scholarly journals Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an Unmanned Aerial Vehicle

2017 ◽  
Author(s):  
Filippo Bandini ◽  
Daniel Olesen ◽  
Jakob Jakobsen ◽  
Cecile Marie Margaretha Kittel ◽  
Sheng Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Cross Sections ◽  
Water Bodies ◽  
Water Turbidity ◽  
Inland Water ◽  
Single Beam ◽  
Aerial Vehicle ◽  
Inland Water Bodies ◽  
Water Depths

Abstract. High-quality bathymetric maps of inland water bodies are a common requirement for hydraulic engineering and hydrological science applications. Remote sensing methods, e.g. space-borne and airborne multispectral or LIDAR, have been developed to estimate water depth, but are ineffective for most inland water bodies, because of water turbidity and attenuation of electromagnetic radiation in water. Surveys conducted with boats equipped with sonars can retrieve accurate water depths, but are expensive, time-consuming, and are unsuitable for non-navigable water bodies. We develop and assess a novel approach to retrieve accurate and high resolution bathymetry maps. We measured accurate water depths using a tethered floating sonar controlled by an Unmanned Aerial Vehicle (UAV) in a Danish lake and in a few river cross sections. The developed technique combines the advantages of remote sensing techniques with the potential of bathymetric sonars. UAV surveys can be conducted also in non-navigable, inaccessible, or remote water bodies. The tethered sonar can measure bathymetry with an accuracy of ca. 2.1 % of the actual depth for observations up to 35 m, without being significantly affected by water turbidity, bedform or bed material.

scholarly journals Technical note: Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle

2018 ◽  
Vol 22 (8) ◽  
pp. 4165-4181 ◽  
Author(s):  
Filippo Bandini ◽  
Daniel Olesen ◽  
Jakob Jakobsen ◽  
Cecile Marie Margaretha Kittel ◽  
Sheng Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Multispectral Imaging ◽  
Technical Note ◽  
Water Bodies ◽  
Inland Water ◽  
Single Beam ◽  
Aerial Vehicle ◽  
Inland Water Bodies ◽  
Water Depths

Abstract. High-quality bathymetric maps of inland water bodies are a common requirement for hydraulic engineering and hydrological science applications. Remote sensing methods, such as space-borne and airborne multispectral imaging or lidar, have been developed to estimate water depth, but are ineffective for most inland water bodies, because of the attenuation of electromagnetic radiation in water, especially under turbid conditions. Surveys conducted with boats equipped with sonars can retrieve accurate water depths, but are expensive, time-consuming, and unsuitable for unnavigable water bodies. We develop and assess a novel approach to retrieve accurate and high-resolution bathymetry maps. We measured accurate water depths using a tethered floating sonar controlled by an unmanned aerial vehicle (UAV) in a lake and in two different rivers located in Denmark. The developed technique combines the advantages of remote sensing with the potential of bathymetric sonars. UAV surveys can be conducted also in unnavigable, inaccessible, or remote water bodies. The tethered sonar can measure bathymetry with an accuracy of ∼2.1 % of the actual depth for observations up to 35 m, without being significantly affected by water turbidity, bed form, or bed material.

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 Editorial for the Special Issue “Remote Sensing of Water Quality”

2019 ◽  
Vol 11 (18) ◽  
pp. 2178
Author(s):  
Wesley J. Moses ◽  
W. David Miller
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Water Resources ◽  
Water Bodies ◽  
Special Issue ◽  
Coastal Regions ◽  
Inland Water ◽  
Quality Of Water ◽  
Inland Water Bodies

The importance of monitoring, preserving, and, where needed, improving the quality of water resources in the open ocean, coastal regions, estuaries, and inland water bodies cannot be overstated [...]

scholarly journals Identification of Potential Surface Water Resources for Inland Aquaculture from Sentinel-2 Images of the Rwenzori Region of Uganda

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2657
Author(s):  
Athanasius Ssekyanzi ◽  
Nancy Nevejan ◽  
Dimitry Van der Van der Zande ◽  
Molly E. Brown ◽  
Gilbert Van Van Stappen
Keyword(s):  
Remote Sensing ◽  
Surface Water ◽  
Water Resources ◽  
Image Resolution ◽  
Water Bodies ◽  
Inland Water ◽  
Surface Water Resources ◽  
Moderate Resolution ◽  
Sentinel 2A ◽  
Inland Water Bodies

Aquaculture has the potential to sustainably meet the growing demand for animal protein. The availability of water is essential for aquaculture development, but there is no knowledge about the potential inland water resources of the Rwenzori region of Uganda. Though remote sensing is popularly utilized during studies involving various aspects of surface water, it has never been employed in mapping inland water bodies of Uganda. In this study, we assessed the efficiency of seven remote-sensing derived water index methods to map the available surface water resources in the Rwenzori region using moderate resolution Sentinel 2A/B imagery. From the four targeted sites, the Automated Water Extraction Index for urban areas (AWEInsh) and shadow removal (AWEIsh) were the best at identifying inland water bodies in the region. Both AWEIsh and AWEInsh consistently had the highest overall accuracy (OA) and kappa (OA > 90%, kappa > 0.8 in sites 1 and 2; OA > 84.9%, kappa > 0.61 in sites 3 and 4), as well as the lowest omission errors in all sites. AWEI was able to suppress classification noise from shadows and other non-water dark surfaces. However, none of the seven water indices used during this study was able to efficiently extract narrow water bodies such as streams. This was due to a combination of factors like the presence of terrain shadows, a dense vegetation cover, and the image resolution. Nonetheless, AWEI can efficiently identify other surface water resources such as crater lakes and rivers/streams that are potentially suitable for aquaculture from moderate resolution Sentinel 2A/B imagery.

Method of Evaluation of Potential Numbers and Biomass of Benthos-eating Fishes of Inland Water Bodies Based on Macrozoobenthos State

2016 ◽  
Vol 52 (6) ◽  
pp. 43-49
Author(s):  
V. V. Zamorov ◽  
Ye. Yu. Leonchyk ◽  
M. P. Zamorova ◽  
M. M. Dzhurtubayev
Keyword(s):  
Water Bodies ◽  
Inland Water ◽  
Method Of Evaluation ◽  
Inland Water Bodies

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.

Sign in / Sign up

Export Citation Format

Share Document