Water resource management at catchment scales using lightweight UAVs: current capabilities and future perspectives
-
Published:2016-03-01
Issue:1
Volume:4
Page:7-30
-
ISSN:2291-3467
-
Container-title:Journal of Unmanned Vehicle Systems
-
language:en
-
Short-container-title:J. Unmanned Veh. Sys.
Author:
DeBell L.1, Anderson K.1, Brazier R.E.2, King N.3, Jones L.4
Affiliation:
1. Environment and Sustainability Institute, University of Exeter, Penryn Campus, Penryn, Cornwall, UK 2. Department of Geography, College of Life and Environmental Sciences, University of Exeter, Exeter, UK 3. QuestUAV, Unit 7B Coquetdale Enterprise Park, Amble, Northumberland, UK 4. South West Water, Peninsula House, Rydon Lane, Exeter, Devon, UK
Abstract
Lightweight, portable unmanned aerial vehicles (UAVs) or ‘drones’ are set to become a key component of a water resource management (WRM) toolkit, but are currently not widely used in this context. In practical WRM there is a growing need for fine-scale responsive data, which cannot be delivered from satellites or aircraft in a cost-effective way. Such a capability is needed where water supplies are located in spatially heterogeneous dynamic catchments. In this review, we demonstrate the step change in hydrological process understanding that could be delivered if WRM employed UAVs. The paper discusses a range of pragmatic concepts in UAV science for cost-effective and practical WRM, from choosing the right sensor and platform combination through to practical deployment and data processing challenges. The paper highlights that multi-sensor approaches, such as combining thermal imaging with fine-scale structure-from-motion topographic models, are currently best placed to assist in WRM decision-making because they provide a means of monitoring the spatio-temporal distribution of sources, sinks, and flows of water through landscapes. The manuscript highlights areas where research is needed to support the integration of UAVs into practical WRM, for example, in improving positional accuracy through integration of differential global positioning system sensors, and developing intelligent control of UAV platforms to optimize the accuracy of spatial data capture.
Publisher
Canadian Science Publishing
Subject
Electrical and Electronic Engineering,Control and Optimization,Computer Science Applications,Aerospace Engineering,Automotive Engineering,Control and Systems Engineering
Reference105 articles.
1. Abdelkader, M., Shaqura, M., Ghommem, M., Collier, N., Calo, V., and Claudel, C. 2014. Optimal multi-agent path planning for fast inverse modeling in UAV-based flood sensing applications. In 2014 International Conference on Unmanned Aircraft Systems (ICUAS), Orlando, FL. pp. 64–71. 2. Integrated use of remote sensing, GIS and precipitation data for the assessment of soil erosion rate in the catchment area of “Yialias” in Cyprus 3. Anderson, C.A., Vivoni, E.R., Pierini, N., Robles-Morua, A., Rango, A., Laliberte, A., and Saripalli, A. 2012. Characterization of shrubland-atmosphere interactions through use of the Eddy covariance method, distributed footprint sampling and imagery from unmanned aerial vehicles. Poster presentation. In American Geophysical Union Fall Meeting, San Francisco, CA, USA. 3–7 December 2012. 4. Lightweight unmanned aerial vehicles will revolutionize spatial ecology 5. Interactions and connectivity between runoff generation processes of different spatial scales
Cited by
70 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|