Unmanned aerial vehicle observations of water surface elevation and bathymetry in the cenotes and lagoons of the Yucatan Peninsula, Mexico

Bandini, Filippo; Lopez-Tamayo, Alejandro; Merediz-Alonso, Gonzalo; Olesen, Daniel; Jakobsen, Jakob; García, Mónica; Bauer‐Gottwein, Peter

doi:10.1007/s10040-018-1755-9

Cited by 19 publications

(19 citation statements)

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“…In the post process, an ensemble Kalman filter was applied in both forward and backward directions for best position performance. For details, refer to [37]. Further, after each flight campaign, high accuracy ground control points (GCPs) were measured with Trimble RTK GNSS.…”

Section: Unmanned Aerial System (Uas) and Flight Campaignsmentioning

confidence: 99%

Mapping Root-Zone Soil Moisture Using a Temperature–Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion

et al. 2018

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High resolution root-zone soil moisture (SM) maps are important for understanding the spatial variability of water availability in agriculture, ecosystems research and water resources management. Unmanned Aerial Systems (UAS) can flexibly monitor land surfaces with thermal and optical imagery at very high spatial resolution (meter level, VHR) for most weather conditions. We modified the temperature–vegetation triangle approach to transfer it from satellite to UAS remote sensing. To consider the effects of the limited coverage of UAS mapping, theoretical dry/wet edges were introduced. The new method was tested on a bioenergy willow short rotation coppice site during growing seasons of 2016 and 2017. We demonstrated that by incorporating surface roughness parameters from the structure-from-motion in the interpretation of the measured land surface-atmosphere temperature gradients, the estimates of SM significantly improved. The correlation coefficient between estimated and measured SM increased from not significant to 0.69 and the root mean square deviation decreased from 0.045 m3∙m−3 to 0.025 m3∙m−3 when considering temporal dynamics of surface roughness in the approach. The estimated SM correlated better with in-situ root-zone SM (15–30 cm) than with surface SM (0–5 cm) which is an important advantage over alternative remote sensing methods to estimate SM. The optimal spatial resolution of the triangle approach was found to be around 1.5 m, i.e. similar to the length scale of tree-crowns. This study highlights the importance of considering the 3-D fine scale canopy structure, when addressing the links between surface temperature and SM patterns via surface energy balances. Our methodology can be applied to operationally monitor VHR root-zone SM from UAS in agricultural and natural ecosystems.

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Section: Unmanned Aerial System (Uas) and Flight Campaignsmentioning

confidence: 99%

Mapping Root-Zone Soil Moisture Using a Temperature–Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion

et al. 2018

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“…At remote locations with no in situ measurement access, satellite bathymetry may be an option for estimating the depth of larger lakes and shallow coastlines, albeit with various considerations such as ground resolution, time of capture, and water transparency [29,30], however, this approach is not adequate to validate Lidar bathymetry accuracy. An unmanned airborne vehicle (UAV) with a tethered sonar may provide good bathymetry, but such surveys are localized, restricted with dense aquatic vegetation, and difficult to navigate at locations with heavy riparian vegetation [31].…”

Section: Methodsmentioning

confidence: 99%

Quantifying Airborne Lidar Bathymetry Quality-Control Measures: A Case Study in Frio River, Texas

Saylam

Hupp

Andrews

et al. 2018

Sensors

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Airborne Lidar Bathymetry (ALB) is an advanced and effective technology for mapping water bodies and measuring water depth in relatively shallow inland and coastal zones. The concept of using light beams to detect and traverse water bodies has been around since the 1960s; however, its popularity has increased significantly in recent years with the advent of relatively affordable hardware, supplemented with potent software applications to process and analyze resulting data. To achieve the most accurate final product, which is usually a digital elevation model (DEM) of the bottom of a water body, various quality-control (QC) measures are applied during and after an airborne mission. River surveys, in particular, present various challenges, and quantifying the quality of the end product requires supplemental surveys and careful analysis of all data sets. In this article, we discuss a recent ALB survey of the Frio River in Texas and summarize the findings of all QC measures conducted. We conclude the article with suggestions for successful ALB deployments at similar survey locations.

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“…Autonomous Systems for the Environmental Characterization of Lagoons DOI: http://dx.doi.org /10.5772/intechopen.90405 UAVs have also been used to make water surface elevation (i.e. orthometric water height above mean sea level) and bathymetry observations in lagoons of the Yucatan Peninsula (Mexico) [18]. In Ref.…”

Section: Unmanned Aerial Vehiclesmentioning

confidence: 99%

“…In Ref. [18], the authors used a DJI hexacopter Spreading Wings S900 UAV equipped with an RGB high-resolution camera (Sony DSC-RX100) and lower-resolution fish-eye lens Eken H9 camera to characterize water surface elevation. The UAV was enabled to control a tethered sonar sensor (Deeper Smart Sonar PRO + Deeper, UAB, Vilnius, Lithuania) able to map the bathymetry of the lagoons.…”

Section: Unmanned Aerial Vehiclesmentioning

confidence: 99%

Autonomous Systems for the Environmental Characterization of Lagoons

Casado¹,

Palma²,

Leinster³

2020

Lagoon Environments Around the World - A Scientific Perspective

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This chapter reviews the state of the art in robotics and autonomous systems (RAS) for monitoring the environmental characteristics of lagoons, as well as potential future uses of such technologies that could contribute to enhancing current monitoring programmes. Particular emphasis will be given to unmanned aerial vehicles (UAVs), autonomous under water vehicles (AUVs), remotely operated underwater vehicles (ROVs) and (semi-)autonomous boats. Recent technological advances in UAVs, AUVs and ROVs have demonstrated that high-resolution data (e.g. 0.4 cm imagery resolution) can be gathered when bespoke sensors are incorporated within these platforms. This in turn enables the accurate quantification of key metrics within lagoon environments, such as coral morphometries. For example, coral height and width can now be estimated remotely with errors below 12.6 and 14.7 cm, respectively. The chapter will explore how the use of such technologies in combination could improve the understanding of lagoon environments through increased knowledge of the spatial and temporal variations of parameters of interest. Within this context, both advantages and limitations of the proposed approaches will be highlighted and described from operational, logistical, and regulatory considerations. The chapter will be based on recent peer-reviewed research outputs obtained by the authors.

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Unmanned aerial vehicle observations of water surface elevation and bathymetry in the cenotes and lagoons of the Yucatan Peninsula, Mexico

Cited by 19 publications

References 58 publications

Mapping Root-Zone Soil Moisture Using a Temperature–Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion

Mapping Root-Zone Soil Moisture Using a Temperature–Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion

Quantifying Airborne Lidar Bathymetry Quality-Control Measures: A Case Study in Frio River, Texas

Autonomous Systems for the Environmental Characterization of Lagoons

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