How does DEM error impact the optimal grid resolution of soil evolution simulation?

2021 ◽  
Author(s):  
Yangyang Liu ◽  
Jintao Liu ◽  
Wei Zhao
Keyword(s):  
Grid Resolution ◽  
Slope Aspect ◽  
Soil Thickness ◽  
Simulation Accuracy ◽  
Correlation Curve ◽  
Evolution Simulation ◽  
Macro Scale ◽  
Two Factors ◽  
Thickness Prediction ◽  
Elevation Model

<p>The soil thickness is the key controlling factor of local hydrology and geomorphologic characteristics. The accuracy, reliability and coverage of soil thickness map are required for reliable application. Though with quite distinct structures, models for simulating soil thickness take modern topographic data (normally digital elevation model, DEM) as one of the most important inputs. Understanding the effect of grid resolution on soil thickness prediction and selecting an appropriate resolution is crucial for the macro-scale modeling. In this study, we further explored the relationship between topographic resolution and simulation accuracy of soil thickness, and propose a new method to determine the optimal simulation resolution. A series of abstract hillslopes with different terrain noise and terrain complexity were construct and different resolutions of DEM were generated. We used a simple geomorphic based model to calculate topographic index (slope, aspect and curvature) and soil thickness. The results show that the truncation error and noise of DEM will propagate during the simulation process. Furtherly, the correlation curve between DEM resolution and the simulation error of soil thickness is a hook curve. The shape of the curve is mainly controlled by two factors, terrain noise and terrain complexity. By fitting the correlation curve of all hillslopes, the curve can be predicted by them, and the resolution corresponding to the error minimum be found out, which can be called the optimal simulation resolution of the soil thickness prediction model.</p>

scholarly journals A New Approach to the Quality Control of Slope and Aspect Classes Derived from Digital Elevation Models

2021 ◽  
Vol 13 (11) ◽  
pp. 2069
Author(s):  
M. V. Alba-Fernández ◽  
F. J. Ariza-López ◽  
M. D. Jiménez-Gamero
Keyword(s):  
Quality Control ◽  
Hypothesis Test ◽  
Simulated Data ◽  
Slope Aspect ◽  
New Approach ◽  
Reference Set ◽  
Digital Elevation ◽  
Using Data ◽  
Elevation Model ◽  
Degree Of Similarity

The usefulness of the parameters (e.g., slope, aspect) derived from a Digital Elevation Model (DEM) is limited by its accuracy. In this paper, a thematic-like quality control (class-based) of aspect and slope classes is proposed. A product can be compared against a reference dataset, which provides the quality requirements to be achieved, by comparing the product proportions of each class with those of the reference set. If a distance between the product proportions and the reference proportions is smaller than a small enough positive tolerance, which is fixed by the user, it will be considered that the degree of similarity between the product and the reference set is acceptable, and hence that its quality meets the requirements. A formal statistical procedure, based on a hypothesis test, is developed and its performance is analyzed using simulated data. It uses the Hellinger distance between the proportions. The application to the slope and aspect is illustrated using data derived from a 2×2 m DEM (reference) and 5×5 m DEM in Allo (province of Navarra, Spain).

scholarly journals Spatial analysis of damaged vegetation in the Mianyuan River basin after the Wenchuan Earthquake

2015 ◽  
Vol 3 (5) ◽  
pp. 3225-3250
Author(s):  
H. Z. Zhang ◽  
J. R. Fan ◽  
X. M. Wang ◽  
T. H. Chi ◽  
L. Peng
Keyword(s):  
Slope Stability ◽  
Wenchuan Earthquake ◽  
River Basin ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Probabilistic Approach ◽  
Model Development ◽  
Slope Aspect ◽  
2008 Wenchuan Earthquake ◽  
Elevation Model

Abstract. The 2008 Wenchuan earthquake destroyed large areas of vegetation. Presently, these areas of damaged vegetation are at various stages of recovery. In this study, we present a probabilistic approach for slope stability analysis that quantitatively relates data on earthquake-damaged vegetation with slope stability in a given river basin. The Mianyuan River basin was selected for model development, and earthquake-damaged vegetation and post-earthquake recovery conditions were identified via the normalized difference vegetation index (NDVI), from multi-temporal (2001–2014) remote sensing images. DSAL (digital elevation model, slope, aspect, and lithology) spatial zonation was applied to characterize the survival environments of vegetation, which were used to discern the relationships between successful vegetation regrowth and environmental conditions. Finally, the slope stability susceptibility model was trained through multivariate analysis of earthquake-damaged vegetation and its controlling factors (i.e. topographic environments and material properties). Application to the Subao River basin validated the proposed model, showing that most of the damaged vegetation areas have high susceptibility levels (88.1% > susceptibility level 3, and 61.5% > level 4). Our modelling approach may also be valuable for use in other regions prone to landslide hazards.

scholarly journals Study on the Dependence of Reverse Simulation for Identifying a Pollutant Source on Grid Resolution and Filter Width in Cavity Flow

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Satoshi Abe ◽  
Shinsuke Kato ◽  
Fujihiro Hamba ◽  
Daisuke Kitazawa
Keyword(s):  
Cavity Flow ◽  
Grid Resolution ◽  
Hazardous Substance ◽  
Simulation Accuracy ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Filter Width ◽  
Pollutant Source ◽  
Reverse Simulation ◽  
Negative Diffusion

When a hazardous substance is diffused, it is necessary to identify the pollutant source and respond immediately. However, there are many cases in which damage is caused without a clear understanding of where the pollutant source is located. There are three groups of identifying pollutant source information (Liu and Zhai, 2007): the probability method, forward method, and backward method. In our previous study, we proposed reverse simulation, which is categorized as a backward method (Abe and Kato, 2011). Numerical instability by negative diffusion is a principal problem in the backward method. In order to improve the problem, we applied a low-pass filter operation to the concentration flux in the RANS analysis. The simulation secured the numerical stability. However, reverse simulation accuracy is expected to depend on the grid resolution and filter width. In this paper, we introduce reverse simulation results in cavity flow. In particular, we survey the dependence of reverse simulation accuracy on the grid resolution and filter width. Moreover, we discuss the dependence of reverse simulation on the grid resolution and filter width with a one-dimensional diffusion equation. As a result, we found that the simulated negative diffusion varies greatly among the grid resolution and filter width.

scholarly journals Mapping Post-Earthquake Landslide Susceptibility: A U-Net Like Approach

2020 ◽  
Vol 12 (17) ◽  
pp. 2767
Author(s):  
Yu Chen ◽  
Yongming Wei ◽  
Qinjun Wang ◽  
Fang Chen ◽  
Chunyan Lu ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Environmental Influence ◽  
Landslide Susceptibility Mapping ◽  
Slope Aspect ◽  
Support Vector ◽  
Gis Technology ◽  
2008 Wenchuan Earthquake ◽  
Structure Information ◽  
Digital Elevation ◽  
Elevation Model

A serious earthquake could trigger thousands of landslides and produce some slopes more sensitive to slide in future. Landslides could threaten human’s lives and properties, and thus mapping the post-earthquake landslide susceptibility is very valuable for a rapid response to landslide disasters in terms of relief resource allocation and posterior earthquake reconstruction. Previous researchers have proposed many methods to map landslide susceptibility but seldom considered the spatial structure information of the factors that influence a slide. In this study, we first developed a U-net like model suitable for mapping post-earthquake landslide susceptibility. The post-earthquake high spatial airborne images were used for producing a landslide inventory. Pre-earthquake Landsat TM (Thematic Mapper) images and the influencing factors such as digital elevation model (DEM), slope, aspect, multi-scale topographic position index (mTPI), lithology, fault, road network, streams network, and macroseismic intensity (MI) were prepared as the input layers of the model. Application of the model to the heavy-hit area of the destructive 2008 Wenchuan earthquake resulted in a high validation accuracy (precision 0.77, recall 0.90, F1 score 0.83, and AUC 0.90). The performance of this U-net like model was also compared with those of traditional logistic regression (LR) and support vector machine (SVM) models on both the model area and independent testing area with the former being stronger than the two traditional models. The U-net like model introduced in this paper provides us the inspiration that balancing the environmental influence of a pixel itself and its surrounding pixels to perform a better landslide susceptibility mapping (LSM) task is useful and feasible when using remote sensing and GIS technology.

Zonation of the Landslide Hazards Based on Artificial Neural Network

2012 ◽  
Vol 204-208 ◽  
pp. 3389-3392
Author(s):  
Zhi Wang Wang ◽  
Duan You Li ◽  
Jing Ning
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Research Result ◽  
Slope Angle ◽  
Slope Aspect ◽  
Gis Technology ◽  
Rs And Gis ◽  
Landslide Hazards ◽  
Artificial Neural ◽  
Elevation Model

This paper applies RS and GIS technology to study zonation of the landslide hazards in the study area from Badong county to Zigui county in TGP reservoir region. The causative factors involves lithology, distance to faults, slope angle, slope aspect, elevation, drainage network, distance to river and distribution of plant, which are derived from geological map, Spot imagery data and Digital Elevation Model (DEM) based on RS and GIS technology. We analyze the zonation of the landslide hazards with artificial neural network. The research result is very coincident with the occurrence of the known landslides in the study area.

scholarly journals ICESAT VALIDATION OF TANDEM-X I-DEMS OVER THE UK

2016 ◽  
Vol XLI-B4 ◽  
pp. 129-136 ◽  
Author(s):  
L. Feng ◽  
J.-P. Muller
Keyword(s):  
Slope Aspect ◽  
Surface Slope ◽  
Grid Spacing ◽  
Digital Elevation ◽  
X Band ◽  
Elevation Data ◽  
Vertical Accuracy ◽  
Elevation Model ◽  
The Uk ◽  
Interferometric Sar

From the latest TanDEM-X mission (bistatic X-Band interferometric SAR), globally consistent Digital Elevation Model (DEM) will be available from 2017, but their accuracy has not yet been fully characterised. This paper presents the methods and implementation of statistical procedures for the validation of the vertical accuracy of TanDEM-X iDEMs at grid-spacing of approximately 12.5 m, 30 m and 90 m based on processed ICESat data over the UK in order to assess their potential extrapolation across the globe. The accuracy of the TanDEM-X iDEM in UK was obtained as follows: against ICESat GLA14 elevation data, TanDEM-X iDEM has −0.028±3.654 m over England and Wales and 0.316 ± 5.286 m over Scotland for 12 m, −0.073 ± 6.575 m for 30 m, and 0.0225 ± 9.251 m at 90 m. Moreover, 90 % of all results at the three resolutions of TanDEM-X iDEM data (with a linear error at 90 % confidence level) are below 16.2 m. These validation results also indicate that derivative topographic parameters (slope, aspect and relief) have a strong effect on the vertical accuracy of the TanDEM-X iDEMs. In high-relief and large slope terrain, large errors and data voids are frequent, and their location is strongly influenced by topography, whilst in the low- to medium-relief and low slope sites, errors are smaller. ICESat derived elevations are heavily influenced by surface slope within the 70 m footprint as well as there being slope dependent errors in the TanDEM-X iDEMs.

scholarly journals Floods Risk Mapping and Assessing Vulnerability of Morang, Nepal

2021 ◽  
Author(s):  
Pawan Thapa ◽  
Narayan Thapa
Keyword(s):  
Drainage Density ◽  
Google Earth ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Digital Elevation ◽  
Two Factors ◽  
Flooding Risk ◽  
Elevation Model ◽  
The One ◽  
The Impact

Abstract Background: The impact of flooding rises due to unplanned settlements, especially in developing and underdeveloped countries. This study tries to address these issues by mapping flood risk places and assessing their impact on population and household.Methods: This study used the dataset available in Google Earth Engine (GEE), Food and Agriculture Organization (FAO), Central Bureau Statistics (CBS), Earth Data for preparing slope, drainage density, digital elevation model, rainfall, land use map, and soil map. These maps create using GEE and QGIS through overlay analysis that has two factors. The one is influence and other slopes, and it has provided high and low value according to its role on flooding.Results: The risk assessment shows around twenty-four percent population is at higher risk, whereas more than three thousand settlements are prone to flooding. It depicts a significant increasing trend of floods in the Morang district.Conclusion: This settlement risk map can help determine the flood safe and very high-risk areas in the Morang district. It will support residential places' planning by the local government, urban planners, and community people to reduce flooding risk.

scholarly journals Floods Risk Mapping and Assessing Vulnerability of Morang, Nepal

2021 ◽  
Author(s):  
Pawan Thapa ◽  
Narayan Thapa
Keyword(s):  
Drainage Density ◽  
Google Earth ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Digital Elevation ◽  
Two Factors ◽  
Flooding Risk ◽  
Elevation Model ◽  
The One ◽  
The Impact

Abstract Background: The impact of flooding rises due to unplanned settlements, especially in developing countries. This study tries to address these issues by mapping flood risk places and assessing their impact on population and household.Methods: This study used the dataset available in Google Earth Engine (GEE), Food and Agriculture Organization (FAO), Central Bureau Statistics (CBS), Earth Data for preparing slope, drainage density, digital elevation model, rainfall, land use map, and soil map. These maps create using GEE and QGIS through overlay analysis that has two factors. The one is influence and other slopes, and it has provided high and low value according to its role on flooding.Results: The risk assessment shows around twenty-four percent population is at higher risk, whereas more than three thousand settlements are prone to flooding. It depicts a significant increasing trend of floods in the Morang district.Conclusion: This settlement risk map can help determine the flood safe and very high-risk areas in the Morang district. It will support residential places' planning by the local government, urban planners, and community people to reduce flooding risk.

scholarly journals Hybrid data-model-based mapping of soil thickness in a mountainous watershed

2021 ◽  
Author(s):  
Qina Yan ◽  
Haruko Wainwright ◽  
Baptiste Dafflon ◽  
Sebastian Uhlemann ◽  
Carl I. Steefel ◽  
...  
Keyword(s):  
Hybrid Model ◽  
Spatial Resolution ◽  
Soil Layer ◽  
The South ◽  
Soil Thickness ◽  
The North ◽  
Soil Erosion Rate ◽  
East River ◽  
Thickness Prediction ◽  
Study Sites

Abstract. Soil thickness plays a central role in the interactions between vegetation, soils, and topography where it controls the retention and release of water, carbon, nitrogen, and metals. However, mapping soil thickness, here defined as the mobile regolith layer, at high spatial resolution remains challenging. Here, we develop a hybrid model that combines a process-based model and empirical relationships to estimate the spatial heterogeneity of soil thickness with fine spatial resolution (0.5 m). We apply this model to two examples of hillslopes (south-facing and north-facing, respectively) in the East River Watershed in Colorado that validates the effectiveness of the model. Two independent measurement methods – auger and cone penetrometer – are used to sample soil thickness at 78 locations to calibrate the local value of unconstrained parameters within the hybrid model. Sensitivity analysis using the hybrid model reveals that the diffusion coefficient used in hillslope diffusion modelling has the largest sensitivity among all input parameters. In addition, our results from both sampling and modeling show that, in general, the north-facing hillslope has a deeper soil layer than the south-facing hillslope. By comparing the soil thickness estimated between a machine learning approach and this hybrid model, the hybrid model provides higher accuracy and requires less sampling data. Modeling results further reveal that the south-facing hillslope has a slightly faster surface soil erosion rate and soil production rate than the north-facing hillslope, which suggests that the relatively less dense vegetation cover and drier surface soils on the south-facing slopes may influence soil characteristics. With only seven parameters for calibration, this hybrid model can provide a realistic soil thickness map at other study sites by with a relatively small amount of sampling dataset. Integrating process-based modeling and statistical analysis not only provides a thorough understanding of the fundamental mechanisms for soil thickness prediction, but integrates the strengths of both statistical approaches and process-based modeling approaches.

Sediment residence time variations in an Alpine river system inferred by uranium activity ratio.

2020 ◽  
Author(s):  
Maude Thollon ◽  
Anthony Dosseto ◽  
Samuel Toucanne ◽  
Germain Bayon
Keyword(s):  
Residence Time ◽  
Chemical Weathering ◽  
Activity Ratio ◽  
River System ◽  
Uranium Isotopes ◽  
Soil Thickness ◽  
Thickness Prediction ◽  
Geomorphological Parameters ◽  
The One ◽  
Physical And Chemical

<p>The sediment residence time represents the time elapsed since the formation of the sediment in soils until its deposition. In order to better constrain timescales of sedimentary processes (erosion, transport, and deposition), it is important to understand to what extent sediment residence time is controlled by geomorphological parameters (e.g. elevation, curvature, slope). Uranium isotopes have been used to infer the time elapsed since the formation of fine detrital grains (<63 µm) by physical and chemical weathering (i.e. comminution age).</p><p>In this study, uranium isotopes were measured in fluvial sediments (<63 µm) sampled at different locations in a catchment (Var, France) to determine the variation of uranium activity ratio (<sup>234</sup>U/<sup>238</sup>U) along the river profile. The absence of fluvial plain implies that the sediment residence time mainly represents the storage time on hillslopes, as sediment transport is expected to be very rapid in this mountainous sedimentary system. </p><p>The catchment was divided into 27 sub-catchments to investigate the variability of the geomorphological parameters that have been extracted from spatial analysis. Additionally, sediment residence time was estimated based on soil thickness prediction data combined with denudation rate information to compare this predicted residence time to the one calculated with (<sup>234</sup>U/<sup>238</sup>U).</p><p>The correlation between (<sup>234</sup>U/<sup>238</sup>U) and the estimated sediment residence time confirms that (<sup>234</sup>U/<sup>238</sup>U) can be modelled to infer sediment residence time. Furthermore, the correlations between the slope, the elevation and (<sup>234</sup>U/<sup>238</sup>U) highlight the geomorphological controls on the sediment residence time. The use of (<sup>234</sup>U/<sup>238</sup>U) in sedimentary archives will help to determine past geomorphological variations and re-construct past links between catchment erosion and climate change.</p>

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