scholarly journals NEW INITIATIVE OF UNMANNED AERIAL VEHICLE (UAV) EMERGING TECHNOLOGY APPLICATIONS IN NORTH EAST FOR CAPACITY BUILDING AND OUTREACH ACTIVITIES OF NORTH EASTERN SPACE APPLICATIONS CENTRE

2018 ◽  
Vol IV-5 ◽  
pp. 421-424
Author(s):  
P. L. N. Raju ◽  
C. Gupta ◽  
V. Saikhom ◽  
S. Pandit ◽  
A. Qadir ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Capacity Building ◽  
Unmanned Aerial Vehicle ◽  
Training Programs ◽  
Space Applications ◽  
North East ◽  
Sensing Applications ◽  
North Eastern ◽  
Aerial Vehicle ◽  
Remote Sensing Applications

<p><strong>Abstract.</strong> Unmanned Aerial Vehicle (UAV) technology is revolutionizing and acting as an alternative for many of remote sensing applications, particularly for very high resolution satellite requirements, considering easy of flying in the areas of persistent cloud cover like North East. According to top market reports, UAV business is growing at very fast rate. It is valued at USD 18.14 Billion in 2017 and is projected to reach USD 52.30 Billion by 2025, at a CAGR of 14.15% from 2018 to 2025.</p><p>North Eastern Space Applications Centre, Umiam, Shillong, Meghalaya, which is responsible for promoting space technology tools for governance and development activities; has taken up a lead role in initiating use of Unmanned Aerial Vehicle for large number of applications such as natural resources management, infrastructure development, disaster response and rescue, project monitoring, research and development etc. Capacity building, training and outreach are important activities taken up by NESAC for promoting use of UAV remote sensing at central/state/academic/research institutions and individual level.</p><p> As part of capacity building, NESAC has successfully organized two 2 weeks training program for UAV Remote sensing &amp; Applications for the participants all over the country. NESAC has also organised 1 week training programs for officials from State Remote Sensing Centres of North Eastern Region and North Eastern Council. More than 100 participants have been trained from different part of the country. The focus of the training was to include all aspects of UAV Remote Sensing applications. The details of course curriculum are: basic concepts of UAV, building of UAVs, UAV flight simulation, flight planning, UAV data processing, generation of DSM/DTM/Orthomosaic, use of UAV data for different applications in the field of Agriculture, Disaster management, Forestry, Infrastructure planning, construction monitoring etc. Pilot project is also incorporated as part of the training. Apart from training programs at NESAC, large numbers of application projects (&amp;gt;<span class="thinspace"></span>60<span class="thinspace"></span>nos.) have been successfully completed. Outreach activities are also carried out which includes exhibiting UAVs at seminars, demonstration to large no. of students, showcasing UAV capabilities at disaster drills carried out by State Disaster Management Authority (SDMA) etc. The new initiatives of UAV convinced all concerned at taking up UAV RS applications for governance and developmental activities. The full paper will discuss all the aspects of UAV technology and applications.</p>

scholarly journals Evaluation of Regression Analysis and Neural Networks to Predict Total Suspended Solids in Water Bodies from Unmanned Aerial Vehicle Images

2019 ◽  
Vol 11 (9) ◽  
pp. 2580 ◽  
Author(s):  
Tainá T. Guimarães ◽  
Maurício R. Veronez ◽  
Emilie C. Koste ◽  
Eniuce M. Souza ◽  
Diego Brum ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Regression Analysis ◽  
Unmanned Aerial Vehicle ◽  
Suspended Solids ◽  
Total Suspended Solids ◽  
Water Bodies ◽  
Sampling Point ◽  
Sensing Applications ◽  
Aerial Vehicle

The concentration of suspended solids in water is one of the quality parameters that can be recovered using remote sensing data. This paper investigates the data obtained using a sensor coupled to an unmanned aerial vehicle (UAV) in order to estimate the concentration of suspended solids in a lake in southern Brazil based on the relation of spectral images and limnological data. The water samples underwent laboratory analysis to determine the concentration of total suspended solids (TSS). The images obtained using the UAV were orthorectified and georeferenced so that the values referring to the near, green, and blue infrared channels were collected at each sampling point to relate with the laboratory data. The prediction of the TSS concentration was performed using regression analysis and artificial neural networks. The obtained results were important for two main reasons. First, although regression methods have been used in remote sensing applications, they may not be adequate to capture the linear and/or non-linear relationships of interest. Second, results show that the integration of UAV in the mapping of water bodies together with the application of neural networks in the data analysis is a promising approach to predict TSS as well as their temporal and spatial variations.

scholarly journals Social Network and Bibliometric Analysis of Unmanned Aerial Vehicle Remote Sensing Applications from 2010 to 2021

2021 ◽  
Vol 13 (15) ◽  
pp. 2912
Author(s):  
Jingrui Wang ◽  
Shuqing Wang ◽  
Dongxiao Zou ◽  
Huimin Chen ◽  
Run Zhong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Social Network ◽  
Unmanned Aerial Vehicle ◽  
Environmental Science ◽  
Interaction Network ◽  
The United States ◽  
Future Research ◽  
The Past ◽  
Sensing Applications ◽  
Aerial Vehicle

Unmanned Aerial Vehicle (UAV) Remote sensing (RS) has unique advantages over traditional satellite RS, including convenience, high resolution, affordability and fast acquisition speed, making it widely used in many fields. To provide an overview of the development of UAV RS applications during the past decade, we screened related publications from the Web of Science core database from 2010 to 2021, built co-author networks, a discipline interaction network, a keywords timeline view, a co-citation cluster, and detected burst citations using bibliometrics and social network analysis. Our results show that: (1) The number of UAV RS publications had an increasing trend, with explosive growth in the past five years. The number of papers published by China and the United States (US) is far ahead in this field; (2) The US has currently the greatest influence in this field through the largest number of international cooperations. Cooperation is mainly concentrated in countries and institutions with a large number of publications but is not widely distributed. (3) The application of UAV RS involves multiple interdisciplinary subjects, among which “Environmental Science and Ecology” ranks first; (4) Future research trends of UAV RS are expected to be related to artificial intelligence (e.g., artificial neural networks-based research). This paper provides a scientific basis and guidance for future developments of UAV RS applications, which can help the research community to better grasp the developments of this field.

scholarly journals Unmanned Aerial Vehicle for Remote Sensing Applications—A Review

2019 ◽  
Vol 11 (12) ◽  
pp. 1443 ◽  
Author(s):  
Huang Yao ◽  
Rongjun Qin ◽  
Xiaoyu Chen
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Cover ◽  
Unmanned Aerial Vehicle ◽  
Land Cover Classification ◽  
Sensor Data ◽  
Future Research ◽  
Systematic Analysis ◽  
Sensing Applications ◽  
Aerial Vehicle

The unmanned aerial vehicle (UAV) sensors and platforms nowadays are being used in almost every application (e.g., agriculture, forestry, and mining) that needs observed information from the top or oblique views. While they intend to be a general remote sensing (RS) tool, the relevant RS data processing and analysis methods are still largely ad-hoc to applications. Although the obvious advantages of UAV data are their high spatial resolution and flexibility in acquisition and sensor integration, there is in general a lack of systematic analysis on how these characteristics alter solutions for typical RS tasks such as land-cover classification, change detection, and thematic mapping. For instance, the ultra-high-resolution data (less than 10 cm of Ground Sampling Distance (GSD)) bring more unwanted classes of objects (e.g., pedestrian and cars) in land-cover classification; the often available 3D data generated from photogrammetric images call for more advanced techniques for geometric and spectral analysis. In this paper, we perform a critical review on RS tasks that involve UAV data and their derived products as their main sources including raw perspective images, digital surface models, and orthophotos. In particular, we focus on solutions that address the “new” aspects of the UAV data including (1) ultra-high resolution; (2) availability of coherent geometric and spectral data; and (3) capability of simultaneously using multi-sensor data for fusion. Based on these solutions, we provide a brief summary of existing examples of UAV-based RS in agricultural, environmental, urban, and hazards assessment applications, etc., and by discussing their practical potentials, we share our views in their future research directions and draw conclusive remarks.

scholarly journals Mapping Analysis of Mangrove Areas using Unmanned Aerial Vehicle (UAV) Method in Maros District South Sulawesi

2021 ◽  
Vol 2123 (1) ◽  
pp. 012010
Author(s):  
A Arfan ◽  
S Nyompa ◽  
R Maru ◽  
S Nurdin ◽  
M F Juanda
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Unmanned Aerial Vehicle ◽  
Mangrove Forest ◽  
The Road ◽  
South Sulawesi ◽  
Sensing Applications ◽  
Analysis Technique ◽  
Aerial Vehicle ◽  
Bodies Of Water

Abstract Unmanned Aerial Vehicle (UAV) technology can be used for remote sensing applications. The use of UAVs increases the efficiency of collecting land use information in mangrove forest areas. The purpose of the study was to analyze the mangrove forest area using an Unmanned Aerial Vehicle around Sabang Tambua Pier and Ampekale Village. The data analysis technique is remote sensing analysis and geographic information system using Pix4D, Agisoft Metashape 1.7 and ArcGIS ArcMap 1.4 applications. The results of the analysis show that mangroves appear green in color, rough texture, elongated shape following the coastline. Residential settlements are white or brown in color, rectangular in shape, rough in texture and the site sometimes follows the highway and follows the coastline. The clear green pond resembles a body of water with a rectangular shape. The road segment is in the form of black lines on asphalt roads and grayish-white on concrete roads. The area of land use for mangroves, settlements, ponds, bodies of water (sea) around the Sabang Tambua Pier is 4.67 ha, 1.20 ha, 26.73 ha and 3.85 ha, while in Ampekale Village 4.06 h2, 1.95 ha, 12.61 ha and 2.10 ha.

scholarly journals Recent Advances in Unmanned Aerial Vehicle Forest Remote Sensing—A Systematic Review. Part I: A General Framework

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 327 ◽  
Author(s):  
Riccardo Dainelli ◽  
Piero Toscano ◽  
Salvatore Filippo Di Gennaro ◽  
Alessandro Matese
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Relevant Information ◽  
Forest Monitoring ◽  
Machine Learning Techniques ◽  
Planted Forests ◽  
Systematic Analysis ◽  
Aerial Photogrammetry ◽  
Wide Range ◽  
Aerial Vehicle

Natural, semi-natural, and planted forests are a key asset worldwide, providing a broad range of positive externalities. For sustainable forest planning and management, remote sensing (RS) platforms are rapidly going mainstream. In a framework where scientific production is growing exponentially, a systematic analysis of unmanned aerial vehicle (UAV)-based forestry research papers is of paramount importance to understand trends, overlaps and gaps. The present review is organized into two parts (Part I and Part II). Part II inspects specific technical issues regarding the application of UAV-RS in forestry, together with the pros and cons of different UAV solutions and activities where additional effort is needed, such as the technology transfer. Part I systematically analyzes and discusses general aspects of applying UAV in natural, semi-natural and artificial forestry ecosystems in the recent peer-reviewed literature (2018–mid-2020). The specific goals are threefold: (i) create a carefully selected bibliographic dataset that other researchers can draw on for their scientific works; (ii) analyze general and recent trends in RS forest monitoring (iii) reveal gaps in the general research framework where an additional activity is needed. Through double-step filtering of research items found in the Web of Science search engine, the study gathers and analyzes a comprehensive dataset (226 articles). Papers have been categorized into six main topics, and the relevant information has been subsequently extracted. The strong points emerging from this study concern the wide range of topics in the forestry sector and in particular the retrieval of tree inventory parameters often through Digital Aerial Photogrammetry (DAP), RGB sensors, and machine learning techniques. Nevertheless, challenges still exist regarding the promotion of UAV-RS in specific parts of the world, mostly in the tropical and equatorial forests. Much additional research is required for the full exploitation of hyperspectral sensors and for planning long-term monitoring.

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