Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau

Gully erosion is an important sediment source in small watershed, and causes severe land degradation, particularly in semi-arid regions. Accurately measuring gully morphological characteristics, and determining its topographic threshold, are vital for gully erosion simulation and control. In this study, 910 gullies were visually interpreted by unmanned aerial vehicle (UAV) technology combined with field measurement. Ten gully morphological characteristics were extracted from the digital orthophoto map (DOM) and digital elevation model (DEM) generated by UAV images, including gully length (L), circumference (C), plane area (PA), surface area (SA), volume (V), depth (D), top width (TW), mean width (MW), cross-sectional area (CSA), and ratio of top width to depth (TW/D). The morphological characteristics of 30 reachable gullies were measured by a real time kinematic (RTK) to validate the parameters extracted from the UAV images. The topographic thresholds were determined based on the local slope gradient (S) and upland drainage area (A), using a dataset of 365 gully heads and their corresponding land-use types. The results show that the mean absolute percentage errors (MAPE) of the 2D and 3D gully characteristics are less than 10% and 20%, respectively, demonstrating a high accuracy of gully characteristic extraction from UAV images. Gully V is significantly related to the other nine parameters. Significant power functions were fitted between V, and L, C, PA, and SA. The gully volume could be well-estimated by SA (V = 0.212 SA<sup<0.982</sup<), with a R<sup<2</sup< of 0.99. For all land-use types, the topographic threshold could be described as S = 0.61 A<sup<0.48</sup<, implying that water erosion is the dominant process controlling gully erosion in this region. The topographic threshold is land-use-dependent, and shrubland is hardest for gully incision, followed by grassland and cropland. The results are helpful to rapidly estimate gully erosion, and identify the areas for gully erosion mitigation in small watershed. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Ziguan Wang [verfasserIn] Guanghui Zhang [verfasserIn] Chengshu Wang [verfasserIn] Shukun Xing [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	gully erosion gully volume gully initiation slope gradient land-use type

Übergeordnetes Werk:	In: Remote Sensing - MDPI AG, 2009, 14(2022), 15, p 3529
Übergeordnetes Werk:	volume:14 ; year:2022 ; number:15, p 3529

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/rs14153529

Katalog-ID:	DOAJ034531343

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allfields	10.3390/rs14153529 doi (DE-627)DOAJ034531343 (DE-599)DOAJdd8068f8039c4dbc92b3e8f4071db6f8 DE-627 ger DE-627 rakwb eng Ziguan Wang verfasserin aut Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gully erosion is an important sediment source in small watershed, and causes severe land degradation, particularly in semi-arid regions. Accurately measuring gully morphological characteristics, and determining its topographic threshold, are vital for gully erosion simulation and control. In this study, 910 gullies were visually interpreted by unmanned aerial vehicle (UAV) technology combined with field measurement. Ten gully morphological characteristics were extracted from the digital orthophoto map (DOM) and digital elevation model (DEM) generated by UAV images, including gully length (L), circumference (C), plane area (PA), surface area (SA), volume (V), depth (D), top width (TW), mean width (MW), cross-sectional area (CSA), and ratio of top width to depth (TW/D). The morphological characteristics of 30 reachable gullies were measured by a real time kinematic (RTK) to validate the parameters extracted from the UAV images. The topographic thresholds were determined based on the local slope gradient (S) and upland drainage area (A), using a dataset of 365 gully heads and their corresponding land-use types. The results show that the mean absolute percentage errors (MAPE) of the 2D and 3D gully characteristics are less than 10% and 20%, respectively, demonstrating a high accuracy of gully characteristic extraction from UAV images. Gully V is significantly related to the other nine parameters. Significant power functions were fitted between V, and L, C, PA, and SA. The gully volume could be well-estimated by SA (V = 0.212 SA<sup<0.982</sup<), with a R<sup<2</sup< of 0.99. For all land-use types, the topographic threshold could be described as S = 0.61 A<sup<0.48</sup<, implying that water erosion is the dominant process controlling gully erosion in this region. The topographic threshold is land-use-dependent, and shrubland is hardest for gully incision, followed by grassland and cropland. The results are helpful to rapidly estimate gully erosion, and identify the areas for gully erosion mitigation in small watershed. gully erosion gully volume gully initiation slope gradient land-use type Science Q Guanghui Zhang verfasserin aut Chengshu Wang verfasserin aut Shukun Xing verfasserin aut In Remote Sensing MDPI AG, 2009 14(2022), 15, p 3529 (DE-627)608937916 (DE-600)2513863-7 20724292 nnns volume:14 year:2022 number:15, p 3529 https://doi.org/10.3390/rs14153529 kostenfrei https://doaj.org/article/dd8068f8039c4dbc92b3e8f4071db6f8 kostenfrei https://www.mdpi.com/2072-4292/14/15/3529 kostenfrei https://doaj.org/toc/2072-4292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 14 2022 15, p 3529
spelling	10.3390/rs14153529 doi (DE-627)DOAJ034531343 (DE-599)DOAJdd8068f8039c4dbc92b3e8f4071db6f8 DE-627 ger DE-627 rakwb eng Ziguan Wang verfasserin aut Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gully erosion is an important sediment source in small watershed, and causes severe land degradation, particularly in semi-arid regions. Accurately measuring gully morphological characteristics, and determining its topographic threshold, are vital for gully erosion simulation and control. In this study, 910 gullies were visually interpreted by unmanned aerial vehicle (UAV) technology combined with field measurement. Ten gully morphological characteristics were extracted from the digital orthophoto map (DOM) and digital elevation model (DEM) generated by UAV images, including gully length (L), circumference (C), plane area (PA), surface area (SA), volume (V), depth (D), top width (TW), mean width (MW), cross-sectional area (CSA), and ratio of top width to depth (TW/D). The morphological characteristics of 30 reachable gullies were measured by a real time kinematic (RTK) to validate the parameters extracted from the UAV images. The topographic thresholds were determined based on the local slope gradient (S) and upland drainage area (A), using a dataset of 365 gully heads and their corresponding land-use types. The results show that the mean absolute percentage errors (MAPE) of the 2D and 3D gully characteristics are less than 10% and 20%, respectively, demonstrating a high accuracy of gully characteristic extraction from UAV images. Gully V is significantly related to the other nine parameters. Significant power functions were fitted between V, and L, C, PA, and SA. The gully volume could be well-estimated by SA (V = 0.212 SA<sup<0.982</sup<), with a R<sup<2</sup< of 0.99. For all land-use types, the topographic threshold could be described as S = 0.61 A<sup<0.48</sup<, implying that water erosion is the dominant process controlling gully erosion in this region. The topographic threshold is land-use-dependent, and shrubland is hardest for gully incision, followed by grassland and cropland. The results are helpful to rapidly estimate gully erosion, and identify the areas for gully erosion mitigation in small watershed. gully erosion gully volume gully initiation slope gradient land-use type Science Q Guanghui Zhang verfasserin aut Chengshu Wang verfasserin aut Shukun Xing verfasserin aut In Remote Sensing MDPI AG, 2009 14(2022), 15, p 3529 (DE-627)608937916 (DE-600)2513863-7 20724292 nnns volume:14 year:2022 number:15, p 3529 https://doi.org/10.3390/rs14153529 kostenfrei https://doaj.org/article/dd8068f8039c4dbc92b3e8f4071db6f8 kostenfrei https://www.mdpi.com/2072-4292/14/15/3529 kostenfrei https://doaj.org/toc/2072-4292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 14 2022 15, p 3529
allfields_unstemmed	10.3390/rs14153529 doi (DE-627)DOAJ034531343 (DE-599)DOAJdd8068f8039c4dbc92b3e8f4071db6f8 DE-627 ger DE-627 rakwb eng Ziguan Wang verfasserin aut Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gully erosion is an important sediment source in small watershed, and causes severe land degradation, particularly in semi-arid regions. Accurately measuring gully morphological characteristics, and determining its topographic threshold, are vital for gully erosion simulation and control. In this study, 910 gullies were visually interpreted by unmanned aerial vehicle (UAV) technology combined with field measurement. Ten gully morphological characteristics were extracted from the digital orthophoto map (DOM) and digital elevation model (DEM) generated by UAV images, including gully length (L), circumference (C), plane area (PA), surface area (SA), volume (V), depth (D), top width (TW), mean width (MW), cross-sectional area (CSA), and ratio of top width to depth (TW/D). The morphological characteristics of 30 reachable gullies were measured by a real time kinematic (RTK) to validate the parameters extracted from the UAV images. The topographic thresholds were determined based on the local slope gradient (S) and upland drainage area (A), using a dataset of 365 gully heads and their corresponding land-use types. The results show that the mean absolute percentage errors (MAPE) of the 2D and 3D gully characteristics are less than 10% and 20%, respectively, demonstrating a high accuracy of gully characteristic extraction from UAV images. Gully V is significantly related to the other nine parameters. Significant power functions were fitted between V, and L, C, PA, and SA. The gully volume could be well-estimated by SA (V = 0.212 SA<sup<0.982</sup<), with a R<sup<2</sup< of 0.99. For all land-use types, the topographic threshold could be described as S = 0.61 A<sup<0.48</sup<, implying that water erosion is the dominant process controlling gully erosion in this region. The topographic threshold is land-use-dependent, and shrubland is hardest for gully incision, followed by grassland and cropland. The results are helpful to rapidly estimate gully erosion, and identify the areas for gully erosion mitigation in small watershed. gully erosion gully volume gully initiation slope gradient land-use type Science Q Guanghui Zhang verfasserin aut Chengshu Wang verfasserin aut Shukun Xing verfasserin aut In Remote Sensing MDPI AG, 2009 14(2022), 15, p 3529 (DE-627)608937916 (DE-600)2513863-7 20724292 nnns volume:14 year:2022 number:15, p 3529 https://doi.org/10.3390/rs14153529 kostenfrei https://doaj.org/article/dd8068f8039c4dbc92b3e8f4071db6f8 kostenfrei https://www.mdpi.com/2072-4292/14/15/3529 kostenfrei https://doaj.org/toc/2072-4292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 14 2022 15, p 3529
allfieldsGer	10.3390/rs14153529 doi (DE-627)DOAJ034531343 (DE-599)DOAJdd8068f8039c4dbc92b3e8f4071db6f8 DE-627 ger DE-627 rakwb eng Ziguan Wang verfasserin aut Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gully erosion is an important sediment source in small watershed, and causes severe land degradation, particularly in semi-arid regions. Accurately measuring gully morphological characteristics, and determining its topographic threshold, are vital for gully erosion simulation and control. In this study, 910 gullies were visually interpreted by unmanned aerial vehicle (UAV) technology combined with field measurement. Ten gully morphological characteristics were extracted from the digital orthophoto map (DOM) and digital elevation model (DEM) generated by UAV images, including gully length (L), circumference (C), plane area (PA), surface area (SA), volume (V), depth (D), top width (TW), mean width (MW), cross-sectional area (CSA), and ratio of top width to depth (TW/D). The morphological characteristics of 30 reachable gullies were measured by a real time kinematic (RTK) to validate the parameters extracted from the UAV images. The topographic thresholds were determined based on the local slope gradient (S) and upland drainage area (A), using a dataset of 365 gully heads and their corresponding land-use types. The results show that the mean absolute percentage errors (MAPE) of the 2D and 3D gully characteristics are less than 10% and 20%, respectively, demonstrating a high accuracy of gully characteristic extraction from UAV images. Gully V is significantly related to the other nine parameters. Significant power functions were fitted between V, and L, C, PA, and SA. The gully volume could be well-estimated by SA (V = 0.212 SA<sup<0.982</sup<), with a R<sup<2</sup< of 0.99. For all land-use types, the topographic threshold could be described as S = 0.61 A<sup<0.48</sup<, implying that water erosion is the dominant process controlling gully erosion in this region. The topographic threshold is land-use-dependent, and shrubland is hardest for gully incision, followed by grassland and cropland. The results are helpful to rapidly estimate gully erosion, and identify the areas for gully erosion mitigation in small watershed. gully erosion gully volume gully initiation slope gradient land-use type Science Q Guanghui Zhang verfasserin aut Chengshu Wang verfasserin aut Shukun Xing verfasserin aut In Remote Sensing MDPI AG, 2009 14(2022), 15, p 3529 (DE-627)608937916 (DE-600)2513863-7 20724292 nnns volume:14 year:2022 number:15, p 3529 https://doi.org/10.3390/rs14153529 kostenfrei https://doaj.org/article/dd8068f8039c4dbc92b3e8f4071db6f8 kostenfrei https://www.mdpi.com/2072-4292/14/15/3529 kostenfrei https://doaj.org/toc/2072-4292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 14 2022 15, p 3529
allfieldsSound	10.3390/rs14153529 doi (DE-627)DOAJ034531343 (DE-599)DOAJdd8068f8039c4dbc92b3e8f4071db6f8 DE-627 ger DE-627 rakwb eng Ziguan Wang verfasserin aut Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gully erosion is an important sediment source in small watershed, and causes severe land degradation, particularly in semi-arid regions. Accurately measuring gully morphological characteristics, and determining its topographic threshold, are vital for gully erosion simulation and control. In this study, 910 gullies were visually interpreted by unmanned aerial vehicle (UAV) technology combined with field measurement. Ten gully morphological characteristics were extracted from the digital orthophoto map (DOM) and digital elevation model (DEM) generated by UAV images, including gully length (L), circumference (C), plane area (PA), surface area (SA), volume (V), depth (D), top width (TW), mean width (MW), cross-sectional area (CSA), and ratio of top width to depth (TW/D). The morphological characteristics of 30 reachable gullies were measured by a real time kinematic (RTK) to validate the parameters extracted from the UAV images. The topographic thresholds were determined based on the local slope gradient (S) and upland drainage area (A), using a dataset of 365 gully heads and their corresponding land-use types. The results show that the mean absolute percentage errors (MAPE) of the 2D and 3D gully characteristics are less than 10% and 20%, respectively, demonstrating a high accuracy of gully characteristic extraction from UAV images. Gully V is significantly related to the other nine parameters. Significant power functions were fitted between V, and L, C, PA, and SA. The gully volume could be well-estimated by SA (V = 0.212 SA<sup<0.982</sup<), with a R<sup<2</sup< of 0.99. For all land-use types, the topographic threshold could be described as S = 0.61 A<sup<0.48</sup<, implying that water erosion is the dominant process controlling gully erosion in this region. The topographic threshold is land-use-dependent, and shrubland is hardest for gully incision, followed by grassland and cropland. The results are helpful to rapidly estimate gully erosion, and identify the areas for gully erosion mitigation in small watershed. gully erosion gully volume gully initiation slope gradient land-use type Science Q Guanghui Zhang verfasserin aut Chengshu Wang verfasserin aut Shukun Xing verfasserin aut In Remote Sensing MDPI AG, 2009 14(2022), 15, p 3529 (DE-627)608937916 (DE-600)2513863-7 20724292 nnns volume:14 year:2022 number:15, p 3529 https://doi.org/10.3390/rs14153529 kostenfrei https://doaj.org/article/dd8068f8039c4dbc92b3e8f4071db6f8 kostenfrei https://www.mdpi.com/2072-4292/14/15/3529 kostenfrei https://doaj.org/toc/2072-4292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 14 2022 15, p 3529
language	English
source	In Remote Sensing 14(2022), 15, p 3529 volume:14 year:2022 number:15, p 3529
sourceStr	In Remote Sensing 14(2022), 15, p 3529 volume:14 year:2022 number:15, p 3529
format_phy_str_mv	Article
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topic_facet	gully erosion gully volume gully initiation slope gradient land-use type Science Q
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authorswithroles_txt_mv	Ziguan Wang @@aut@@ Guanghui Zhang @@aut@@ Chengshu Wang @@aut@@ Shukun Xing @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
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author	Ziguan Wang
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topic_title	Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau gully erosion gully volume gully initiation slope gradient land-use type
topic	misc gully erosion misc gully volume misc gully initiation misc slope gradient misc land-use type misc Science misc Q
topic_unstemmed	misc gully erosion misc gully volume misc gully initiation misc slope gradient misc land-use type misc Science misc Q
topic_browse	misc gully erosion misc gully volume misc gully initiation misc slope gradient misc land-use type misc Science misc Q
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
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title	Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau
ctrlnum	(DE-627)DOAJ034531343 (DE-599)DOAJdd8068f8039c4dbc92b3e8f4071db6f8
title_full	Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau
author_sort	Ziguan Wang
journal	Remote Sensing
journalStr	Remote Sensing
lang_code	eng
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publishDateSort	2022
contenttype_str_mv	txt
author_browse	Ziguan Wang Guanghui Zhang Chengshu Wang Shukun Xing
container_volume	14
format_se	Elektronische Aufsätze
author-letter	Ziguan Wang
doi_str_mv	10.3390/rs14153529
author2-role	verfasserin
title_sort	gully morphological characteristics and topographic threshold determined by uav in a small watershed on the loess plateau
title_auth	Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau
abstract	Gully erosion is an important sediment source in small watershed, and causes severe land degradation, particularly in semi-arid regions. Accurately measuring gully morphological characteristics, and determining its topographic threshold, are vital for gully erosion simulation and control. In this study, 910 gullies were visually interpreted by unmanned aerial vehicle (UAV) technology combined with field measurement. Ten gully morphological characteristics were extracted from the digital orthophoto map (DOM) and digital elevation model (DEM) generated by UAV images, including gully length (L), circumference (C), plane area (PA), surface area (SA), volume (V), depth (D), top width (TW), mean width (MW), cross-sectional area (CSA), and ratio of top width to depth (TW/D). The morphological characteristics of 30 reachable gullies were measured by a real time kinematic (RTK) to validate the parameters extracted from the UAV images. The topographic thresholds were determined based on the local slope gradient (S) and upland drainage area (A), using a dataset of 365 gully heads and their corresponding land-use types. The results show that the mean absolute percentage errors (MAPE) of the 2D and 3D gully characteristics are less than 10% and 20%, respectively, demonstrating a high accuracy of gully characteristic extraction from UAV images. Gully V is significantly related to the other nine parameters. Significant power functions were fitted between V, and L, C, PA, and SA. The gully volume could be well-estimated by SA (V = 0.212 SA<sup<0.982</sup<), with a R<sup<2</sup< of 0.99. For all land-use types, the topographic threshold could be described as S = 0.61 A<sup<0.48</sup<, implying that water erosion is the dominant process controlling gully erosion in this region. The topographic threshold is land-use-dependent, and shrubland is hardest for gully incision, followed by grassland and cropland. The results are helpful to rapidly estimate gully erosion, and identify the areas for gully erosion mitigation in small watershed.
abstractGer	Gully erosion is an important sediment source in small watershed, and causes severe land degradation, particularly in semi-arid regions. Accurately measuring gully morphological characteristics, and determining its topographic threshold, are vital for gully erosion simulation and control. In this study, 910 gullies were visually interpreted by unmanned aerial vehicle (UAV) technology combined with field measurement. Ten gully morphological characteristics were extracted from the digital orthophoto map (DOM) and digital elevation model (DEM) generated by UAV images, including gully length (L), circumference (C), plane area (PA), surface area (SA), volume (V), depth (D), top width (TW), mean width (MW), cross-sectional area (CSA), and ratio of top width to depth (TW/D). The morphological characteristics of 30 reachable gullies were measured by a real time kinematic (RTK) to validate the parameters extracted from the UAV images. The topographic thresholds were determined based on the local slope gradient (S) and upland drainage area (A), using a dataset of 365 gully heads and their corresponding land-use types. The results show that the mean absolute percentage errors (MAPE) of the 2D and 3D gully characteristics are less than 10% and 20%, respectively, demonstrating a high accuracy of gully characteristic extraction from UAV images. Gully V is significantly related to the other nine parameters. Significant power functions were fitted between V, and L, C, PA, and SA. The gully volume could be well-estimated by SA (V = 0.212 SA<sup<0.982</sup<), with a R<sup<2</sup< of 0.99. For all land-use types, the topographic threshold could be described as S = 0.61 A<sup<0.48</sup<, implying that water erosion is the dominant process controlling gully erosion in this region. The topographic threshold is land-use-dependent, and shrubland is hardest for gully incision, followed by grassland and cropland. The results are helpful to rapidly estimate gully erosion, and identify the areas for gully erosion mitigation in small watershed.
abstract_unstemmed	Gully erosion is an important sediment source in small watershed, and causes severe land degradation, particularly in semi-arid regions. Accurately measuring gully morphological characteristics, and determining its topographic threshold, are vital for gully erosion simulation and control. In this study, 910 gullies were visually interpreted by unmanned aerial vehicle (UAV) technology combined with field measurement. Ten gully morphological characteristics were extracted from the digital orthophoto map (DOM) and digital elevation model (DEM) generated by UAV images, including gully length (L), circumference (C), plane area (PA), surface area (SA), volume (V), depth (D), top width (TW), mean width (MW), cross-sectional area (CSA), and ratio of top width to depth (TW/D). The morphological characteristics of 30 reachable gullies were measured by a real time kinematic (RTK) to validate the parameters extracted from the UAV images. The topographic thresholds were determined based on the local slope gradient (S) and upland drainage area (A), using a dataset of 365 gully heads and their corresponding land-use types. The results show that the mean absolute percentage errors (MAPE) of the 2D and 3D gully characteristics are less than 10% and 20%, respectively, demonstrating a high accuracy of gully characteristic extraction from UAV images. Gully V is significantly related to the other nine parameters. Significant power functions were fitted between V, and L, C, PA, and SA. The gully volume could be well-estimated by SA (V = 0.212 SA<sup<0.982</sup<), with a R<sup<2</sup< of 0.99. For all land-use types, the topographic threshold could be described as S = 0.61 A<sup<0.48</sup<, implying that water erosion is the dominant process controlling gully erosion in this region. The topographic threshold is land-use-dependent, and shrubland is hardest for gully incision, followed by grassland and cropland. The results are helpful to rapidly estimate gully erosion, and identify the areas for gully erosion mitigation in small watershed.
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700
container_issue	15, p 3529
title_short	Gully Morphological Characteristics and Topographic Threshold Determined by UAV in a Small Watershed on the Loess Plateau
url	https://doi.org/10.3390/rs14153529 https://doaj.org/article/dd8068f8039c4dbc92b3e8f4071db6f8 https://www.mdpi.com/2072-4292/14/15/3529 https://doaj.org/toc/2072-4292
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up_date	2024-07-03T23:37:04.502Z
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