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  • Cartography and geographic base data  (4)
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  • Cartography and geographic base data  (4)
  • 1
    Online Resource
    Online Resource
    Informa UK Limited ; 2023
    In:  GIScience & Remote Sensing Vol. 60, No. 1 ( 2023-12-31)
    In: GIScience & Remote Sensing, Informa UK Limited, Vol. 60, No. 1 ( 2023-12-31)
    Type of Medium: Online Resource
    ISSN: 1548-1603 , 1943-7226
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2023
    detail.hit.zdb_id: 2209042-3
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  • 2
    Online Resource
    Online Resource
    Vilnius Gediminas Technical University ; 2013
    In:  Geodesy and Cartography Vol. 39, No. 2 ( 2013-06-28), p. 41-52
    In: Geodesy and Cartography, Vilnius Gediminas Technical University, Vol. 39, No. 2 ( 2013-06-28), p. 41-52
    Abstract: Different slope algorithms can result in totally different estimates. In the worst case, this may lead to inappropriate and useless modelling estimates. A frequent lack of awareness when choosing algorithms justifies a thorough comparison of their characteristics, making it possible for researchers to select an algorithm which is optimal for their purpose. In this study, eight frequently used slope algorithms applied to Digital Elevation Models (DEMs) are compared. The influences of the resolution of the DEM (0.5, 1, 2, and 5 metres), as well as the terrain form (flat and steep terrain), are considered. It should be noted that the focus of the study is not to compare estimates with ‘ground truth’ data, but on the comparisons between the algorithms, and the ways in which they might differ depending on resolution and terrain. Descriptive statistics are calculated in order to characterize the general characteristics of the eight tested algorithms. Eight combinations of DEM resolution and terrain form are analysed. The results show that the Maximum and Simple Difference algorithms always yield higher mean slope values than the other algorithms, while the Constrained Quadratic Surface algorithm produces the lowest values compared to the others. It is concluded that the estimated slope values are heavily dependent on the number of neighbouring cells included in the estimation. An Analysis of Variance (ANOVA) of estimated slope values strongly indicates (at the significance level of 0.01) that the tested algorithms yield statistically different results. The eight algorithms produce different estimates for all tested resolutions and terrain forms but one. The differences are more pronounced in steep terrain and at a higher resolution. More detailed pairwise comparisons between estimated slope values are also carried out. It is concluded that the smoothing effects associated with the Constrained Quadratic Surface algorithm are greater in steeper terrain, showing significantly lower estimates than other algorithms. On the other hand, the Maximum and Simple Difference algorithms show significantly higher estimates in almost all cases, except the combination of steep terrain and low resolution. With an increase in grid cell size, the loss of information contents in DEMs leads to lower estimated slope values as well as smaller relative differences between algorithms. Based on the results of this study it is concluded that the choice of algorithm results in different estimated slope values, and that resolution and terrain influences these differences significantly.
    Type of Medium: Online Resource
    ISSN: 2029-6991 , 2029-7009
    Language: Unknown
    Publisher: Vilnius Gediminas Technical University
    Publication Date: 2013
    detail.hit.zdb_id: 2737682-5
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  • 3
    Online Resource
    Online Resource
    MDPI AG ; 2019
    In:  ISPRS International Journal of Geo-Information Vol. 8, No. 3 ( 2019-02-28), p. 110-
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 8, No. 3 ( 2019-02-28), p. 110-
    Abstract: Evacuation is an important activity for reducing the number of casualties and amount of damage in disaster management. Evacuation planning is tackled as a spatial optimization problem. The decision-making process for evacuation involves high uncertainty, conflicting objectives, and spatial constraints. This study presents a Multi-Objective Artificial Bee Colony (MOABC) algorithm, modified to provide a better solution to the evacuation problem. The new approach combines random swap and random insertion methods for neighborhood search, the two-point crossover operator, and the Pareto-based method. For evacuation planning, two objective functions were considered to minimize the total traveling distance from an affected area to shelters and to minimize the overload capacity of shelters. The developed model was tested on real data from the city of Kigali, Rwanda. From computational results, the proposed model obtained a minimum fitness value of 5.80 for capacity function and 8.72 × 108 for distance function, within 161 s of execution time. Additionally, in this research we compare the proposed algorithm with Non-Dominated Sorting Genetic Algorithm II and the existing Multi-Objective Artificial Bee Colony algorithm. The experimental results show that the proposed MOABC outperforms the current methods both in terms of computational time and better solutions with minimum fitness values. Therefore, developing MOABC is recommended for applications such as evacuation planning, where a fast-running and efficient model is needed.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2655790-3
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  • 4
    Online Resource
    Online Resource
    Vilnius Gediminas Technical University ; 2012
    In:  Geodesy and Cartography Vol. 38, No. 2 ( 2012-06-29), p. 57-69
    In: Geodesy and Cartography, Vilnius Gediminas Technical University, Vol. 38, No. 2 ( 2012-06-29), p. 57-69
    Abstract: Global change and GHG emission modelling are dependent on accurate wetness estimations for predictions of e.g. methane emissions. This study aims to quantify how the slope, drainage area and the TWI vary with the resolution of DEMs for a flat peatland area. Six DEMs with spatial resolutions from 0.5 to 90 m were interpolated with four different search radiuses. The relationship between accuracy of the DEM and the slope was tested. The LiDAR elevation data was divided into two data sets. The number of data points facilitated an evaluation dataset with data points not more than 10 mm away from the cell centre points in the interpolation dataset. The DEM was evaluated using a quantile-quantile test and the normalized median absolute deviation. It showed independence of the resolution when using the same search radius. The accuracy of the estimated elevation for different slopes was tested using the 0.5 meter DEM and it showed a higher deviation from evaluation data for steep areas. The slope estimations between resolutions showed differences with values that exceeded 50%. Drainage areas were tested for three resolutions, with coinciding evaluation points. The model ability to generate drainage area at each resolution was tested by pair wise comparison of three data subsets and showed differences of more than 50% in 25% of the evaluated points. The results show that consideration of DEM resolution is a necessity for the use of slope, drainage area and TWI data in large scale modelling.
    Type of Medium: Online Resource
    ISSN: 2029-6991 , 2029-7009
    Language: Unknown
    Publisher: Vilnius Gediminas Technical University
    Publication Date: 2012
    detail.hit.zdb_id: 2737682-5
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