scholarly journals A Simple GIS-Based Tool for the Detection of Landslide-Prone Zones on a Coastal Slope in Scotland

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 685
Author(s):  
Alejandro Gonzalez-Ollauri ◽  
Slobodan B. Mickovski
Keyword(s):  
Natural Hazards ◽  
Slope Failure ◽  
Spatial Scales ◽  
Detection Methods ◽  
Limited Information ◽  
Multiple Spatial Scales ◽  
Coastal Slope ◽  
Digital Elevation ◽  
Negative Impacts ◽  
Elevation Model

Effective landslide detection is crucial to mitigate the negative impacts derived from the occurrence of these natural hazards. Research on landslide detection methods has been extensively undertaken. However, simplified methods for landslide detection requiring a minimum amount of data inputs are still lacking. Simple approaches for landslide detection should be particularly interesting for geographical areas with limited information or resources availability. The aim of this paper is to present a refined, simple, GIS-based tool for the detection of landslide-prone and slope restoration zones. The tool only requires a digital elevation model (DEM) dataset as input, it is interoperable at multiple spatial scales, and it can be implemented on any GIS platform. The tool was applied on a coastal slope prone to instability, located in Scotland, in order to verify the functionality of the tool. The results indicated that the proposed tool is able to detect both shallow and deeper landslides satisfactorily, suggesting that the spatial combination of steep and potentially wet soil zones is effective for detecting areas prone to slope failure.

scholarly journals Scale-Optimized Surface Roughness for Topographic Analysis

Geosciences ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 322 ◽  
Author(s):  
John B. Lindsay ◽  
Daniel R. Newman ◽  
Anthony Francioni
Keyword(s):  
Surface Roughness ◽  
Forest Cover ◽  
Agricultural Land ◽  
Spatial Scales ◽  
Grid Cell ◽  
Topographic Analysis ◽  
Digital Elevation ◽  
Locally Adaptive ◽  
Elevation Model

Surface roughness is a terrain parameter that has been widely applied to the study of geomorphological processes. One of the main challenges in studying roughness is its highly scale-dependent nature. Determining appropriate mapping scales in topographically heterogenous landscapes can be difficult. A method is presented for estimating multiscale surface roughness based on the standard deviation of surface normals. This method utilizes scale partitioning and integral image processing to isolate scales of surface complexity. The computational efficiency of the method enables high scale sampling density and identification of maximum roughness for each grid cell in a digital elevation model (DEM). The approach was applied to a 0.5 m resolution LiDAR DEM of a 210 km2 area near Brantford, Canada. The case study demonstrated substantial heterogeneity in roughness properties. At shorter scales, tillage patterns and other micro-topography associated with ground beneath forest cover dominated roughness scale signatures. Extensive agricultural land-use resulted in 35.6% of the site exhibiting maximum roughness at micro-topographic scales. At larger spatial scales, rolling morainal topography and fluvial landforms, including incised channels and meander cut banks, were associated with maximum surface roughness. This method allowed for roughness mapping at spatial scales that are locally adapted to the topographic context of each individual grid cell within a DEM. Furthermore, the analysis revealed significant differences in roughness characteristics among soil texture categories, demonstrating the practical utility of locally adaptive, scale-optimized roughness.

scholarly journals Terrestrial Laser Scanning for the Detection of Coarse Grain Size Movement in a Mountain Riverbed

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2199 ◽  
Author(s):  
Walicka ◽  
Jóźków ◽  
Kasprzak ◽  
Borkowski
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Horizontal Displacement ◽  
Mountain Stream ◽  
Limited Information ◽  
Fluvial Transport ◽  
Digital Elevation ◽  
Load Transport ◽  
Elevation Model

Fluvial transport is a natural process that shapes riverbeds and the surrounding terrain surface, particularly in mountainous areas. Since the traditional techniques used for fluvial transport investigation provide only limited information about the bed load transport, recently, laser scanning technology has been increasingly incorporated into research to investigate this issue in depth. In this study, a terrestrial laser scanning technique was used to investigate the transport of individual boulders. The measurements were carried out annually from 2011 to 2016 on the Łomniczka River, which is a medium-sized mountain stream. The main goal of this research was to detect and determine displacements of the biggest particles in the mountain riverbed. The methodology was divided into two steps. First, the change zones were detected using two strategies. The first strategy was based on differential digital elevation model (DEM) creation and the second involved the calculation of differences between point clouds instead of DEMs. The experiments show that the second strategy was more efficient. In the second step, the displacements of the boulders were determined based on the detected areas of change. Using the proposed methodology, displacements for individual stones in each year were determined. Most of the changes took place in 2012–2014, which correlates well with the hydrological observations. During the six-year period, movements of individual particles with diameters less than 0.8 m were observed. Maximal displacements in the observed period reached 3 m. Therefore, it is possible to determine both vertical and horizontal displacement in the riverbed using multitemporal TLS.

The effects of spatial aggregation of complex topography on hydroecological process simulations within a rugged forest landscape: development and application of a satellite-based topoclimatic model

2004 ◽  
Vol 34 (3) ◽  
pp. 519-530 ◽  
Author(s):  
S Kang ◽  
D Lee ◽  
J S Kimball
Keyword(s):  
Solar Radiation ◽  
Scale Effects ◽  
Net Primary Production ◽  
Spatial Scales ◽  
Spatial Aggregation ◽  
Area Index ◽  
Topographic Complexity ◽  
Digital Elevation ◽  
Process Simulations ◽  
Elevation Model

We evaluated the effects of topographic complexity on landscape carbon and hydrologic process simulations within a rugged mixed hardwood forest by developing and applying a satellite-based hydroecological model at multiple spatial scales. The effects of topographic variability were evaluated by aggregating raster-based digital elevation model and satellite-derived leaf area index inputs across eight different spatial resolutions from 30 m (62 208 pixels) to 2160 m (12 pixels). Our modeling analysis showed that the effect of topography was the strongest on solar radiation and temperature, intermediate on soil water and evapotranspiration, and ambiguous on soil respiration. Spatial aggregation of model inputs smoothed heterogeneous spatial patterns of modeled output variables relative to fine-scale results. Model outputs varied nonlinearly with different levels of spatial aggregation, while spatial variability of model inputs and outputs were dampened at increasingly coarse aggregation levels. Biases in spatially aggregated model predictions were generally less than ±10%, except for solar radiation, which showed biases of up to +50% at coarser spatial scales. The large positive bias in the solar radiation implies that overestimation of biophysical variables that are sensitive to solar radiation (e.g., photosynthesis and net primary production) may be considerable in rugged forested landscapes unless subgrid scale effects are accounted for.

scholarly journals A Mountain Summit Recognition Method Based on Improved Faster R-CNN

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yueping Kong ◽  
Yun Wang ◽  
Song Guo ◽  
Jiajing Wang
Keyword(s):  
Detection Methods ◽  
Feature Points ◽  
Feature Maps ◽  
Recognition Method ◽  
Objective Criterion ◽  
Detection Algorithms ◽  
Digital Elevation ◽  
Feature Pyramid ◽  
Mountain Summit ◽  
Elevation Model

Mountain summits are vital topographic feature points, which are essential for understanding landform processes and their impacts on the environment and ecosystem. Traditional summit detection methods operate on handcrafted features extracted from digital elevation model (DEM) data and apply parametric detection algorithms to locate mountain summits. However, these methods may no longer be effective to achieve desirable recognition results in small summits and suffer from the objective criterion lacking problem. Thus, to address these problems, we propose an improved Faster region-convolutional neural network (R-CNN) to accurately detect the mountain summits from DEM data. Based on Faster R-CNN, the improved network adopts a residual convolution block to replace the traditional part and adds a feature pyramid network (FPN) to fuse the features with adjacent layers to better address the mountain summit detection task. The residual convolution is employed to capture the deep correlation between visual and physical morphological features. The FPN is utilized to integrate the location and semantic information in the extracted feature maps to effectively represent the mountain summit area. The experimental results demonstrate that the proposed network could achieve the highest recall and precision without manually designed summit features and accurately identify small summits.

scholarly journals Improving digital elevation models over ice sheets using AVHRR-based photoclinometry

1998 ◽  
Vol 44 (146) ◽  
pp. 97-103 ◽  
Author(s):  
Ted A. Scambos ◽  
Mark A. Fahnestock
Keyword(s):  
Spatial Scales ◽  
Fold Increase ◽  
Photometric Determination ◽  
Test Case ◽  
Topographic Map ◽  
Ice Stream ◽  
Digital Elevation ◽  
Surface Slopes ◽  
Avhrr Data ◽  
Elevation Model

AbstractAdvanced very high-resolution radiometer (AVHRR) images and a radar-altimetry-based digital elevation model (DEM) covering part of the northeast Greenland ice stream are combined to create an improved topographic map of the area using photoclinometry. In this application of photoclinometry, a DEM is used to establish the photometric relationship for two AVHRR images of a snow surface. Slopes from the DEM are compared with AVHRR data that are filtered (i.e. blurred) to the resolution of the DEM to give an empirical photometric determination. This is then used to convert unfiltered AVHRR data into quantitative slope measurements of the surface in the along-sun direction in each image, resolving features not present (or poorly represented) in the DEM. Co-registration of the images is based on the assumption that the two slope fields from the images describe one continuous smooth surface. The combined slopes are then converted to topography. In the test case, the technique adds topographic details with spatial scales of ~3 to ~20 km. A comparison of our results with airborne laser elevation profiles demonstrates that the new technique recovers most of the topography that is missed by the DEM. The improved topographic map reveals a ten-fold increase in local surface relief over the ice-stream feature, and shows the presence of shallow troughs over the shear margins of the feature.

scholarly journals Improving digital elevation models over ice sheets using AVHRR-based photoclinometry

1998 ◽  
Vol 44 (146) ◽  
pp. 97-103 ◽  
Author(s):  
Ted A. Scambos ◽  
Mark A. Fahnestock
Keyword(s):  
Spatial Scales ◽  
Fold Increase ◽  
Photometric Determination ◽  
Test Case ◽  
Topographic Map ◽  
Ice Stream ◽  
Digital Elevation ◽  
Surface Slopes ◽  
Avhrr Data ◽  
Elevation Model

AbstractAdvanced very high-resolution radiometer (AVHRR) images and a radar-altimetry-based digital elevation model (DEM) covering part of the northeast Greenland ice stream are combined to create an improved topographic map of the area using photoclinometry. In this application of photoclinometry, a DEM is used to establish the photometric relationship for two AVHRR images of a snow surface. Slopes from the DEM are compared with AVHRR data that are filtered (i.e. blurred) to the resolution of the DEM to give an empirical photometric determination. This is then used to convert unfiltered AVHRR data into quantitative slope measurements of the surface in the along-sun direction in each image, resolving features not present (or poorly represented) in the DEM. Co-registration of the images is based on the assumption that the two slope fields from the images describe one continuous smooth surface. The combined slopes are then converted to topography. In the test case, the technique adds topographic details with spatial scales of ~3 to ~20 km. A comparison of our results with airborne laser elevation profiles demonstrates that the new technique recovers most of the topography that is missed by the DEM. The improved topographic map reveals a ten-fold increase in local surface relief over the ice-stream feature, and shows the presence of shallow troughs over the shear margins of the feature.

scholarly journals Using the roadeng system to design an optimum forest road variant aimed at the minimization of negative impacts on the natural environment

2002 ◽  
Vol 48 (8) ◽  
pp. 361-365
Author(s):  
L. Heralt ◽  
Keyword(s):  
Natural Environment ◽  
Final Report ◽  
Forest Road ◽  
Road Design ◽  
Optimization Study ◽  
Digital Elevation ◽  
Project Documentation ◽  
Optimum Variant ◽  
Negative Impacts ◽  
Elevation Model

The optimization study was carried out in the part of the Jeseníky Mts. region in order to find the optimum variant of a forest road route. The ROADENG system was used for determining the Jezerná forest road design with use of projection above the digital elevation model of terrain. Particular variants of the forest road route were calculated and analyzed on the basis of environmental approach. The final report recommended one of the variants for the final elaboration of project documentation and for construction.

scholarly journals Measuring decadal vertical land-level changes from SRTM-C (2000) and TanDEM-X ( ∼ 2015) in the south-central Andes

2018 ◽  
Vol 6 (4) ◽  
pp. 971-987 ◽  
Author(s):  
Benjamin Purinton ◽  
Bodo Bookhagen
Keyword(s):  
Spatial Scales ◽  
Central Andes ◽  
Control Surface ◽  
The Arctic ◽  
The South ◽  
Gravel Bed ◽  
South Central ◽  
Digital Elevation ◽  
Vertical Changes ◽  
Elevation Model

Abstract. In the arctic and high mountains it is common to measure vertical changes of ice sheets and glaciers via digital elevation model (DEM) differencing. This requires the signal of change to outweigh the noise associated with the datasets. Excluding large landslides, on the ice-free earth the land-level change is smaller in vertical magnitude and thus requires more accurate DEMs for differencing and identification of change. Previously, this has required meter to submeter data at small spatial scales. Following careful corrections, we are able to measure land-level changes in gravel-bed channels and steep hillslopes in the south-central Andes using the SRTM-C (collected in 2000) and the TanDEM-X (collected from 2010 to 2015) near-global 12–30 m DEMs. Long-standing errors in the SRTM-C are corrected using the TanDEM-X as a control surface and applying cosine-fit co-registration to remove ∼1/10 pixel (∼3 m) shifts, fast Fourier transform (FFT) and filtering to remove SRTM-C short- and long-wavelength stripes, and blocked shifting to remove remaining complex biases. The datasets are then differenced and outlier pixels are identified as a potential signal for the case of gravel-bed channels and hillslopes. We are able to identify signals of incision and aggradation (with magnitudes down to ∼3 m in the best case) in two >100 km river reaches, with increased geomorphic activity downstream of knickpoints. Anthropogenic gravel excavation and piling is prominently measured, with magnitudes exceeding ±5 m (up to >10 m for large piles). These values correspond to conservative average rates of 0.2 to >0.5 m yr−1 for vertical changes in gravel-bed rivers. For hillslopes, since we require stricter cutoffs for noise, we are only able to identify one major landslide in the study area with a deposit volume of 16±0.15×106 m3. Additional signals of change can be garnered from TanDEM-X auxiliary layers; however, these are more difficult to quantify. The methods presented can be extended to any region of the world with SRTM-C and TanDEM-X coverage where vertical land-level changes are of interest, with the caveat that remaining vertical uncertainties in primarily the SRTM-C limit detection in steep and complex topography.

scholarly journals The pattern of coastline change based on the characteristics of sediment and coastal slope in Pangenan coast of Cirebon, West Java

2018 ◽  
Vol 47 ◽  
pp. 06001 ◽  
Author(s):  
Suhendra ◽  
Amron Amron ◽  
Endang Hilmi
Keyword(s):  
Coastal Slope ◽  
Coastline Change ◽  
Digital Elevation ◽  
Abrasion Rate ◽  
Analysis System ◽  
End Point Rate ◽  
Elevation Model ◽  
Digital Elevation Model Data ◽  
Landsat Satellite ◽  
The Relationship

The coastline changes depend on stability of coastal bodies, such as characteristics of sediment and coastal slope. This research aimed to determine the relationship between the rate of coastline changes with the characteristics of sediment and coastal slope. The coastline changes were analysed by Landsat satellite images in 1991, 1999 and 2017 used End Point Rate (EPR) method on Digital Shoreline Analysis System (DSAS) module. Sediment characteristics (grain size and sediment statistics mean, sorting, skewness and kurtosis) were analysed by dry sieves and hydrometer with graphical method. The coastal slope used ASTER DEM (Digital Elevation Model) data analysis. The results showed that coastline changes at Pangenan coast of Cirebon in 1991-1999, 1999-2017 and 1991-2017 had average accretion rate respectively was 10.72 m/year, 7.25 m/year, 8.97 m/year and average abrasion rate was -12.49 m/year, -9.67 m/year, -6.70 m/year. The sediments were dominated by coarse silt, that had characteristics, were very well sorted, very fine skewed and platykurtic. The coastal slope was categorized as flat. The conclusion of this research was the rate of coastline change had not significant correlation with sediment and coastal slope.

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