scholarly journals Effective Identification of Terrain Positions from Gridded DEM Data Using Multimodal Classification Integration

2018 ◽  
Vol 7 (11) ◽  
pp. 443 ◽  
Author(s):  
Ling Jiang ◽  
Dequan Ling ◽  
Mingwei Zhao ◽  
Chun Wang ◽  
Qiuhua Liang ◽  
...  

Terrain positions are widely used to describe the Earth’s topographic features and play an important role in the studies of landform evolution, soil erosion and hydrological modeling. This work develops a new multimodal classification system with enhanced classification performance by integrating different approaches for terrain position identification. The adopted classification approaches include local terrain attribute (LA)-based and regional terrain attribute (RA)-based, rule-based and supervised, and pixel-based and object-oriented methods. Firstly, a double-level definition scheme is presented for terrain positions. Then, utilizing a hierarchical framework, a multimodal approach is developed by integrating different classification techniques. Finally, an assessment method is established to evaluate the new classification system from different aspects. The experimental results, obtained at a Loess Plateau region in northern China on a 5 m digital elevation model (DEM), show reasonably positional relationship, and larger inter-class and smaller intra-class variances. This indicates that identified terrain positions are consistent with the actual topography from both overall and local perspectives, and have relatively good integrity and rationality. This study demonstrates that the current multimodal classification system, developed by taking advantage of various classification methods, can reflect the geographic meanings and topographic features of terrain positions from different levels.

2020 ◽  
pp. 147592172097970
Author(s):  
Liangliang Cheng ◽  
Vahid Yaghoubi ◽  
Wim Van Paepegem ◽  
Mathias Kersemans

The Mahalanobis–Taguchi system is considered as a promising and powerful tool for handling binary classification cases. Though, the Mahalanobis–Taguchi system has several restrictions in screening useful features and determining the decision boundary in an optimal manner. In this article, an integrated Mahalanobis classification system is proposed which builds on the concept of Mahalanobis distance and its space. The integrated Mahalanobis classification system integrates the decision boundary searching process, based on particle swarm optimizer, directly into the feature selection phase for constructing the Mahalanobis distance space. This integration (a) avoids the need for user-dependent input parameters and (b) improves the classification performance. For the feature selection phase, both the use of binary particle swarm optimizer and binary gravitational search algorithm is investigated. To deal with possible overfitting problems in case of sparse data sets, k-fold cross-validation is considered. The integrated Mahalanobis classification system procedure is benchmarked with the classical Mahalanobis–Taguchi system as well as the recently proposed two-stage Mahalanobis classification system in terms of classification performance. Results are presented on both an experimental case study of complex-shaped metallic turbine blades with various damage types and a synthetic case study of cylindrical dogbone samples with creep and microstructural damage. The results indicate that the proposed integrated Mahalanobis classification system shows good and robust classification performance.


2019 ◽  
Vol 8 (1) ◽  
pp. 30 ◽  
Author(s):  
Ying Zhu ◽  
Xuejun Liu ◽  
Jing Zhao ◽  
Jianjun Cao ◽  
Xiaolei Wang ◽  
...  

Topographic factors such as slope and aspect are essential parameters in depicting the structure and morphology of a terrain surface. We study the effect of the number of points in the neighbourhood of a digital elevation model (DEM) interpolation method on mean slope, mean aspect, and RMSEs of slope and aspect from the interpolated DEM. As the moving least squares (MLS) method can maintain the inherent properties and other characteristics of a surface, this method is chosen for DEM interpolation. Three areas containing different types of topographic features are selected for study. Simulated data from a Gauss surface is also used for comparison. First, the impact of the number of points on the DEM root mean square error (RMSE) is analysed. The DEM RMSE in the three study areas decreases gradually with the number of points in the neighbourhood. In addition, the effect of the number of points in the neighbourhood on mean slope and mean aspect was studied across varying topographies through regression analysis. The two variables respond differently to changes in terrain. However, the RMSEs of the slope and aspect in all study areas are logarithmically related to the number of points in the neighbourhood and the values decrease uniformly as the number of points in the neighbourhood increases. With more points in the neighbourhood, the RMSEs of the slope and aspect are not sensitive to topography differences and the same trends are observed for the three studied quantities. Results for the Gauss surface are similar. Finally, this study analyses the spatial distribution of slope and aspect errors. The slope error is concentrated in ridges, valleys, steep-slope areas, and ditch edges while the aspect error is concentrated in ridges, valleys, and flat regions. With more points in the neighbourhood, the number of grid cells in which the slope error is greater than 15° is gradually reduced. With similar terrain types and data sources, if the calculation efficiency is not a concern, sufficient points in the spatial autocorrelation range should be analysed in the neighbourhood to maximize the accuracy of the slope and aspect. However, selecting between 10 and 12 points in the neighbourhood is economical.


2019 ◽  
Vol 46 (5) ◽  
pp. 683-695 ◽  
Author(s):  
Hayri Volkan Agun ◽  
Ozgur Yilmazel

Domain, genre and topic influences on author style adversely affect the performance of authorship attribution (AA) in multi-genre and multi-domain data sets. Although recent approaches to AA tasks focus on suggesting new feature sets and sampling techniques to improve the robustness of a classification system, they do not incorporate domain-specific properties to reduce the negative impact of irrelevant features on AA. This study presents a novel scaling approach, namely, bucketed common vector scaling, to efficiently reduce negative domain influence without reducing the dimensionality of existing features; therefore, this approach is easily transferable and applicable in a classification system. Classification performances on English-language competition data sets consisting of emails and articles and Turkish-language web documents consisting of blogs, articles and tweets indicate that our approach is very competitive to top-performing approaches in English competition data sets and is significantly improving the top classification performance in mixed-domain experiments on blogs, articles and tweets.


2014 ◽  
Vol 590 ◽  
pp. 693-697
Author(s):  
Jing Peng

In multimodal classification, we look for a set of strategies for mining and exploiting the most informative modalities for a given situation. These strategies are computations performed by the algorithms. In this paper, we propose to consider strategies as advice given to an algorithm by “expert.” There can be several classification strategies. Each strategy makes different assumptions regarding the fidelity of a sensor modality and uses different data to arrive at its estimates. Each strategy may place different trust in a sensor at different times, and each may be better in different situations. In this paper, we introduce a novel algorithm for combining expert strategies to achieve robust classification performance in a multimodal setting. We provide experimental results using real world examples to demonstrate the efficacy of the proposed algorithm.


2018 ◽  
Author(s):  
Ralf Loritz ◽  
Hoshin Gupta ◽  
Conrad Jackisch ◽  
Martijn Westhoff ◽  
Axel Kleidon ◽  
...  

Abstract. The increasing diversity and resolution of spatially distributed data on terrestrial systems greatly enhances the potential of hydrological modeling. Optimal and parsimonious use of these data sources implies, however, that we better understand (a) which system characteristics exert primary controls on hydrological dynamics and (b) to what level of detail do those characteristics need to be represented in a model. In this study we develop and test an approach to explore these questions that draws upon information theoretic and thermodynamic reasoning, using spatially distributed topographic information as a straightforward example. Specifically, we subdivide a meso-scale catchment into 105 hillslopes and represent each by a two dimensional numerical hillslope model. These hillslope models differ exclusively with respect to topography related parameters derived from a digital elevation model; the remaining setup and meteorological forcing for each are identical. We analyze the degree of similarity of simulated discharge and storage among the hillslopes as a function of time by examining the Shannon information entropy. We furthermore derive a compressed catchment model by clustering the hillslope models into functional groups of similar runoff generation using normalized mutual information as a distance measure. Our results reveal that, within our given model environment, only a portion of the entire amount of topographic information stored within a digital elevation model is relevant for the simulation of distributed runoff and storage dynamics. This manifests through a possible compression of the model ensemble from the entire set of 105 hillslopes to only 6 hillslopes, each representing a different functional group, which leads to no substantial loss in model performance. Importantly, we find that the concept of hydrological similarity is not necessarily time-invariant. On the contrary, the Shannon entropy as measure for diversity in the simulation ensemble shows a distinct annual pattern, with periods of highly redundant simulations, reflecting coherent and organized dynamics, and periods where hillslopes operate in distinctly different ways. We conclude that the proposed approach provides a powerful framework for understanding and diagnosing how and when process organization and functional similarity of hydrological systems emerges in time. Our approach is neither restricted to the model, nor to model targets or the data source we selected in this study. Overall, we propose that the concepts of hydrological systems acting similarly (and thus giving rise to redundancy) or displaying unique functionality (and thus being irreplaceable) are not mutually exclusive. They are in fact of complementary nature, and systems operate by gradually changing to different levels of organization in time.


OENO One ◽  
2021 ◽  
Vol 55 (3) ◽  
pp. 317-336
Author(s):  
Vittorio Alba ◽  
Giovanni Gentilesco ◽  
Luigi Tarricone

The present research focused on the characterisation of climate evolution in a typical Apulian region for table grape production under the protected geographical indication, “Uva di Puglia I.G.P.”Two thirty-year time window period (TW) were analysed: 1961-1990 and 1991-2020. Georeferenced maps for both TWs were produced to delimit homogeneous zones and to evaluate the climate variability within the investigated area by means of the two bioclimatic indices, Heliothermal Index (HI) and Winkler Index (WI). Spatial analysis of HI and WI was performed using the regression-kriging (RK) interpolation method and the Digital Elevation Model/DEM (10 x 10 m) as a prediction attribute.An increase in both the minimum and maximum temperatures was observed, and locations above 300 m a.s.l. shifted from HI+1 “temperate warm” to HI+2 “warm” according to the Geoviticulture Multicriteria Climatic Classification System. WI values similarly increased between the periods 1961–1990 and 1991–2020, shifting all the sites grouped in the Elevation Classes defined as being below 300 m a.s.l. from Region IV to Region V of the Winkler Classification.According to HI and WI, presumed maturity was calculated as being reached 9 to 15 (HI) and 12 to 28 days (WI) earlier in 1991–2020 than in 1961–1990, taking into account the heat requirements of cv. Italia table grape (representative of Apulian table grape production), were set at 2200 for both indices on the basis of literature data.Moreover, three table grape vineyards, located in the three main producing provinces of Apulia (Bari, Taranto and Barletta-Andria-Trani (BAT)), were considered for future scenarios analysis on the basis of two different Representative Concentration Pathways (RCPs), 4.5 and 8.5, and classified according to the Geoviticulture Multicriteria Climatic Classification System (MCC). Future scenarios scored WI values that exceeded the threshold of 2700 in the BAT and TA provinces in the 2061–2090 time window period for RCP 8.5. In contrast, RCP 4.5 led to a mitigating effect, which was not noticeable until 2040, with a consequent reclassification of the investigated areas on the basis of HI and Cool Night Index (CI).These findings suggest that in order to prevent or overcome heat stress, it will be necessary to implement strategies, such as vineyard relocation to unexplored elevations or latitudes and/or the exploitation of new table grape varieties able to fulfill the optimal maturity parameters, even when the duration of the phenological phases is shorter.


2017 ◽  
Author(s):  
Florin Constantin MIHAI

Landslides are common and frequent geomorphic phenomena for the plateau regions in Romania having important consequences, especially economic ones, that needs designing scientific and technical plans for landslide risk mitigation. For this, an important preliminary step is assessing and mapping the landslide susceptibility. This paper examines a plateau zone in eastern Romania providing such a map, based on the landslides inventory, the digital elevation model (DEM) and the thematic layers of several factors thought to be potential predictors of landslides occurrence: topographic features, land use, and lithology. The methodological framework is based on the analytical hierarchy process (AHP) principles and factors weights attributed based on frequency of landslides. The predictive performance of the model was assessed using the confusion matrix, the ROC (receiver operating characteristic) curve and the AUC (area under curve) parameter. The results indicate a good correspondence between the susceptibility estimated for the test samples and for the validation samples


2020 ◽  
Vol 12 (21) ◽  
pp. 3522
Author(s):  
Laurent Polidori ◽  
Mhamad El Hage

Digital elevation models (DEMs) are widely used in geoscience. The quality of a DEM is a primary requirement for many applications and is affected during the different processing steps, from the collection of elevations to the interpolation implemented for resampling, and it is locally influenced by the landcover and the terrain slope. The quality must meet the user’s requirements, which only make sense if the nominal terrain and the relevant resolution have been explicitly specified. The aim of this article is to review the main quality assessment methods, which may be separated into two approaches, namely, with or without reference data, called external and internal quality assessment, respectively. The errors and artifacts are described. The methods to detect and quantify them are reviewed and discussed. Different product levels are considered, i.e., from point cloud to grid surface model and to derived topographic features, as well as the case of global DEMs. Finally, the issue of DEM quality is considered from the producer and user perspectives.


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