Spatial analysis and prediction of Curonian lagoon data with Gstat
The typical goal of geostatistical analysis is to interpolate values of variable under consideration at unobserved locations using data on observed locations because it is not feasible to gather all data of the observations in the study area. The second goal is to know how they represent the study a...
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Gespeichert in:
| Autor*in: |
R. Garška [verfasserIn] I. Krūminiene [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2004 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Mathematical Modelling and Analysis - Vilnius Gediminas Technical University, 2018, 9(2004), 1 |
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| Übergeordnetes Werk: |
volume:9 ; year:2004 ; number:1 |
| Links: |
Link aufrufen |
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| DOI / URN: |
10.3846/13926292.2004.9637240 |
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| Katalog-ID: |
DOAJ010135790 |
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| 520 | |a The typical goal of geostatistical analysis is to interpolate values of variable under consideration at unobserved locations using data on observed locations because it is not feasible to gather all data of the observations in the study area. The second goal is to know how they represent the study area on the basis of the sample points. Kriging is one of geostatistical methods for spatial interpolation. This method relies on the spatial correlation reflected in the available data and so represents a global view of all the data as well as the nearest neighbor influence. Before spatial prediction using kriging can be executed, the semivariogram has to be computed and modelled. The objective of our work is to create maps of the Curonian lagoon using kriging and cokriging methods. Our spatial data consist of observations on sounding and bed sediments of different Curonian lagoon locations. For computation and simulation of semivariograms, as well as for application kriging and cokriging methods and visualization of results on maps Gstat and PCRaster are used. Apie Kuršių marių duomenų erdvinę analizę ir prognozavimą Gstat programos pagalba Santrauka Šio darbo pagrindinis tikslas‐Gstat bei PCRaster programu pagalba sukurti prognozuojamu duomenu ir ju dispersiju žemelapius. Žemelapiams sudaryti pritaikyti krigingo ir kokrigingo metodai. Krigingas yra vienas iš geostatistikos metodu, kuris atsižvelgdamas i erdvini dvieju kintamuju ryši ir kaimyniniu tašku reikšmes atlieka erdvine interpoliacija. Tuo tarpu kok‐rigingas atlieka pirminio kintamojo duomenu prognoze naudojant antriniu kintamuju duomenis. Pagrindinis geostatistines analizes tikslas yra interpoliuoti duomenis nežinomuose srities taškuose, nes dažniausiai atliekant geostatistinius tyrimus naudojami daliniai stebejimai, kurie apima tik visumos dali; arba nera žinoma, ar imties duomenys pakankamai gerai atspindi visa studijuojama sriti. Rezultatu analize parode, kad tikslesne prognoze gaunama taikant kokrigingo metoda. | ||
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10.3846/13926292.2004.9637240 doi (DE-627)DOAJ010135790 (DE-599)DOAJe7f0c078c415492981d8e3ce30911ca8 DE-627 ger DE-627 rakwb eng QA1-939 R. Garška verfasserin aut Spatial analysis and prediction of Curonian lagoon data with Gstat 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The typical goal of geostatistical analysis is to interpolate values of variable under consideration at unobserved locations using data on observed locations because it is not feasible to gather all data of the observations in the study area. The second goal is to know how they represent the study area on the basis of the sample points. Kriging is one of geostatistical methods for spatial interpolation. This method relies on the spatial correlation reflected in the available data and so represents a global view of all the data as well as the nearest neighbor influence. Before spatial prediction using kriging can be executed, the semivariogram has to be computed and modelled. The objective of our work is to create maps of the Curonian lagoon using kriging and cokriging methods. Our spatial data consist of observations on sounding and bed sediments of different Curonian lagoon locations. For computation and simulation of semivariograms, as well as for application kriging and cokriging methods and visualization of results on maps Gstat and PCRaster are used. Apie Kuršių marių duomenų erdvinę analizę ir prognozavimą Gstat programos pagalba Santrauka Šio darbo pagrindinis tikslas‐Gstat bei PCRaster programu pagalba sukurti prognozuojamu duomenu ir ju dispersiju žemelapius. Žemelapiams sudaryti pritaikyti krigingo ir kokrigingo metodai. Krigingas yra vienas iš geostatistikos metodu, kuris atsižvelgdamas i erdvini dvieju kintamuju ryši ir kaimyniniu tašku reikšmes atlieka erdvine interpoliacija. Tuo tarpu kok‐rigingas atlieka pirminio kintamojo duomenu prognoze naudojant antriniu kintamuju duomenis. Pagrindinis geostatistines analizes tikslas yra interpoliuoti duomenis nežinomuose srities taškuose, nes dažniausiai atliekant geostatistinius tyrimus naudojami daliniai stebejimai, kurie apima tik visumos dali; arba nera žinoma, ar imties duomenys pakankamai gerai atspindi visa studijuojama sriti. Rezultatu analize parode, kad tikslesne prognoze gaunama taikant kokrigingo metoda. variogram semivariogram cross semivariogram kriging cokriging Mathematics I. Krūminiene verfasserin aut In Mathematical Modelling and Analysis Vilnius Gediminas Technical University, 2018 9(2004), 1 (DE-627)638410843 (DE-600)2578803-6 16483510 nnns volume:9 year:2004 number:1 https://doi.org/10.3846/13926292.2004.9637240 kostenfrei https://doaj.org/article/e7f0c078c415492981d8e3ce30911ca8 kostenfrei https://journals.vgtu.lt/index.php/MMA/article/view/9708 kostenfrei https://doaj.org/toc/1392-6292 Journal toc kostenfrei https://doaj.org/toc/1648-3510 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2004 1 |
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10.3846/13926292.2004.9637240 doi (DE-627)DOAJ010135790 (DE-599)DOAJe7f0c078c415492981d8e3ce30911ca8 DE-627 ger DE-627 rakwb eng QA1-939 R. Garška verfasserin aut Spatial analysis and prediction of Curonian lagoon data with Gstat 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The typical goal of geostatistical analysis is to interpolate values of variable under consideration at unobserved locations using data on observed locations because it is not feasible to gather all data of the observations in the study area. The second goal is to know how they represent the study area on the basis of the sample points. Kriging is one of geostatistical methods for spatial interpolation. This method relies on the spatial correlation reflected in the available data and so represents a global view of all the data as well as the nearest neighbor influence. Before spatial prediction using kriging can be executed, the semivariogram has to be computed and modelled. The objective of our work is to create maps of the Curonian lagoon using kriging and cokriging methods. Our spatial data consist of observations on sounding and bed sediments of different Curonian lagoon locations. For computation and simulation of semivariograms, as well as for application kriging and cokriging methods and visualization of results on maps Gstat and PCRaster are used. Apie Kuršių marių duomenų erdvinę analizę ir prognozavimą Gstat programos pagalba Santrauka Šio darbo pagrindinis tikslas‐Gstat bei PCRaster programu pagalba sukurti prognozuojamu duomenu ir ju dispersiju žemelapius. Žemelapiams sudaryti pritaikyti krigingo ir kokrigingo metodai. Krigingas yra vienas iš geostatistikos metodu, kuris atsižvelgdamas i erdvini dvieju kintamuju ryši ir kaimyniniu tašku reikšmes atlieka erdvine interpoliacija. Tuo tarpu kok‐rigingas atlieka pirminio kintamojo duomenu prognoze naudojant antriniu kintamuju duomenis. Pagrindinis geostatistines analizes tikslas yra interpoliuoti duomenis nežinomuose srities taškuose, nes dažniausiai atliekant geostatistinius tyrimus naudojami daliniai stebejimai, kurie apima tik visumos dali; arba nera žinoma, ar imties duomenys pakankamai gerai atspindi visa studijuojama sriti. Rezultatu analize parode, kad tikslesne prognoze gaunama taikant kokrigingo metoda. variogram semivariogram cross semivariogram kriging cokriging Mathematics I. Krūminiene verfasserin aut In Mathematical Modelling and Analysis Vilnius Gediminas Technical University, 2018 9(2004), 1 (DE-627)638410843 (DE-600)2578803-6 16483510 nnns volume:9 year:2004 number:1 https://doi.org/10.3846/13926292.2004.9637240 kostenfrei https://doaj.org/article/e7f0c078c415492981d8e3ce30911ca8 kostenfrei https://journals.vgtu.lt/index.php/MMA/article/view/9708 kostenfrei https://doaj.org/toc/1392-6292 Journal toc kostenfrei https://doaj.org/toc/1648-3510 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2004 1 |
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10.3846/13926292.2004.9637240 doi (DE-627)DOAJ010135790 (DE-599)DOAJe7f0c078c415492981d8e3ce30911ca8 DE-627 ger DE-627 rakwb eng QA1-939 R. Garška verfasserin aut Spatial analysis and prediction of Curonian lagoon data with Gstat 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The typical goal of geostatistical analysis is to interpolate values of variable under consideration at unobserved locations using data on observed locations because it is not feasible to gather all data of the observations in the study area. The second goal is to know how they represent the study area on the basis of the sample points. Kriging is one of geostatistical methods for spatial interpolation. This method relies on the spatial correlation reflected in the available data and so represents a global view of all the data as well as the nearest neighbor influence. Before spatial prediction using kriging can be executed, the semivariogram has to be computed and modelled. The objective of our work is to create maps of the Curonian lagoon using kriging and cokriging methods. Our spatial data consist of observations on sounding and bed sediments of different Curonian lagoon locations. For computation and simulation of semivariograms, as well as for application kriging and cokriging methods and visualization of results on maps Gstat and PCRaster are used. Apie Kuršių marių duomenų erdvinę analizę ir prognozavimą Gstat programos pagalba Santrauka Šio darbo pagrindinis tikslas‐Gstat bei PCRaster programu pagalba sukurti prognozuojamu duomenu ir ju dispersiju žemelapius. Žemelapiams sudaryti pritaikyti krigingo ir kokrigingo metodai. Krigingas yra vienas iš geostatistikos metodu, kuris atsižvelgdamas i erdvini dvieju kintamuju ryši ir kaimyniniu tašku reikšmes atlieka erdvine interpoliacija. Tuo tarpu kok‐rigingas atlieka pirminio kintamojo duomenu prognoze naudojant antriniu kintamuju duomenis. Pagrindinis geostatistines analizes tikslas yra interpoliuoti duomenis nežinomuose srities taškuose, nes dažniausiai atliekant geostatistinius tyrimus naudojami daliniai stebejimai, kurie apima tik visumos dali; arba nera žinoma, ar imties duomenys pakankamai gerai atspindi visa studijuojama sriti. Rezultatu analize parode, kad tikslesne prognoze gaunama taikant kokrigingo metoda. variogram semivariogram cross semivariogram kriging cokriging Mathematics I. Krūminiene verfasserin aut In Mathematical Modelling and Analysis Vilnius Gediminas Technical University, 2018 9(2004), 1 (DE-627)638410843 (DE-600)2578803-6 16483510 nnns volume:9 year:2004 number:1 https://doi.org/10.3846/13926292.2004.9637240 kostenfrei https://doaj.org/article/e7f0c078c415492981d8e3ce30911ca8 kostenfrei https://journals.vgtu.lt/index.php/MMA/article/view/9708 kostenfrei https://doaj.org/toc/1392-6292 Journal toc kostenfrei https://doaj.org/toc/1648-3510 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2004 1 |
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Spatial analysis and prediction of Curonian lagoon data with Gstat |
| abstract |
The typical goal of geostatistical analysis is to interpolate values of variable under consideration at unobserved locations using data on observed locations because it is not feasible to gather all data of the observations in the study area. The second goal is to know how they represent the study area on the basis of the sample points. Kriging is one of geostatistical methods for spatial interpolation. This method relies on the spatial correlation reflected in the available data and so represents a global view of all the data as well as the nearest neighbor influence. Before spatial prediction using kriging can be executed, the semivariogram has to be computed and modelled. The objective of our work is to create maps of the Curonian lagoon using kriging and cokriging methods. Our spatial data consist of observations on sounding and bed sediments of different Curonian lagoon locations. For computation and simulation of semivariograms, as well as for application kriging and cokriging methods and visualization of results on maps Gstat and PCRaster are used. Apie Kuršių marių duomenų erdvinę analizę ir prognozavimą Gstat programos pagalba Santrauka Šio darbo pagrindinis tikslas‐Gstat bei PCRaster programu pagalba sukurti prognozuojamu duomenu ir ju dispersiju žemelapius. Žemelapiams sudaryti pritaikyti krigingo ir kokrigingo metodai. Krigingas yra vienas iš geostatistikos metodu, kuris atsižvelgdamas i erdvini dvieju kintamuju ryši ir kaimyniniu tašku reikšmes atlieka erdvine interpoliacija. Tuo tarpu kok‐rigingas atlieka pirminio kintamojo duomenu prognoze naudojant antriniu kintamuju duomenis. Pagrindinis geostatistines analizes tikslas yra interpoliuoti duomenis nežinomuose srities taškuose, nes dažniausiai atliekant geostatistinius tyrimus naudojami daliniai stebejimai, kurie apima tik visumos dali; arba nera žinoma, ar imties duomenys pakankamai gerai atspindi visa studijuojama sriti. Rezultatu analize parode, kad tikslesne prognoze gaunama taikant kokrigingo metoda. |
| abstractGer |
The typical goal of geostatistical analysis is to interpolate values of variable under consideration at unobserved locations using data on observed locations because it is not feasible to gather all data of the observations in the study area. The second goal is to know how they represent the study area on the basis of the sample points. Kriging is one of geostatistical methods for spatial interpolation. This method relies on the spatial correlation reflected in the available data and so represents a global view of all the data as well as the nearest neighbor influence. Before spatial prediction using kriging can be executed, the semivariogram has to be computed and modelled. The objective of our work is to create maps of the Curonian lagoon using kriging and cokriging methods. Our spatial data consist of observations on sounding and bed sediments of different Curonian lagoon locations. For computation and simulation of semivariograms, as well as for application kriging and cokriging methods and visualization of results on maps Gstat and PCRaster are used. Apie Kuršių marių duomenų erdvinę analizę ir prognozavimą Gstat programos pagalba Santrauka Šio darbo pagrindinis tikslas‐Gstat bei PCRaster programu pagalba sukurti prognozuojamu duomenu ir ju dispersiju žemelapius. Žemelapiams sudaryti pritaikyti krigingo ir kokrigingo metodai. Krigingas yra vienas iš geostatistikos metodu, kuris atsižvelgdamas i erdvini dvieju kintamuju ryši ir kaimyniniu tašku reikšmes atlieka erdvine interpoliacija. Tuo tarpu kok‐rigingas atlieka pirminio kintamojo duomenu prognoze naudojant antriniu kintamuju duomenis. Pagrindinis geostatistines analizes tikslas yra interpoliuoti duomenis nežinomuose srities taškuose, nes dažniausiai atliekant geostatistinius tyrimus naudojami daliniai stebejimai, kurie apima tik visumos dali; arba nera žinoma, ar imties duomenys pakankamai gerai atspindi visa studijuojama sriti. Rezultatu analize parode, kad tikslesne prognoze gaunama taikant kokrigingo metoda. |
| abstract_unstemmed |
The typical goal of geostatistical analysis is to interpolate values of variable under consideration at unobserved locations using data on observed locations because it is not feasible to gather all data of the observations in the study area. The second goal is to know how they represent the study area on the basis of the sample points. Kriging is one of geostatistical methods for spatial interpolation. This method relies on the spatial correlation reflected in the available data and so represents a global view of all the data as well as the nearest neighbor influence. Before spatial prediction using kriging can be executed, the semivariogram has to be computed and modelled. The objective of our work is to create maps of the Curonian lagoon using kriging and cokriging methods. Our spatial data consist of observations on sounding and bed sediments of different Curonian lagoon locations. For computation and simulation of semivariograms, as well as for application kriging and cokriging methods and visualization of results on maps Gstat and PCRaster are used. Apie Kuršių marių duomenų erdvinę analizę ir prognozavimą Gstat programos pagalba Santrauka Šio darbo pagrindinis tikslas‐Gstat bei PCRaster programu pagalba sukurti prognozuojamu duomenu ir ju dispersiju žemelapius. Žemelapiams sudaryti pritaikyti krigingo ir kokrigingo metodai. Krigingas yra vienas iš geostatistikos metodu, kuris atsižvelgdamas i erdvini dvieju kintamuju ryši ir kaimyniniu tašku reikšmes atlieka erdvine interpoliacija. Tuo tarpu kok‐rigingas atlieka pirminio kintamojo duomenu prognoze naudojant antriniu kintamuju duomenis. Pagrindinis geostatistines analizes tikslas yra interpoliuoti duomenis nežinomuose srities taškuose, nes dažniausiai atliekant geostatistinius tyrimus naudojami daliniai stebejimai, kurie apima tik visumos dali; arba nera žinoma, ar imties duomenys pakankamai gerai atspindi visa studijuojama sriti. Rezultatu analize parode, kad tikslesne prognoze gaunama taikant kokrigingo metoda. |
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| title_short |
Spatial analysis and prediction of Curonian lagoon data with Gstat |
| url |
https://doi.org/10.3846/13926292.2004.9637240 https://doaj.org/article/e7f0c078c415492981d8e3ce30911ca8 https://journals.vgtu.lt/index.php/MMA/article/view/9708 https://doaj.org/toc/1392-6292 https://doaj.org/toc/1648-3510 |
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I. Krūminiene |
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10.3846/13926292.2004.9637240 |
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2024-07-04T02:20:21.294Z |
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