Digital repository of Slovenian research organisations

Search the repository
A+ | A- | Help | SLO | ENG

Query: search in
search in
search in
search in


Query: "keywords" (spatial interpolation) .

1 - 3 / 3
First pagePrevious page1Next pageLast page
Comparison of mapping efficiency for small datasets using inverse distance weighting vs. moving average, Northern Croatia Miocene hydrocarbon reservoir
Josip Ivšinović, Tomislav Malvić, 2022, original scientific article

Abstract: Mapping of geological variables in the Croatian part of the Pannonian Basin System (CPBS) is mostly based on small input datasets. In the case of the analyzed hydrocarbon field "B", reservoir "K", due to the complex geological structure and pronounced tectonics, the interpretations are restricted on several blocks, where each has very limited dataset. The porosity (19 data) and permeability (18 data) variables were analyzed. The applied interpolation methods are the Inverse Distance Weighting (IDW) and the Moving Average (MA). They were compared and analyzed by visual inspection of the obtained maps, comparison of mathematical background and by calculation of cross-validation (CV). The cross-validation value for the porosity of the "K" reservoir in the case of IDW application is 0.0011, and in the case of MA 0.0010; while in the case of permeability the IDW is 480.84, and in the case of MA 1346.41. According to the visual review of maps, the values of descriptive statistics of estimated values and the results of cross-validation, the IDW method is recommended for mapping the porosity and permeability of reservoirs blocks in the Sava Depression.
Keywords: Sava depression, Croatia, interpolation, hydrocarbon reservoirs, mapping spatial comparison
Published in DiRROS: 26.07.2022; Views: 58; Downloads: 30
.pdf Full text (1,52 MB)

Reconstruction of landslide activity using dendrogeomorphological analysis in the Karavanke mountains in NW Slovenia
Domen Oven, Tom Levanič, Jernej Jež, Milan Kobal, 2019, original scientific article

Abstract: Tree ring eccentricity was used to reconstruct landslide activity in the last 138 years in the Urbas landslide located at Potoška planina in the NW part of the Karavanke Mountains, Slovenia. The research was based on the dendrochronological sampling of Norway spruce (Picea abies (L.) Karst.) in areas of varying landslide intensity. Analysis of a sudden change in the eccentricity index of 82 curved trees concluded that there were 139 growth disturbances and 16 landslide reactivations between 1880 and 2015, with a landslide return period of 8.5 years. Using lidar data, changes in the surface of the digital terrain model (DTM) were compared with changes in the eccentricity index of trees at the same location in the period 2014-2017. On the basis of temporal changes in the eccentricity index and by using spatial interpolation, landslide activity was reconstructed for the period 1943%2015. During this period, landslide intensity increased in the central part of the landslide. Although categorization into seven categories of different stem curvature was proposed, no distinction between categories with respect to their eccentricity index was found.
Keywords: landslide activity, dendrogeomorphology, tree ring eccentricity, eccentricity index, digital terrain model, spatial interpolation
Published in DiRROS: 20.02.2020; Views: 1265; Downloads: 888
.pdf Full text (9,35 MB)
This document has many files! More...

Evaluating WorldClim version 1 (1961-1990) as the baseline for sustainable use of forest and environmental resources in a changing climate
Maurizio Marchi, Iztok Sinjur, Michele Bozzano, Marjana Westergren, 2019, original scientific article

Abstract: WorldClim version 1 is a high-resolution, global climate gridded dataset covering 1961-1990; a ˝normal˝ climate. It has been widely used for ecological studies thanks to its free availability and global coverage. This study aims to evaluate the quality of WorldClim data by quantifying any discrepancies by comparison with an independent dataset of measured temperature and precipitation records across Europe. BIO1 (mean annual temperature, MAT) and BIO12 (mean total annual precipitation, MAP) were used as proxies to evaluate the spatial accuracy of the WorldClim grids. While good representativeness was detected for MAT, the study demonstrated a bias with respect to MAP. The average difference between WorldClim predictions and climate observations was around +0.2 °C for MAT and -48.7 mm for MAP, with large variability. The regression analysis revealed a good correlation and adequate proportion of explained variance for MAT (adjusted R2 = 0.856) but results for MAP were poor, with just 64% of the variance explained (adjusted R2 = 0.642). Moreover no spatial structure was found across Europe, nor any statistical relationship with elevation, latitude, or longitude, the environmental predictors used to generate climate surfaces. A detectable spatial autocorrelation was only detectable for the two most thoroughly sampled countries (Germany and Sweden). Although further adjustments might be evaluated by means of geostatistical methods (i.e., kriging), the huge environmental variability of the European environment deeply stressed the WorldClim database. Overall, these results show the importance of an adequate spatial structure of meteorological stations as fundamental to improve the reliability of climate surfaces and derived products of the research (i.e., statistical models, future projections).
Keywords: spatial analysis, spatial interpolation, geostatistics, ecological mathematics
Published in DiRROS: 20.02.2020; Views: 1244; Downloads: 706
.pdf Full text (2,62 MB)
This document has many files! More...

Search done in 0.23 sec.
Back to top