Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess
Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking pl...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yang, Yang [verfasserIn] Shi, Yangzi [verfasserIn] Liang, Xiaozhen [verfasserIn] Huang, Tingting [verfasserIn] Fu, Suhua [verfasserIn] Liu, Baoyuan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Geomorphology - Amsterdam [u.a.] : Elsevier Science, 1987, 385 |
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| Übergeordnetes Werk: |
volume:385 |
| DOI / URN: |
10.1016/j.geomorph.2021.107734 |
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| Katalog-ID: |
ELV005977479 |
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| 245 | 1 | 0 | |a Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess |
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| 520 | |a Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking place in the loess that is vulnerable to erosion. The objective was to examine the accuracy and limits of SfM in quantifying rill and interrill erosion occurring in a typical loess during consecutive rainfall simulations. The loess collected from the plough layer of a cropland in the Loess Plateau of China was packed into a 200 × 100 × 35 cm runoff plot and received simulated rainfall at the intensity of 90 mm h−1 on three slopes of 10°, 15° and 20°. A portable laser scanner (LS) and SfM were used to measure soil surface at every 30 min until rill emergence and after another 30-min rainfall aiming to study rill development. Meanwhile, runoff and sediment samples were collected at the plot outlet and oven-dried to calculate the soil loss. The results showed that the elevation differences calculated by subtracting digital elevation models (DEMs) derived by SfM and LS mainly fell between −2 and 2 mm. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) were mostly smaller than 3 mm, suggesting accurate soil erosion measurement made by SfM at the plot scale. Considering the surface variations, the relative RMSE and MAE, i.e., dividing over the mean elevations measured by LS, were found to decrease as soil erosion proceeded and rills emerged. The rill morphology comparison, however, suggested a better fit of SfM for rills larger than 9 cm in maximum surface width, 6.0 × 10−2 m2 in area and 0.9 × 10−3 m3 in volume. In accordance with DEM comparisons, the soil losses estimated by SfM and LS were statistically similar. Nevertheless, these values were much greater than the amount of sediments collected for the early simulation runs, which might be explained primarily by the settling of loess when subject to heavy rainfall. But as rainfall continued and rills further developed, the misestimations made by LS and SfM remarkably dropped, i.e., from −17.8% to 4.9% and from −18.1% to 4.3%, respectively. These findings suggest a generally higher accuracy of SfM in quantifying rill erosion with more fluctuating soil surface than in interrill erosion measurement. | ||
| 650 | 4 | |a Structure from motion (SfM) photogrammetry | |
| 650 | 4 | |a Rill and interrill erosion | |
| 650 | 4 | |a Loess | |
| 650 | 4 | |a Laser scanning (LS) | |
| 650 | 4 | |a Rainfall simulation | |
| 700 | 1 | |a Shi, Yangzi |e verfasserin |4 aut | |
| 700 | 1 | |a Liang, Xiaozhen |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Tingting |e verfasserin |4 aut | |
| 700 | 1 | |a Fu, Suhua |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Baoyuan |e verfasserin |4 aut | |
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10.1016/j.geomorph.2021.107734 doi (DE-627)ELV005977479 (ELSEVIER)S0169-555X(21)00142-2 DE-627 ger DE-627 rda eng 910 DE-600 38.45 bkl Yang, Yang verfasserin aut Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking place in the loess that is vulnerable to erosion. The objective was to examine the accuracy and limits of SfM in quantifying rill and interrill erosion occurring in a typical loess during consecutive rainfall simulations. The loess collected from the plough layer of a cropland in the Loess Plateau of China was packed into a 200 × 100 × 35 cm runoff plot and received simulated rainfall at the intensity of 90 mm h−1 on three slopes of 10°, 15° and 20°. A portable laser scanner (LS) and SfM were used to measure soil surface at every 30 min until rill emergence and after another 30-min rainfall aiming to study rill development. Meanwhile, runoff and sediment samples were collected at the plot outlet and oven-dried to calculate the soil loss. The results showed that the elevation differences calculated by subtracting digital elevation models (DEMs) derived by SfM and LS mainly fell between −2 and 2 mm. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) were mostly smaller than 3 mm, suggesting accurate soil erosion measurement made by SfM at the plot scale. Considering the surface variations, the relative RMSE and MAE, i.e., dividing over the mean elevations measured by LS, were found to decrease as soil erosion proceeded and rills emerged. The rill morphology comparison, however, suggested a better fit of SfM for rills larger than 9 cm in maximum surface width, 6.0 × 10−2 m2 in area and 0.9 × 10−3 m3 in volume. In accordance with DEM comparisons, the soil losses estimated by SfM and LS were statistically similar. Nevertheless, these values were much greater than the amount of sediments collected for the early simulation runs, which might be explained primarily by the settling of loess when subject to heavy rainfall. But as rainfall continued and rills further developed, the misestimations made by LS and SfM remarkably dropped, i.e., from −17.8% to 4.9% and from −18.1% to 4.3%, respectively. These findings suggest a generally higher accuracy of SfM in quantifying rill erosion with more fluctuating soil surface than in interrill erosion measurement. Structure from motion (SfM) photogrammetry Rill and interrill erosion Loess Laser scanning (LS) Rainfall simulation Shi, Yangzi verfasserin aut Liang, Xiaozhen verfasserin aut Huang, Tingting verfasserin aut Fu, Suhua verfasserin aut Liu, Baoyuan verfasserin aut Enthalten in Geomorphology Amsterdam [u.a.] : Elsevier Science, 1987 385 Online-Ressource (DE-627)320412997 (DE-600)2001554-9 (DE-576)091017661 1872-695X nnns volume:385 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.45 Geomorphologie AR 385 |
| spelling |
10.1016/j.geomorph.2021.107734 doi (DE-627)ELV005977479 (ELSEVIER)S0169-555X(21)00142-2 DE-627 ger DE-627 rda eng 910 DE-600 38.45 bkl Yang, Yang verfasserin aut Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking place in the loess that is vulnerable to erosion. The objective was to examine the accuracy and limits of SfM in quantifying rill and interrill erosion occurring in a typical loess during consecutive rainfall simulations. The loess collected from the plough layer of a cropland in the Loess Plateau of China was packed into a 200 × 100 × 35 cm runoff plot and received simulated rainfall at the intensity of 90 mm h−1 on three slopes of 10°, 15° and 20°. A portable laser scanner (LS) and SfM were used to measure soil surface at every 30 min until rill emergence and after another 30-min rainfall aiming to study rill development. Meanwhile, runoff and sediment samples were collected at the plot outlet and oven-dried to calculate the soil loss. The results showed that the elevation differences calculated by subtracting digital elevation models (DEMs) derived by SfM and LS mainly fell between −2 and 2 mm. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) were mostly smaller than 3 mm, suggesting accurate soil erosion measurement made by SfM at the plot scale. Considering the surface variations, the relative RMSE and MAE, i.e., dividing over the mean elevations measured by LS, were found to decrease as soil erosion proceeded and rills emerged. The rill morphology comparison, however, suggested a better fit of SfM for rills larger than 9 cm in maximum surface width, 6.0 × 10−2 m2 in area and 0.9 × 10−3 m3 in volume. In accordance with DEM comparisons, the soil losses estimated by SfM and LS were statistically similar. Nevertheless, these values were much greater than the amount of sediments collected for the early simulation runs, which might be explained primarily by the settling of loess when subject to heavy rainfall. But as rainfall continued and rills further developed, the misestimations made by LS and SfM remarkably dropped, i.e., from −17.8% to 4.9% and from −18.1% to 4.3%, respectively. These findings suggest a generally higher accuracy of SfM in quantifying rill erosion with more fluctuating soil surface than in interrill erosion measurement. Structure from motion (SfM) photogrammetry Rill and interrill erosion Loess Laser scanning (LS) Rainfall simulation Shi, Yangzi verfasserin aut Liang, Xiaozhen verfasserin aut Huang, Tingting verfasserin aut Fu, Suhua verfasserin aut Liu, Baoyuan verfasserin aut Enthalten in Geomorphology Amsterdam [u.a.] : Elsevier Science, 1987 385 Online-Ressource (DE-627)320412997 (DE-600)2001554-9 (DE-576)091017661 1872-695X nnns volume:385 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.45 Geomorphologie AR 385 |
| allfields_unstemmed |
10.1016/j.geomorph.2021.107734 doi (DE-627)ELV005977479 (ELSEVIER)S0169-555X(21)00142-2 DE-627 ger DE-627 rda eng 910 DE-600 38.45 bkl Yang, Yang verfasserin aut Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking place in the loess that is vulnerable to erosion. The objective was to examine the accuracy and limits of SfM in quantifying rill and interrill erosion occurring in a typical loess during consecutive rainfall simulations. The loess collected from the plough layer of a cropland in the Loess Plateau of China was packed into a 200 × 100 × 35 cm runoff plot and received simulated rainfall at the intensity of 90 mm h−1 on three slopes of 10°, 15° and 20°. A portable laser scanner (LS) and SfM were used to measure soil surface at every 30 min until rill emergence and after another 30-min rainfall aiming to study rill development. Meanwhile, runoff and sediment samples were collected at the plot outlet and oven-dried to calculate the soil loss. The results showed that the elevation differences calculated by subtracting digital elevation models (DEMs) derived by SfM and LS mainly fell between −2 and 2 mm. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) were mostly smaller than 3 mm, suggesting accurate soil erosion measurement made by SfM at the plot scale. Considering the surface variations, the relative RMSE and MAE, i.e., dividing over the mean elevations measured by LS, were found to decrease as soil erosion proceeded and rills emerged. The rill morphology comparison, however, suggested a better fit of SfM for rills larger than 9 cm in maximum surface width, 6.0 × 10−2 m2 in area and 0.9 × 10−3 m3 in volume. In accordance with DEM comparisons, the soil losses estimated by SfM and LS were statistically similar. Nevertheless, these values were much greater than the amount of sediments collected for the early simulation runs, which might be explained primarily by the settling of loess when subject to heavy rainfall. But as rainfall continued and rills further developed, the misestimations made by LS and SfM remarkably dropped, i.e., from −17.8% to 4.9% and from −18.1% to 4.3%, respectively. These findings suggest a generally higher accuracy of SfM in quantifying rill erosion with more fluctuating soil surface than in interrill erosion measurement. Structure from motion (SfM) photogrammetry Rill and interrill erosion Loess Laser scanning (LS) Rainfall simulation Shi, Yangzi verfasserin aut Liang, Xiaozhen verfasserin aut Huang, Tingting verfasserin aut Fu, Suhua verfasserin aut Liu, Baoyuan verfasserin aut Enthalten in Geomorphology Amsterdam [u.a.] : Elsevier Science, 1987 385 Online-Ressource (DE-627)320412997 (DE-600)2001554-9 (DE-576)091017661 1872-695X nnns volume:385 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.45 Geomorphologie AR 385 |
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10.1016/j.geomorph.2021.107734 doi (DE-627)ELV005977479 (ELSEVIER)S0169-555X(21)00142-2 DE-627 ger DE-627 rda eng 910 DE-600 38.45 bkl Yang, Yang verfasserin aut Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking place in the loess that is vulnerable to erosion. The objective was to examine the accuracy and limits of SfM in quantifying rill and interrill erosion occurring in a typical loess during consecutive rainfall simulations. The loess collected from the plough layer of a cropland in the Loess Plateau of China was packed into a 200 × 100 × 35 cm runoff plot and received simulated rainfall at the intensity of 90 mm h−1 on three slopes of 10°, 15° and 20°. A portable laser scanner (LS) and SfM were used to measure soil surface at every 30 min until rill emergence and after another 30-min rainfall aiming to study rill development. Meanwhile, runoff and sediment samples were collected at the plot outlet and oven-dried to calculate the soil loss. The results showed that the elevation differences calculated by subtracting digital elevation models (DEMs) derived by SfM and LS mainly fell between −2 and 2 mm. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) were mostly smaller than 3 mm, suggesting accurate soil erosion measurement made by SfM at the plot scale. Considering the surface variations, the relative RMSE and MAE, i.e., dividing over the mean elevations measured by LS, were found to decrease as soil erosion proceeded and rills emerged. The rill morphology comparison, however, suggested a better fit of SfM for rills larger than 9 cm in maximum surface width, 6.0 × 10−2 m2 in area and 0.9 × 10−3 m3 in volume. In accordance with DEM comparisons, the soil losses estimated by SfM and LS were statistically similar. Nevertheless, these values were much greater than the amount of sediments collected for the early simulation runs, which might be explained primarily by the settling of loess when subject to heavy rainfall. But as rainfall continued and rills further developed, the misestimations made by LS and SfM remarkably dropped, i.e., from −17.8% to 4.9% and from −18.1% to 4.3%, respectively. These findings suggest a generally higher accuracy of SfM in quantifying rill erosion with more fluctuating soil surface than in interrill erosion measurement. Structure from motion (SfM) photogrammetry Rill and interrill erosion Loess Laser scanning (LS) Rainfall simulation Shi, Yangzi verfasserin aut Liang, Xiaozhen verfasserin aut Huang, Tingting verfasserin aut Fu, Suhua verfasserin aut Liu, Baoyuan verfasserin aut Enthalten in Geomorphology Amsterdam [u.a.] : Elsevier Science, 1987 385 Online-Ressource (DE-627)320412997 (DE-600)2001554-9 (DE-576)091017661 1872-695X nnns volume:385 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.45 Geomorphologie AR 385 |
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10.1016/j.geomorph.2021.107734 doi (DE-627)ELV005977479 (ELSEVIER)S0169-555X(21)00142-2 DE-627 ger DE-627 rda eng 910 DE-600 38.45 bkl Yang, Yang verfasserin aut Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking place in the loess that is vulnerable to erosion. The objective was to examine the accuracy and limits of SfM in quantifying rill and interrill erosion occurring in a typical loess during consecutive rainfall simulations. The loess collected from the plough layer of a cropland in the Loess Plateau of China was packed into a 200 × 100 × 35 cm runoff plot and received simulated rainfall at the intensity of 90 mm h−1 on three slopes of 10°, 15° and 20°. A portable laser scanner (LS) and SfM were used to measure soil surface at every 30 min until rill emergence and after another 30-min rainfall aiming to study rill development. Meanwhile, runoff and sediment samples were collected at the plot outlet and oven-dried to calculate the soil loss. The results showed that the elevation differences calculated by subtracting digital elevation models (DEMs) derived by SfM and LS mainly fell between −2 and 2 mm. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) were mostly smaller than 3 mm, suggesting accurate soil erosion measurement made by SfM at the plot scale. Considering the surface variations, the relative RMSE and MAE, i.e., dividing over the mean elevations measured by LS, were found to decrease as soil erosion proceeded and rills emerged. The rill morphology comparison, however, suggested a better fit of SfM for rills larger than 9 cm in maximum surface width, 6.0 × 10−2 m2 in area and 0.9 × 10−3 m3 in volume. In accordance with DEM comparisons, the soil losses estimated by SfM and LS were statistically similar. Nevertheless, these values were much greater than the amount of sediments collected for the early simulation runs, which might be explained primarily by the settling of loess when subject to heavy rainfall. But as rainfall continued and rills further developed, the misestimations made by LS and SfM remarkably dropped, i.e., from −17.8% to 4.9% and from −18.1% to 4.3%, respectively. These findings suggest a generally higher accuracy of SfM in quantifying rill erosion with more fluctuating soil surface than in interrill erosion measurement. Structure from motion (SfM) photogrammetry Rill and interrill erosion Loess Laser scanning (LS) Rainfall simulation Shi, Yangzi verfasserin aut Liang, Xiaozhen verfasserin aut Huang, Tingting verfasserin aut Fu, Suhua verfasserin aut Liu, Baoyuan verfasserin aut Enthalten in Geomorphology Amsterdam [u.a.] : Elsevier Science, 1987 385 Online-Ressource (DE-627)320412997 (DE-600)2001554-9 (DE-576)091017661 1872-695X nnns volume:385 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.45 Geomorphologie AR 385 |
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Structure from motion (SfM) photogrammetry Rill and interrill erosion Loess Laser scanning (LS) Rainfall simulation |
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Yang, Yang @@aut@@ Shi, Yangzi @@aut@@ Liang, Xiaozhen @@aut@@ Huang, Tingting @@aut@@ Fu, Suhua @@aut@@ Liu, Baoyuan @@aut@@ |
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Yang, Yang |
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Yang, Yang ddc 910 bkl 38.45 misc Structure from motion (SfM) photogrammetry misc Rill and interrill erosion misc Loess misc Laser scanning (LS) misc Rainfall simulation Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess |
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910 DE-600 38.45 bkl Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess Structure from motion (SfM) photogrammetry Rill and interrill erosion Loess Laser scanning (LS) Rainfall simulation |
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ddc 910 bkl 38.45 misc Structure from motion (SfM) photogrammetry misc Rill and interrill erosion misc Loess misc Laser scanning (LS) misc Rainfall simulation |
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ddc 910 bkl 38.45 misc Structure from motion (SfM) photogrammetry misc Rill and interrill erosion misc Loess misc Laser scanning (LS) misc Rainfall simulation |
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ddc 910 bkl 38.45 misc Structure from motion (SfM) photogrammetry misc Rill and interrill erosion misc Loess misc Laser scanning (LS) misc Rainfall simulation |
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Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess |
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Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess |
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Yang, Yang |
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Geomorphology |
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Yang, Yang Shi, Yangzi Liang, Xiaozhen Huang, Tingting Fu, Suhua Liu, Baoyuan |
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10.1016/j.geomorph.2021.107734 |
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910 |
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evaluation of structure from motion (sfm) photogrammetry on the measurement of rill and interrill erosion in a typical loess |
| title_auth |
Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess |
| abstract |
Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking place in the loess that is vulnerable to erosion. The objective was to examine the accuracy and limits of SfM in quantifying rill and interrill erosion occurring in a typical loess during consecutive rainfall simulations. The loess collected from the plough layer of a cropland in the Loess Plateau of China was packed into a 200 × 100 × 35 cm runoff plot and received simulated rainfall at the intensity of 90 mm h−1 on three slopes of 10°, 15° and 20°. A portable laser scanner (LS) and SfM were used to measure soil surface at every 30 min until rill emergence and after another 30-min rainfall aiming to study rill development. Meanwhile, runoff and sediment samples were collected at the plot outlet and oven-dried to calculate the soil loss. The results showed that the elevation differences calculated by subtracting digital elevation models (DEMs) derived by SfM and LS mainly fell between −2 and 2 mm. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) were mostly smaller than 3 mm, suggesting accurate soil erosion measurement made by SfM at the plot scale. Considering the surface variations, the relative RMSE and MAE, i.e., dividing over the mean elevations measured by LS, were found to decrease as soil erosion proceeded and rills emerged. The rill morphology comparison, however, suggested a better fit of SfM for rills larger than 9 cm in maximum surface width, 6.0 × 10−2 m2 in area and 0.9 × 10−3 m3 in volume. In accordance with DEM comparisons, the soil losses estimated by SfM and LS were statistically similar. Nevertheless, these values were much greater than the amount of sediments collected for the early simulation runs, which might be explained primarily by the settling of loess when subject to heavy rainfall. But as rainfall continued and rills further developed, the misestimations made by LS and SfM remarkably dropped, i.e., from −17.8% to 4.9% and from −18.1% to 4.3%, respectively. These findings suggest a generally higher accuracy of SfM in quantifying rill erosion with more fluctuating soil surface than in interrill erosion measurement. |
| abstractGer |
Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking place in the loess that is vulnerable to erosion. The objective was to examine the accuracy and limits of SfM in quantifying rill and interrill erosion occurring in a typical loess during consecutive rainfall simulations. The loess collected from the plough layer of a cropland in the Loess Plateau of China was packed into a 200 × 100 × 35 cm runoff plot and received simulated rainfall at the intensity of 90 mm h−1 on three slopes of 10°, 15° and 20°. A portable laser scanner (LS) and SfM were used to measure soil surface at every 30 min until rill emergence and after another 30-min rainfall aiming to study rill development. Meanwhile, runoff and sediment samples were collected at the plot outlet and oven-dried to calculate the soil loss. The results showed that the elevation differences calculated by subtracting digital elevation models (DEMs) derived by SfM and LS mainly fell between −2 and 2 mm. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) were mostly smaller than 3 mm, suggesting accurate soil erosion measurement made by SfM at the plot scale. Considering the surface variations, the relative RMSE and MAE, i.e., dividing over the mean elevations measured by LS, were found to decrease as soil erosion proceeded and rills emerged. The rill morphology comparison, however, suggested a better fit of SfM for rills larger than 9 cm in maximum surface width, 6.0 × 10−2 m2 in area and 0.9 × 10−3 m3 in volume. In accordance with DEM comparisons, the soil losses estimated by SfM and LS were statistically similar. Nevertheless, these values were much greater than the amount of sediments collected for the early simulation runs, which might be explained primarily by the settling of loess when subject to heavy rainfall. But as rainfall continued and rills further developed, the misestimations made by LS and SfM remarkably dropped, i.e., from −17.8% to 4.9% and from −18.1% to 4.3%, respectively. These findings suggest a generally higher accuracy of SfM in quantifying rill erosion with more fluctuating soil surface than in interrill erosion measurement. |
| abstract_unstemmed |
Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking place in the loess that is vulnerable to erosion. The objective was to examine the accuracy and limits of SfM in quantifying rill and interrill erosion occurring in a typical loess during consecutive rainfall simulations. The loess collected from the plough layer of a cropland in the Loess Plateau of China was packed into a 200 × 100 × 35 cm runoff plot and received simulated rainfall at the intensity of 90 mm h−1 on three slopes of 10°, 15° and 20°. A portable laser scanner (LS) and SfM were used to measure soil surface at every 30 min until rill emergence and after another 30-min rainfall aiming to study rill development. Meanwhile, runoff and sediment samples were collected at the plot outlet and oven-dried to calculate the soil loss. The results showed that the elevation differences calculated by subtracting digital elevation models (DEMs) derived by SfM and LS mainly fell between −2 and 2 mm. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) were mostly smaller than 3 mm, suggesting accurate soil erosion measurement made by SfM at the plot scale. Considering the surface variations, the relative RMSE and MAE, i.e., dividing over the mean elevations measured by LS, were found to decrease as soil erosion proceeded and rills emerged. The rill morphology comparison, however, suggested a better fit of SfM for rills larger than 9 cm in maximum surface width, 6.0 × 10−2 m2 in area and 0.9 × 10−3 m3 in volume. In accordance with DEM comparisons, the soil losses estimated by SfM and LS were statistically similar. Nevertheless, these values were much greater than the amount of sediments collected for the early simulation runs, which might be explained primarily by the settling of loess when subject to heavy rainfall. But as rainfall continued and rills further developed, the misestimations made by LS and SfM remarkably dropped, i.e., from −17.8% to 4.9% and from −18.1% to 4.3%, respectively. These findings suggest a generally higher accuracy of SfM in quantifying rill erosion with more fluctuating soil surface than in interrill erosion measurement. |
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Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess |
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