Modeling Change of Topographic Spatial Structures with DEM Resolution Using Semi-Variogram Analysis and Filter Bank

Wang, Chunmei; Yang, Qinke; Jupp, David L.B.; Pang, Guowei

doi:10.3390/ijgi5070107

Cited by 9 publications

(7 citation statements)

References 39 publications

(32 reference statements)

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“…A steep change in slope gradient is often associated with the occurrence of gullies. Some detailed terrain structures will be lost or reduced at coarse resolutions, and the slope gradient variation will decrease on hillslopes [56]. The model cannot effectively distinguish gully and surrounding non-gully regions in these cases based solely on changes in the slope gradient, resulting in the weakening of the role of the slope gradient in the GES mapping process (Figure 10).…”

Section: Impacts Of Resolution On Variable Importancementioning

confidence: 99%

Choosing the Right Horizontal Resolution for Gully Erosion Susceptibility Mapping Using Machine Learning Algorithms: A Case in Highly Complex Terrain

et al. 2022

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Gully erosion susceptibility (GES) maps are essential for managing land resources and erosion control. Choosing the optimal horizontal resolution in GES mapping is a challenge. In this study, the optimal resolution for GES mapping in a complex loess hilly area on the Chinese Loess Plateau was tested using two machine learning algorithms. Unmanned aerial vehicle (UAV) images with a 9 cm resolution and GNSS RTK field-measured data were employed as base datasets, and 11 factors were used in the machine learning models. A series of horizontal resolutions, from 0.5–30 m, was used to determine which was the optimal level and how the resolution influenced the GES mapping. The results showed that the optimal resolution for GES mapping was 2.5–5 m in the loess hilly area, for both the random forest (RF) and extreme gradient-boosting (XGBoost) machine learning algorithms employed in this study. High resolutions overestimated the probability of gully erosion in stable regions, and it became difficult to identify gully and non-gully regions at too-coarse resolutions. The variable importance for GES mapping changed with the resolution and varied among variables. Slope gradient, land use, and contributing area were, in general, the three most critical factors. Land use remained an important factor at all the tested resolution levels. The importance of the slope gradient was underestimated at coarse resolutions (10–30 m), and the importance of the contributing area was underestimated at resolutions that were comparatively fine (0.5–1 m). This study provides an essential reference for selecting the optimal resolution for gully mapping, and thus, offers support for approaches attempting to map gullies using UAV.

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Section: Impacts Of Resolution On Variable Importancementioning

confidence: 99%

Choosing the Right Horizontal Resolution for Gully Erosion Susceptibility Mapping Using Machine Learning Algorithms: A Case in Highly Complex Terrain

et al. 2022

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“…The Topo to Raster interpolation was developed by the ANU (Australian National University), but this method is often used in many countries and research papers [55,56]. It uses a finite differential interpolation technique and it is optimized to streamline the local interpolation computational method such as IDW interpolation, without losing the continuity of surfaces obtained by the kriging or RBF Spline interpolation methods.…”

Section: Topo To Raster Interpolation (Topor)mentioning

confidence: 99%

Testing Different Interpolation Methods Based on Single Beam Echosounder River Surveying. Case Study: Siret River

Arseni

Voiculescu

Georgescu

et al. 2019

IJGI

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Bathymetric measurements play an important role in assessing the sedimentation rate, deposition of pollutants, erosion rate, or monitoring of morphological changes in a river, lake, or accumulation basin. In order to create a coherent and continuous digital elevation model (DEM) of a river bed, various data interpolation methods are used, especially when single-beam bathymetric measurements do not cover the entire area and when there are areas which are not measured. Interpolation methods are based on numerical models applied to natural landscapes (e.g., meandering river) by taking into account various morphometric and morphologies and a wide range of scales. Obviously, each interpolation method, used in standard or customised form, yields different results. This study aims at testing four interpolation methods in order to determine the most appropriate method which will give an accurate description of the riverbed, based on single-beam bathymetric measurements. The four interpolation methods selected in the present research are: inverse distance weighting (IDW), radial basis function (RBF) with completely regularized spline (CRS) which uses deterministic interpolation, simple kriging (KRG) which is a geo-statistical method, and Topo to Raster (TopoR), a particular method specifically designed for creating continuous surfaces from various elevation points, contour, or polygon data, suitable for creating surfaces for hydrologic analysis. Digital elevation models (DEM’s) were statistically analyzed and precision and errors were evaluated. The single-beam bathymetric measurements were made on the Siret River, between 0 and 35 km. To check and validate the methods, the experiment was repeated for five randomly selected cross-sections in a 1500 m section of the river. The results were then compared with the data extracted from each elevation model generated with each of the four interpolation methods. Our results show that: 1) TopoR is the most accurate technique, and 2) the two deterministic methods give large errors in bank areas, for the entire river channel and for the particular cross-sections.

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“…When sample point distances are greater, it becomes large, but up to a certain distance, the variance levels off, which means that the points are no longer spatially correlated [48]. The formula of the semi-variogram is as follows [49]:…”

Section: Connectivitymentioning

confidence: 99%

Landscape-Based Assessment of Urban Resilience and Its Evolution: A Case Study of the Central City of Shenyang

2019

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Urban resilience is increasingly considered a useful approach to accommodate uncertainties while achieving sustainability in urban systems, especially in the context of rapid urbanization and global environmental change. However, current research on the quantitative assessment of urban resilience is limited. This study introduces four proxies of urban resilience, i.e., diversity, connectivity, decentralization, and self-sufficiency, and the perspective of the urban landscape for the measurement of urban resilience and further guidance on planning practices by establishing connections between resilience potential and landscape characteristics. Using multi-source data and employing landscape-based analysis methods, urban resilience is investigated from 1995 to 2015 in the central city of Shenyang. The results indicate that the composition and configuration of the urban landscape changed significantly during this period, which had a great influence on urban resilience. The temporal and spatial evolution of urban resilience showed obviously directional preferences and an evident distance effect. Overall, the resilience level increased slightly, while the internal differences experienced a declining trend. The four characteristics can be deployed as practical principles to shape urban resilience. The adjustment and trade-offs of these aspects to enhance responsive structures and simultaneously maintain sustainable ecosystem services can be effective ways to realize long-term resilience.

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Modeling Change of Topographic Spatial Structures with DEM Resolution Using Semi-Variogram Analysis and Filter Bank

Cited by 9 publications

References 39 publications

Choosing the Right Horizontal Resolution for Gully Erosion Susceptibility Mapping Using Machine Learning Algorithms: A Case in Highly Complex Terrain

Choosing the Right Horizontal Resolution for Gully Erosion Susceptibility Mapping Using Machine Learning Algorithms: A Case in Highly Complex Terrain

Testing Different Interpolation Methods Based on Single Beam Echosounder River Surveying. Case Study: Siret River

Landscape-Based Assessment of Urban Resilience and Its Evolution: A Case Study of the Central City of Shenyang

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