutions. UAVs are adaptable to various cryospheric research needs in terms of providing flexibility with data acquisition windows, revisits, data/sensor types (multispectral, hyperspectral, microwave, thermal/night imaging, Light Detection and Ranging (LiDAR), and photogrammetric stereos), viewing angles, flying altitudes, and overlap dimensions. Thus, UAVs have the potential to act as a bridging remote sensing platform between spatially discrete in situ observations and spatially continuous but coarser and costlier spaceborne or conventional airborne remote sensing. In recent years, a number of studies using UAVs for cryospheric research have been published. However, a holistic review discussing the methodological advancements, hardware and software improvements, results, and future prospects of such cryospheric studies is completely missing. In the present scenario of rapidly changing global and regional climate, studying cryospheric changes using UAVs is bound to gain further momentum and future studies will benefit from a balanced review on this topic. Our review covers the most recent applications of UAVs within glaciology, snow, permafrost, and polar research to support the continued development of high-resolution investigations of cryosphere. We also analyze the UAV and sensor hardware, and data acquisition and processing software in terms of popularity for cryospheric applications and revisit the existing UAV flying regulations in cold regions of the world. The recent usage of UAVs outlined in 103 case studies provide expertise that future investigators should base decisions on.

A Review of Unmanned Aerial Vehicles, Citizen Science, and Interferometry Remote Sensing in Landslide Hazards

2017 ◽  
pp. 469-491 ◽  
Author(s):  
Panagiotis Partsinevelos ◽  
Zacharias Agioutantis ◽  
Achilleas Tripolitsiotis ◽  
Nathaniel Schaefer
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicles ◽  
Citizen Science ◽  
Aerial Vehicles ◽  
Landslide Hazards

scholarly journals PERSPECTIVE OF USE OF REMOTE SENSING OF THE EARTH AND UNMANNED AERIAL VEHICLES IN THE AGRICULTURE OF TATARSTAN

2018 ◽  
Vol 12 (4) ◽  
pp. 17-19 ◽  
Author(s):  
Салават Сулейманов ◽  
Salavat Suleymanov ◽  
Николай Логинов ◽  
Nikolay Loginov
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicles ◽  
Remote Sensing Data ◽  
Soil Characteristics ◽  
Sensing Data ◽  
Natural Processes ◽  
Aerial Vehicles ◽  
The Earth ◽  
Constant Change ◽  
Vast Territory

The vast territory of Russia, occupied by agricultural lands, is difficult to control due to the lack of an undeveloped network of operational monitoring points, ground stations, including meteorological stations, lack of aviation support due to the high cost of maintaining staff, etc. In addition, due to various types of natural processes, there is a constant change in the boundaries of acreage, soil characteristics and vegetation conditions in different fields and from site to site. Abroad, the above mentioned problems are successfully solved due to the application of remote sensing data (RSD) of the Earth, obtained with the help of unmanned aerial vehicles (UAVs). The proceedings, obtained (UAV), can help both to solve complex tasks of managing agricultural territories, and in highly specialized areas.

Forest Firefighting Monitoring System Based on UAV Team and Remote Sensing

2019 ◽  
pp. 220-241
Author(s):  
Maryna Zharikova ◽  
Vladimir Sherstjuk
Keyword(s):  
Remote Sensing ◽  
Data Integration ◽  
Unmanned Aerial Vehicles ◽  
Monitoring System ◽  
Fire Response ◽  
Ground Support ◽  
Aerial Vehicles ◽  
Remote Sensing Techniques ◽  
Fire Spreading ◽  
Multi Uav

In this chapter, the authors propose an approach to using a heterogeneous team of unmanned aerial vehicles and remote sensing techniques to perform tactical forest firefighting operations. The authors present the three-level architecture of the multi-UAV-based forest firefighting monitoring system; features of patrolling, confirming, and monitoring missions; as well as functions of UAV in such missions. The authors consider an infrastructure for the UAV ground support and equipment used for the UAVs control. The method of the data integration into a fire-spreading model in a real-time DSS for the forest fire response is proposed. The proposed approach has been tested with the multi-UAV team that included three drones for the patrol missions, one helicopter for the confirmation mission, and one octocopter for the monitoring mission. The performance of such multi-UAV team has been studied in the laboratory conditions. The result of the experiment has shown that the proposed approach provides required credibility and efficiency of fire prediction and response.

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