Makro ve Mikro Ölçekteki Lokal Jeoid Tespiti için Enterpolasyon Yöntemlerinin Karşılaştırılması

Yılmaz, Mustafa; Kuru, Birol

doi:10.29128/geomatik.465050

Cited by 6 publications

(2 citation statements)

References 8 publications

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“…It uses local interpolation since it only creates estimates from surrounding spots. The method is based on the notion that local points have a higher weight on the interpolated surface than remote points (Yılmaz and Kuru 2019;Hastaoğlu et al 2021).…”

Section: Inverse Distance Weighted Interpolation Methods (Idw)mentioning

confidence: 99%

Regional Frequency Analysis of Drought Indexes by L-Moments Method

Aktürk

Çıtakoğlu

Demir

2023

Preprint

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Drought has been experienced frequently in Turkey in the last two decades as the effects of withdrawn water resources become more evident. Drought; causes problems for planners and managers. For this reason, in order to provide an accurate framework for sustainable water resources management, it is necessary to investigate the characteristics of drought events and to estimate the return periods of the drought with the help the regional frequency analysis. In this study, firstly, the characteristics of meteorological droughts in the Kızılırmak Basin which has semi-arid climate characteristics, were determined by using the Standardized Precipitation Index (SPI), Z-Score Index (ZSI), China-Z Index (CZI) and Modified China-Z Index (MCZI) as a measure of drought severity and also the applicability and performance of the selected indices to the basin were investigated. Secondly, regional frequency analysis was performed by using L-moment methods for the maximum drought severity values obtained for each year as a result of the application of the four drought indices on a 12-month time scale. According to the results of the meteorological drought analysis of the four drought indices, it was noted that the most severe and long-lasting droughts occurred mainly in the 2000s, the drought severity values increased as the return period increased and also the drought severity values obtained by MCZI method give the extraordinary results than other indices. Thus, it has been seen that the MCZI method is generally not suitable for use in the basin. According to the results of regional frequency analysis, Kızılırmak Basin, which is H1<1, was determined as acceptable homogeneous for all four indices according to the Hosking and Wallis homogeneity test. For each index, the optimum regional distribution function was investigated and Pearson type‒III distribution for SPI and ZSI; distribution of general extreme values for CZI; for MCZI, the generalized logistic distribution was determined as the most appropriate distribution. As a result of the index-flood frequency analysis calculated by using the most appropriate distribution, regional drought severity maps were created for the study area with the Inverse Distance Weighting (IDW) Method for the return periods between 5 years and 1000 years. Using the maps obtained, it is feasible to predict the drought probability of any point in the basin that does not have adequate data for hydrological investigations.

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Section: Inverse Distance Weighted Interpolation Methods (Idw)mentioning

confidence: 99%

Regional Frequency Analysis of Drought Indexes by L-Moments Method

Aktürk

Çıtakoğlu

Demir

2023

Preprint

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“…Creating and selecting the most appropriate and realistic model in geoid determination is extremely important for the practitioners using such models. In the literature to date, many interpolation and least square collocation methods have been used for the geometric modeling of local geoids (Zhan-ji and Yongqi, 1999;Yanalak and Baykal, 2001; Doganalp and Selvi, 2015;Doganalp, 2016;Karaaslan, et al, 2016;Şişman and Elevli, 2018;Yılmaz and Kuru, 2019;Yılmaz, 2019).…”

Section: Introductionmentioning

confidence: 99%

Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey

Akar

Konakoǧlu

2020

Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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This study aimed to determine the most suitable local geoid model based on 641 GNSS/leveling points within the borders of Kars Province in eastern Turkey using the generalized regression neural network (GRNN), weighted average (WA), multiquadric (MQ), inverse multiquadric (IMQ) function, and local polynomial (LP) method. Among these methods used in local geoid determination, the studies conducted with the GRNN method are very limited in the literature. To test the performance of the model, 169 GNSS/leveling points were selected as test data. When selecting reference points and test points, care was taken to distribute these points homogeneously within the study area. The criteria of root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R 2 ) were used to assess the accuracy and error rates of the results achieved using the different methods. According the results of analysis, GRNN method yielded better results than other interpolation methods. These results have showed that GRNN method can be taken into account in modeling various geodesy problems.

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Prediction of geoid undulations: Random forest versus classic interpolation techniques

Akar

Konakoǧlu

Akar

2022

Concurrency and Computation

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Local geoid determination studies are commonly carried out today to establish the relationship between the ellipsoidal height (h)$$ (h) $$ determined by satellite geodesy methods and the orthometric height (H)$$ (H) $$ found using geoid undulation (N)$$ (N) $$. The aim of this study was to determine a local geoid using the kriging, local polynomial (LP), and inverse distance to a power (IDP) interpolation methods along with the random forest (RF) regression method and to compare the performance. For the application, 193 Global Navigation Satellite System (GNSS)/leveling points homogeneously distributed over the study area were selected as reference data, and 70 GNSS/leveling points were selected as test data. The results were compared in terms of accuracy using well‐known performance metrics, namely, the root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) values. According to the results, the highest R2 and the lowest RMSE and MAE values were obtained with the RF regression method. These findings demonstrated the superiority of the RF regression over the classic interpolation methods applied in the local geoid determination for the study area.

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Makro ve Mikro Ölçekteki Lokal Jeoid Tespiti için Enterpolasyon Yöntemlerinin Karşılaştırılması

Cited by 6 publications

References 8 publications

Regional Frequency Analysis of Drought Indexes by L-Moments Method

Regional Frequency Analysis of Drought Indexes by L-Moments Method

Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey

Prediction of geoid undulations: Random forest versus classic interpolation techniques

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