scholarly journals Quantifying small-magnitude soil erosion: Geomorphic change detection at plot scale

2017 ◽  
Vol 29 (3) ◽  
pp. 825-834 ◽  
Author(s):  
Matilde Balaguer-Puig ◽  
Ángel Marqués-Mateu ◽  
José Luis Lerma ◽  
Sara Ibáñez-Asensio
Keyword(s):  
Soil Erosion ◽  
Change Detection ◽  
Small Magnitude ◽  
Geomorphic Change Detection

scholarly journals Comparing High Accuracy t-LiDAR and UAV-SfM Derived Point Clouds for Geomorphological Change Detection

2021 ◽  
Vol 10 (6) ◽  
pp. 367
Author(s):  
Simoni Alexiou ◽  
Georgios Deligiannakis ◽  
Aggelos Pallikarakis ◽  
Ioannis Papanikolaou ◽  
Emmanouil Psomiadis ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Change Detection ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Mean Value ◽  
Detection Methods ◽  
Mountainous Catchments ◽  
Aerial Vehicle ◽  
Soil Erosion Assessment

Analysis of two small semi-mountainous catchments in central Evia island, Greece, highlights the advantages of Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanning (TLS) based change detection methods. We use point clouds derived by both methods in two sites (S1 & S2), to analyse the effects of a recent wildfire on soil erosion. Results indicate that topsoil’s movements in the order of a few centimetres, occurring within a few months, can be estimated. Erosion at S2 is precisely delineated by both methods, yielding a mean value of 1.5 cm within four months. At S1, UAV-derived point clouds’ comparison quantifies annual soil erosion more accurately, showing a maximum annual erosion rate of 48 cm. UAV-derived point clouds appear to be more accurate for channel erosion display and measurement, while the slope wash is more precisely estimated using TLS. Analysis of Point Cloud time series is a reliable and fast process for soil erosion assessment, especially in rapidly changing environments with difficult access for direct measurement methods. This study will contribute to proper georesource management by defining the best-suited methodology for soil erosion assessment after a wildfire in Mediterranean environments.

Assessment of gully development using geomorphic change detection between pre- and post-urbanization scenarios

2020 ◽  
Vol 79 (10) ◽  
Author(s):  
Anesmar Olino de Albuquerque ◽  
Osmar Abílio de Carvalho Júnior ◽  
Renato Fontes Guimarães ◽  
Roberto Arnaldo Trancoso Gomes ◽  
Potira Meirelles Hermuche
Keyword(s):  
Change Detection ◽  
Geomorphic Change Detection

Geomorphic change detection using historic maps and DEM differencing: The temporal dimension of geospatial analysis

Geomorphology ◽  
2012 ◽  
Vol 137 (1) ◽  
pp. 181-198 ◽  
Author(s):  
L. Allan James ◽  
Michael E. Hodgson ◽  
Subhajit Ghoshal ◽  
Mary Megison Latiolais
Keyword(s):  
Change Detection ◽  
Geospatial Analysis ◽  
Temporal Dimension ◽  
Geomorphic Change Detection ◽  
Historic Maps ◽  
Dem Differencing

scholarly journals Dynamic Analysis Of Soil Erosion-Based Watershed Health

2019 ◽  
Vol 12 (3) ◽  
pp. 43-59 ◽  
Author(s):  
Zeinab Hazbavi ◽  
Seyed Hamidreza Sadeghi ◽  
Mehdi Gholamalifard
Keyword(s):  
Soil Erosion ◽  
Change Detection ◽  
Geometric Mean ◽  
Risk Indicators ◽  
Spatiotemporal Variability ◽  
Health Index ◽  
Environmental Pressures ◽  
Factors Affecting ◽  
Detection Analysis ◽  
Watershed Health

Accelerated soil erosion is one of the most important detrimental factors affecting the quality of the watershed health. Due to different environmental pressures and drivers, the effort is needed for ecological health and resilience assessment in regards to erosion changeability. However, this important subject has not been adequately studied yet. Towards this, in the present research, an innovative approach was developed for conceptualizing the watershed health dynamics in viewpoint of soil erosion. A risk-based study was conducted to quantitatively characterize the spatiotemporal variability of erosion-based health in an industrialized watershed i.e., the Shazand Watershed using the conceptual reliability, resilience and vulnerability (RelResVul) framework for four node years of 1986, 1998, 2008 and 2014. To this end, the soil erosion was estimated at monthly scale in 24 sub-watersheds by applying the Revised Universal Soil Loss Equation (RUSLE). The RelResVul indicators were then computed according to the threshold defined for the study watershed. A geometric mean was used to combine the three risk indicators and the erosion-based watershed health index was ultimately calculated for each study sub-watershed. Additionally, the change detection analysis was conducted over the years of 1986 to 2014. According to the results of erosion-based the RelResVul indices, very healthy, healthy, moderately healthy, unhealthy and very un-healthy conditions in the Shazand Watershed were respectively distributed over some 67, 25, zero, zero and eight percent for 1986; 50, 13, eight, zero and 29 % for 1998; 71, eight, 83, zero, zero and eight percent for 2008 and finally 71, zero, 17, zero and 12 % for 2014. The results of change detection revealed an oscillating trend of erosion-based watershed health index during the whole study period (1986 -2014). So that, during periods of 1986-1998, 1986-2008 and 1986-2014, the watershed health decreased at tune of 23, 13 and six percent, respectively. Whilst, the watershed health improved during study periods of 1998-2008 (13 %), 2008-2014 (eight percent) and 1998-2014 (22 %). The results also identified ‘hot spots’ of the most important index of land degradation and ‘bright spots’ of land improvement in the Shazand Watershed.The proposed approach would provide a sustainable framework supporting decision makers to comprehend health-related soil erosion targets according to the integrated watershed management plans.

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