Water resource management at catchment scales using lightweight UAVs: current capabilities and future perspectives
DeBell, L; Anderson, K; Brazier, Richard E.; et al.Jones, L; King, N
Date: 2015
Journal
Journal of Unmanned Vehicle Systems
Publisher
NRC Research Press
Publisher DOI
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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 ...
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 WRM decisions 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 – e.g. 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.
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