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On the Use of Unmanned Aerial Systems for Environmental Monitoring

Dipartimento delle Culture Europee e del Mediterraneo: Architettura, Ambiente, Patrimoni Culturali (DiCEM), Università degli Studi della Basilicata, 75100 Matera, Italy
Water Desalination and Reuse Center, King Abdullah University of Science and Technology, 23955 Thuwal, Saudi Arabia
The James Hutton Institute, Aberdeen AB15 8QH, UK
Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, Ceredigion SY23 3DB, UK
Svarmi ehf., Árleyni 22, 112 Reykjavík, Iceland
Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, 67100 Xanthi, Greece
Department of Geography and Human Environment, Tel Aviv University (TAU), Tel Aviv 6997801, Israel
Department of Geography and the Environment, Bar-Ilan University, Ramat Gan 52900, Israel
Graduate School of Geography, Clark University, Worcester, MA 01610, USA
Dipartimento di Ingegneria Civile, Ambientale, Aerospaziale, dei Materiali, University of Palermo, 90128 Palermo, Italy
Department GIS and Remote Sensing, Institute of Botany, The Czech Acad. Sciences, 252 43 Průhonice, Czech Republic
Centro per l’Innovazione Tecnologica e lo Sviluppo del Territorio (CINTEST), Università degli Studi della Tuscia, 01100 Viterbo, Italy
Marine and Environmental Sciences Centre, Department of Civil Engineering, University of Coimbra, 3000-370 Coimbra, Portugal
Research Group of Hydrological and Environmental Modelling (GIHMA), Research Institute of Water and Environmental Engineering, Universidad Politecnica de Valencia, 46022 València, Spain
Department of Geography, University of California, Santa Barbara, CA 93106-3060, USA
Department of Geology, University of Tartu, 50090 Tartu, Estonia
School of Geography, Politics and Sociology, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
Department of Crop Production Ecology, Swedish University of Agricultural Sciences (SLU), 750 07 Uppsala, Sweden
Department of Water Resources in Faculty of Geo-Information and Earth Observation, University of Twente, 7522 NB Enschede, The Netherlands
Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Hungarian Academy of Sciences, H-1022 Budapest, Hungary
Department of Crop Production and Soil Science, University of Pannonia, 8360 Keszthely, Hungary
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(4), 641;
Received: 12 March 2018 / Revised: 17 April 2018 / Accepted: 17 April 2018 / Published: 20 April 2018
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges. View Full-Text
Keywords: UAS; remote sensing; environmental monitoring; precision agriculture; vegetation indices; soil moisture; river monitoring UAS; remote sensing; environmental monitoring; precision agriculture; vegetation indices; soil moisture; river monitoring
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MDPI and ACS Style

Manfreda, S.; McCabe, M.F.; Miller, P.E.; Lucas, R.; Pajuelo Madrigal, V.; Mallinis, G.; Ben Dor, E.; Helman, D.; Estes, L.; Ciraolo, G.; Müllerová, J.; Tauro, F.; De Lima, M.I.; De Lima, J.L.M.P.; Maltese, A.; Frances, F.; Caylor, K.; Kohv, M.; Perks, M.; Ruiz-Pérez, G.; Su, Z.; Vico, G.; Toth, B. On the Use of Unmanned Aerial Systems for Environmental Monitoring. Remote Sens. 2018, 10, 641.

AMA Style

Manfreda S, McCabe MF, Miller PE, Lucas R, Pajuelo Madrigal V, Mallinis G, Ben Dor E, Helman D, Estes L, Ciraolo G, Müllerová J, Tauro F, De Lima MI, De Lima JLMP, Maltese A, Frances F, Caylor K, Kohv M, Perks M, Ruiz-Pérez G, Su Z, Vico G, Toth B. On the Use of Unmanned Aerial Systems for Environmental Monitoring. Remote Sensing. 2018; 10(4):641.

Chicago/Turabian Style

Manfreda, Salvatore, Matthew F. McCabe, Pauline E. Miller, Richard Lucas, Victor Pajuelo Madrigal, Giorgos Mallinis, Eyal Ben Dor, David Helman, Lyndon Estes, Giuseppe Ciraolo, Jana Müllerová, Flavia Tauro, M. Isabel De Lima, João L. M. P. De Lima, Antonino Maltese, Felix Frances, Kelly Caylor, Marko Kohv, Matthew Perks, Guiomar Ruiz-Pérez, Zhongbo Su, Giulia Vico, and Brigitta Toth. 2018. "On the Use of Unmanned Aerial Systems for Environmental Monitoring" Remote Sensing 10, no. 4: 641.

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