Using Vegetation Indices and a UAV Imaging Platform to Quantify the Density of Vegetation Ground Cover in Olive Groves (<i>Olea Europaea</i> L.) in Southern Spain

In olive groves, vegetation ground cover (VGC) plays an important ecological role. The EU Common Agricultural Policy, through cross-compliance, acknowledges the importance of this factor, but, to determine the real impact of VGC, it must first be quantified. Accordingly, in the present study, eleven...

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Main Authors: Francisco J. Lima-Cueto, Rafael Blanco-Sepúlveda, María L. Gómez-Moreno, Federico B. Galacho-Jiménez
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/11/21/2564
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author Francisco J. Lima-Cueto
Rafael Blanco-Sepúlveda
María L. Gómez-Moreno
Federico B. Galacho-Jiménez
author_facet Francisco J. Lima-Cueto
Rafael Blanco-Sepúlveda
María L. Gómez-Moreno
Federico B. Galacho-Jiménez
author_sort Francisco J. Lima-Cueto
collection DOAJ
description In olive groves, vegetation ground cover (VGC) plays an important ecological role. The EU Common Agricultural Policy, through cross-compliance, acknowledges the importance of this factor, but, to determine the real impact of VGC, it must first be quantified. Accordingly, in the present study, eleven vegetation indices (VIs) were applied to quantify the density of VGC in olive groves (<i>Olea europaea</i> L.), according to high spatial resolution (10&#8722;12 cm) multispectral images obtained by an unmanned aerial vehicle (UAV). The fieldwork was conducted in early spring, in a Mediterranean mountain olive grove in southern Spain presenting various VGC densities. A five-step method was applied: (1) generate image mosaics using UAV technology; (2) apply the VIs; (3) quantify VGC density by means of sampling plots (ground-truth); (4) calculate the mean reflectance of the spectral bands and of the VIs in each sampling plot; and (5) quantify VGC density according to the VIs. The most sensitive index was IRVI, which accounted for 82% (<i>p</i> &lt; 0.001) of the variability of VGC density. The capability of the VIs to differentiate VGC densities increased in line with the cover interval range. RVI most accurately distinguished VGC densities &gt; 80% in a cover interval range of 10% (<i>p</i> &lt; 0.001), while IRVI was most accurate for VGC densities &lt; 30% in a cover interval range of 15% (<i>p</i> &lt; 0.01). IRVI, NRVI, NDVI, GNDVI and SAVI differentiated the complete series of VGC densities when the cover interval range was 30% (<i>p</i> &lt; 0.001 and <i>p</i> &lt; 0.05).
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spelling doaj.art-8f2613520ed64386a728760f023fd69c2022-12-22T01:35:15ZengMDPI AGRemote Sensing2072-42922019-11-011121256410.3390/rs11212564rs11212564Using Vegetation Indices and a UAV Imaging Platform to Quantify the Density of Vegetation Ground Cover in Olive Groves (<i>Olea Europaea</i> L.) in Southern SpainFrancisco J. Lima-Cueto0Rafael Blanco-Sepúlveda1María L. Gómez-Moreno2Federico B. Galacho-Jiménez3Geographic Analysis Research Group, Department of Geography, University of Malaga, Campus of Teatinos, s/n. 29071 Malaga, SpainGeographic Analysis Research Group, Department of Geography, University of Malaga, Campus of Teatinos, s/n. 29071 Malaga, SpainGeographic Analysis Research Group, Department of Geography, University of Malaga, Campus of Teatinos, s/n. 29071 Malaga, SpainGeographic Analysis Research Group, Department of Geography, University of Malaga, Campus of Teatinos, s/n. 29071 Malaga, SpainIn olive groves, vegetation ground cover (VGC) plays an important ecological role. The EU Common Agricultural Policy, through cross-compliance, acknowledges the importance of this factor, but, to determine the real impact of VGC, it must first be quantified. Accordingly, in the present study, eleven vegetation indices (VIs) were applied to quantify the density of VGC in olive groves (<i>Olea europaea</i> L.), according to high spatial resolution (10&#8722;12 cm) multispectral images obtained by an unmanned aerial vehicle (UAV). The fieldwork was conducted in early spring, in a Mediterranean mountain olive grove in southern Spain presenting various VGC densities. A five-step method was applied: (1) generate image mosaics using UAV technology; (2) apply the VIs; (3) quantify VGC density by means of sampling plots (ground-truth); (4) calculate the mean reflectance of the spectral bands and of the VIs in each sampling plot; and (5) quantify VGC density according to the VIs. The most sensitive index was IRVI, which accounted for 82% (<i>p</i> &lt; 0.001) of the variability of VGC density. The capability of the VIs to differentiate VGC densities increased in line with the cover interval range. RVI most accurately distinguished VGC densities &gt; 80% in a cover interval range of 10% (<i>p</i> &lt; 0.001), while IRVI was most accurate for VGC densities &lt; 30% in a cover interval range of 15% (<i>p</i> &lt; 0.01). IRVI, NRVI, NDVI, GNDVI and SAVI differentiated the complete series of VGC densities when the cover interval range was 30% (<i>p</i> &lt; 0.001 and <i>p</i> &lt; 0.05).https://www.mdpi.com/2072-4292/11/21/2564uavvegetation ground covermultispectralvegetation indicesagro-environmental measuresolive grovessouthern spain
spellingShingle Francisco J. Lima-Cueto
Rafael Blanco-Sepúlveda
María L. Gómez-Moreno
Federico B. Galacho-Jiménez
Using Vegetation Indices and a UAV Imaging Platform to Quantify the Density of Vegetation Ground Cover in Olive Groves (<i>Olea Europaea</i> L.) in Southern Spain
Remote Sensing
uav
vegetation ground cover
multispectral
vegetation indices
agro-environmental measures
olive groves
southern spain
title Using Vegetation Indices and a UAV Imaging Platform to Quantify the Density of Vegetation Ground Cover in Olive Groves (<i>Olea Europaea</i> L.) in Southern Spain
title_full Using Vegetation Indices and a UAV Imaging Platform to Quantify the Density of Vegetation Ground Cover in Olive Groves (<i>Olea Europaea</i> L.) in Southern Spain
title_fullStr Using Vegetation Indices and a UAV Imaging Platform to Quantify the Density of Vegetation Ground Cover in Olive Groves (<i>Olea Europaea</i> L.) in Southern Spain
title_full_unstemmed Using Vegetation Indices and a UAV Imaging Platform to Quantify the Density of Vegetation Ground Cover in Olive Groves (<i>Olea Europaea</i> L.) in Southern Spain
title_short Using Vegetation Indices and a UAV Imaging Platform to Quantify the Density of Vegetation Ground Cover in Olive Groves (<i>Olea Europaea</i> L.) in Southern Spain
title_sort using vegetation indices and a uav imaging platform to quantify the density of vegetation ground cover in olive groves i olea europaea i l in southern spain
topic uav
vegetation ground cover
multispectral
vegetation indices
agro-environmental measures
olive groves
southern spain
url https://www.mdpi.com/2072-4292/11/21/2564
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