Soil Degradation Mapping in Drylands Using Unmanned Aerial Vehicle (UAV) Data

Arid and semi-arid landscapes often show a patchwork of bare and vegetated spaces. Their heterogeneous patterns can be of natural origin, but may also indicate soil degradation. This study investigates the use of unmanned aerial vehicle (UAV) imagery to identify the degradation status of soils, base...

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Main Authors: Juliane Krenz, Philip Greenwood, Nikolaus J. Kuhn
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Soil Systems
Subjects:
Online Access:https://www.mdpi.com/2571-8789/3/2/33
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spelling doaj-3b23a57ea5e4441fbc6db2b79b4f859b2020-11-25T01:19:21ZengMDPI AGSoil Systems2571-87892019-05-01323310.3390/soilsystems3020033soilsystems3020033Soil Degradation Mapping in Drylands Using Unmanned Aerial Vehicle (UAV) DataJuliane Krenz0Philip Greenwood1Nikolaus J. Kuhn2Physical Geography and Environmental Change, University of Basel, 4056 Basel, SwitzerlandPhysical Geography and Environmental Change, University of Basel, 4056 Basel, SwitzerlandPhysical Geography and Environmental Change, University of Basel, 4056 Basel, SwitzerlandArid and semi-arid landscapes often show a patchwork of bare and vegetated spaces. Their heterogeneous patterns can be of natural origin, but may also indicate soil degradation. This study investigates the use of unmanned aerial vehicle (UAV) imagery to identify the degradation status of soils, based on the hypothesis that vegetation cover can be used as a proxy for estimating the soils’ health status. To assess the quality of the UAV-derived products, we compare a conventional field-derived map (FM) with two modelled maps based on (i) vegetation cover (RGB map), and (ii) vegetation cover, topographic information, and a flow accumulation analysis (RGB+DEM map). All methods were able to identify areas of soil degradation but differed in the extent of classified soil degradation, with the RGB map classifying the least amount as degraded. The RGB+DEM map classified 12% more as degraded than the FM, due to the wider perspective of the UAV compared to conventional field mapping. Overall, conventional UAVs provide a valuable tool for soil mapping in heterogeneous landscapes where manual field sampling is very time consuming. Additionally, the UAVs’ planform view from a bird’s-eye perspective can overcome the limited view from the surveyors’ (ground-based) vantage point.https://www.mdpi.com/2571-8789/3/2/33erosionlandscape mappingsoil degradationsoil mappingunmanned aerial vehicle (UAV)
collection DOAJ
language English
format Article
sources DOAJ
author Juliane Krenz
Philip Greenwood
Nikolaus J. Kuhn
spellingShingle Juliane Krenz
Philip Greenwood
Nikolaus J. Kuhn
Soil Degradation Mapping in Drylands Using Unmanned Aerial Vehicle (UAV) Data
Soil Systems
erosion
landscape mapping
soil degradation
soil mapping
unmanned aerial vehicle (UAV)
author_facet Juliane Krenz
Philip Greenwood
Nikolaus J. Kuhn
author_sort Juliane Krenz
title Soil Degradation Mapping in Drylands Using Unmanned Aerial Vehicle (UAV) Data
title_short Soil Degradation Mapping in Drylands Using Unmanned Aerial Vehicle (UAV) Data
title_full Soil Degradation Mapping in Drylands Using Unmanned Aerial Vehicle (UAV) Data
title_fullStr Soil Degradation Mapping in Drylands Using Unmanned Aerial Vehicle (UAV) Data
title_full_unstemmed Soil Degradation Mapping in Drylands Using Unmanned Aerial Vehicle (UAV) Data
title_sort soil degradation mapping in drylands using unmanned aerial vehicle (uav) data
publisher MDPI AG
series Soil Systems
issn 2571-8789
publishDate 2019-05-01
description Arid and semi-arid landscapes often show a patchwork of bare and vegetated spaces. Their heterogeneous patterns can be of natural origin, but may also indicate soil degradation. This study investigates the use of unmanned aerial vehicle (UAV) imagery to identify the degradation status of soils, based on the hypothesis that vegetation cover can be used as a proxy for estimating the soils’ health status. To assess the quality of the UAV-derived products, we compare a conventional field-derived map (FM) with two modelled maps based on (i) vegetation cover (RGB map), and (ii) vegetation cover, topographic information, and a flow accumulation analysis (RGB+DEM map). All methods were able to identify areas of soil degradation but differed in the extent of classified soil degradation, with the RGB map classifying the least amount as degraded. The RGB+DEM map classified 12% more as degraded than the FM, due to the wider perspective of the UAV compared to conventional field mapping. Overall, conventional UAVs provide a valuable tool for soil mapping in heterogeneous landscapes where manual field sampling is very time consuming. Additionally, the UAVs’ planform view from a bird’s-eye perspective can overcome the limited view from the surveyors’ (ground-based) vantage point.
topic erosion
landscape mapping
soil degradation
soil mapping
unmanned aerial vehicle (UAV)
url https://www.mdpi.com/2571-8789/3/2/33
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