Geostatistical regionalization of glacial aquitard thickness in northwestern Germany, based on fuzzy kriging

Piotrowski, Jan A.; Bartels, Frank; Salski, A.; Schmidt, G.

doi:10.1007/bf02083655

Cited by 38 publications

(11 citation statements)

References 9 publications

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“…Because of the non-linear structure in ANNs models and ambiguity in variables in FIS models, (Piotrowski et al 1996; Mukhopadhyay 1999), researchers are, recently attracted in using hybrid models such as Adaptive Neural-based Fuzzy Inference System (ANFIS) to further analyze the variables, which are spatially distributed. (Lee, 2000) In this study, efficiency of Adaptive Neural-based Fuzzy Inference System (ANFIS), artificial neural networks (ANN) and multiple regression (MR) models were examined in estimation of saturation percentage (SP) using measured data of clay, silt sand and organic carbon (OC), in Boukan plain in the West Azerbaijan Province, Iran.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Saturation Percentage of Soil Using Multiple Regression, ANN, and ANFIS Techniques

Aali¹,

Parsinejad²,

Rahmani³

2009

CIS

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The saturation percentage (SP) of soils is an important index in hydrological studies. In this paper, artificial neural networks (ANNs), multiple regression (MR), and adaptive neural-based fuzzy inference system (ANFIS) were used for estimation of saturation percentage of soils collected from Boukan region in the northwestern part of Iran. Percent clay, silt, sand and organic carbon (OC) were used to develop the applied methods. In additions contributions of each input variable were assessed on estimation of SP index. Two performance functions, namely root mean square errors (RMSE) and determination coefficient (R 2 ), were used to evaluate the adequacy of the models. ANFIS method was found to be superior over the other methods. It is, then, proposed that ANFIS model can be used for reasonable estimation of SP values of soils.

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Section: Introductionmentioning

confidence: 99%

Estimation of Saturation Percentage of Soil Using Multiple Regression, ANN, and ANFIS Techniques

Aali¹,

Parsinejad²,

Rahmani³

2009

CIS

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“…The dependent variable "potential natural vegetation" is defined as the climax vegetation that would occur under present environmental conditions, assuming all human activities stopped (Tüxen, 1978). The other independent variables or predictors differentially predict the dependent variable PNV: The climate data of precipitation, global radiation, evaporation and temperature are derived from the German network of climate observing stations (Piotrowski et al, 1996). For Brandenburg we used the same spatial variables as in the countrywide ecoregion classification (exception: appending average distance to groundwater table), but with state-limited, larger-scale data and with a 1 × 1 km raster (Table I).…”

Section: Methodsmentioning

confidence: 99%

Determining Ecoregions for Environmental and GMO Monitoring Networks

Graef

Schmidt

Schröder

et al. 2005

Environ Monit Assess

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A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.

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“…The kriging method is especially useful when digitised points are irregularly spaced (Davis, 1986;Goldsztejn & Skrzypek, 2004). However, application of the method may be restricted in case of an insufficient number of data, and then it is suggested that instead of the conventional kriging procedure its modification -fuzzy kriging, which utilises exact measurement data and imprecise estimates is better used (Piotrowski et al, 1996). In the present study the collected data set consists of 2,037 data points which is considered sufficient.…”

Section: Interpolation Proceduresmentioning

confidence: 99%

Substratum morphology and significance during the Weichselian Odra ice lobe advance in northeast Germany and northwest Poland

Hermanowski

2015

Geologos

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In the Polish Lowlands, three main ice lobes, referred to as Odra, Vistula and Mazury, formed during the Last Scandinavian Glaciation. These lobes protruded at least several kilometres beyond the main ice margin and it is believed that they represent terminal parts of the ice streams. Applied geostatistical analysis based on numerous geological data has allowed an approximate reconstruction of the Odra ice lobe substratum in the area of northwest Poland and northeast Germany. A spatial representation of the Odra lobe substratum clearly illustrates the adverse slope of the glacier bed, but also indicates areas morphologically prone to ice streaming. It is suggested that the ice took advantage of local topography that enabled advance out of the Baltic basin; consequently, the ice followed a topographic low which, in combination with favourable hydraulic conditions of its substratum, likely initiated ice streaming.

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Geostatistical regionalization of glacial aquitard thickness in northwestern Germany, based on fuzzy kriging

Cited by 38 publications

References 9 publications

Estimation of Saturation Percentage of Soil Using Multiple Regression, ANN, and ANFIS Techniques

Estimation of Saturation Percentage of Soil Using Multiple Regression, ANN, and ANFIS Techniques

Determining Ecoregions for Environmental and GMO Monitoring Networks

Substratum morphology and significance during the Weichselian Odra ice lobe advance in northeast Germany and northwest Poland

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