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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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 |
work_keys_str_mv |
AT julianekrenz soildegradationmappingindrylandsusingunmannedaerialvehicleuavdata AT philipgreenwood soildegradationmappingindrylandsusingunmannedaerialvehicleuavdata AT nikolausjkuhn soildegradationmappingindrylandsusingunmannedaerialvehicleuavdata |
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