Evaluation of Model Validation Techniques in Land Cover Dynamics

This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as “Stochastic Markov (St_Markov)”, “Cellular Automata Markov (CA_Markov)” and “Multi Layer Perceptron Markov (MLP_Marko...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Xuan Zhu [verfasserIn] Raquib Ahmed [verfasserIn] Bayes Ahmed [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2013

Schlagwörter:	model validation map comparison land cover change Kappa fuzzy Markov chain cellular automata artificial neural network three map comparison

Übergeordnetes Werk:	In: ISPRS International Journal of Geo-Information - MDPI AG, 2012, 2(2013), 3, Seite 577-597
Übergeordnetes Werk:	volume:2 ; year:2013 ; number:3 ; pages:577-597

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/ijgi2030577

Katalog-ID:	DOAJ054710715

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allfields	10.3390/ijgi2030577 doi (DE-627)DOAJ054710715 (DE-599)DOAJ42c5d78661bf42e483d351851e5a0ff9 DE-627 ger DE-627 rakwb eng G1-922 Xuan Zhu verfasserin aut Evaluation of Model Validation Techniques in Land Cover Dynamics 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as “Stochastic Markov (St_Markov)”, “Cellular Automata Markov (CA_Markov)” and “Multi Layer Perceptron Markov (MLP_Markov)” models. Various model validation techniques such as per category method, kappa statistics, components of agreement and disagreement, three map comparison and fuzzy methods have then been applied. A comparative analysis of the validation techniques has also been discussed. In all cases, it is found that “MLP_Markov” gives the best results among the three modeling techniques. Fuzzy set theory is the method that seems best able to distinguish areas of minor spatial errors from major spatial errors. Based on the outcome of this paper, it is recommended that scientists should try to use the Kappa, three map comparison and fuzzy methods for model validation. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of model validation techniques and articulates priorities for future research. model validation map comparison land cover change Kappa fuzzy Markov chain cellular automata artificial neural network three map comparison Geography (General) Raquib Ahmed verfasserin aut Bayes Ahmed verfasserin aut In ISPRS International Journal of Geo-Information MDPI AG, 2012 2(2013), 3, Seite 577-597 (DE-627)689130961 (DE-600)2655790-3 22209964 nnns volume:2 year:2013 number:3 pages:577-597 https://doi.org/10.3390/ijgi2030577 kostenfrei https://doaj.org/article/42c5d78661bf42e483d351851e5a0ff9 kostenfrei http://www.mdpi.com/2220-9964/2/3/577 kostenfrei https://doaj.org/toc/2220-9964 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2 2013 3 577-597
spelling	10.3390/ijgi2030577 doi (DE-627)DOAJ054710715 (DE-599)DOAJ42c5d78661bf42e483d351851e5a0ff9 DE-627 ger DE-627 rakwb eng G1-922 Xuan Zhu verfasserin aut Evaluation of Model Validation Techniques in Land Cover Dynamics 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as “Stochastic Markov (St_Markov)”, “Cellular Automata Markov (CA_Markov)” and “Multi Layer Perceptron Markov (MLP_Markov)” models. Various model validation techniques such as per category method, kappa statistics, components of agreement and disagreement, three map comparison and fuzzy methods have then been applied. A comparative analysis of the validation techniques has also been discussed. In all cases, it is found that “MLP_Markov” gives the best results among the three modeling techniques. Fuzzy set theory is the method that seems best able to distinguish areas of minor spatial errors from major spatial errors. Based on the outcome of this paper, it is recommended that scientists should try to use the Kappa, three map comparison and fuzzy methods for model validation. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of model validation techniques and articulates priorities for future research. model validation map comparison land cover change Kappa fuzzy Markov chain cellular automata artificial neural network three map comparison Geography (General) Raquib Ahmed verfasserin aut Bayes Ahmed verfasserin aut In ISPRS International Journal of Geo-Information MDPI AG, 2012 2(2013), 3, Seite 577-597 (DE-627)689130961 (DE-600)2655790-3 22209964 nnns volume:2 year:2013 number:3 pages:577-597 https://doi.org/10.3390/ijgi2030577 kostenfrei https://doaj.org/article/42c5d78661bf42e483d351851e5a0ff9 kostenfrei http://www.mdpi.com/2220-9964/2/3/577 kostenfrei https://doaj.org/toc/2220-9964 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2 2013 3 577-597
allfields_unstemmed	10.3390/ijgi2030577 doi (DE-627)DOAJ054710715 (DE-599)DOAJ42c5d78661bf42e483d351851e5a0ff9 DE-627 ger DE-627 rakwb eng G1-922 Xuan Zhu verfasserin aut Evaluation of Model Validation Techniques in Land Cover Dynamics 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as “Stochastic Markov (St_Markov)”, “Cellular Automata Markov (CA_Markov)” and “Multi Layer Perceptron Markov (MLP_Markov)” models. Various model validation techniques such as per category method, kappa statistics, components of agreement and disagreement, three map comparison and fuzzy methods have then been applied. A comparative analysis of the validation techniques has also been discussed. In all cases, it is found that “MLP_Markov” gives the best results among the three modeling techniques. Fuzzy set theory is the method that seems best able to distinguish areas of minor spatial errors from major spatial errors. Based on the outcome of this paper, it is recommended that scientists should try to use the Kappa, three map comparison and fuzzy methods for model validation. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of model validation techniques and articulates priorities for future research. model validation map comparison land cover change Kappa fuzzy Markov chain cellular automata artificial neural network three map comparison Geography (General) Raquib Ahmed verfasserin aut Bayes Ahmed verfasserin aut In ISPRS International Journal of Geo-Information MDPI AG, 2012 2(2013), 3, Seite 577-597 (DE-627)689130961 (DE-600)2655790-3 22209964 nnns volume:2 year:2013 number:3 pages:577-597 https://doi.org/10.3390/ijgi2030577 kostenfrei https://doaj.org/article/42c5d78661bf42e483d351851e5a0ff9 kostenfrei http://www.mdpi.com/2220-9964/2/3/577 kostenfrei https://doaj.org/toc/2220-9964 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2 2013 3 577-597
allfieldsGer	10.3390/ijgi2030577 doi (DE-627)DOAJ054710715 (DE-599)DOAJ42c5d78661bf42e483d351851e5a0ff9 DE-627 ger DE-627 rakwb eng G1-922 Xuan Zhu verfasserin aut Evaluation of Model Validation Techniques in Land Cover Dynamics 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as “Stochastic Markov (St_Markov)”, “Cellular Automata Markov (CA_Markov)” and “Multi Layer Perceptron Markov (MLP_Markov)” models. Various model validation techniques such as per category method, kappa statistics, components of agreement and disagreement, three map comparison and fuzzy methods have then been applied. A comparative analysis of the validation techniques has also been discussed. In all cases, it is found that “MLP_Markov” gives the best results among the three modeling techniques. Fuzzy set theory is the method that seems best able to distinguish areas of minor spatial errors from major spatial errors. Based on the outcome of this paper, it is recommended that scientists should try to use the Kappa, three map comparison and fuzzy methods for model validation. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of model validation techniques and articulates priorities for future research. model validation map comparison land cover change Kappa fuzzy Markov chain cellular automata artificial neural network three map comparison Geography (General) Raquib Ahmed verfasserin aut Bayes Ahmed verfasserin aut In ISPRS International Journal of Geo-Information MDPI AG, 2012 2(2013), 3, Seite 577-597 (DE-627)689130961 (DE-600)2655790-3 22209964 nnns volume:2 year:2013 number:3 pages:577-597 https://doi.org/10.3390/ijgi2030577 kostenfrei https://doaj.org/article/42c5d78661bf42e483d351851e5a0ff9 kostenfrei http://www.mdpi.com/2220-9964/2/3/577 kostenfrei https://doaj.org/toc/2220-9964 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2 2013 3 577-597
allfieldsSound	10.3390/ijgi2030577 doi (DE-627)DOAJ054710715 (DE-599)DOAJ42c5d78661bf42e483d351851e5a0ff9 DE-627 ger DE-627 rakwb eng G1-922 Xuan Zhu verfasserin aut Evaluation of Model Validation Techniques in Land Cover Dynamics 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as “Stochastic Markov (St_Markov)”, “Cellular Automata Markov (CA_Markov)” and “Multi Layer Perceptron Markov (MLP_Markov)” models. Various model validation techniques such as per category method, kappa statistics, components of agreement and disagreement, three map comparison and fuzzy methods have then been applied. A comparative analysis of the validation techniques has also been discussed. In all cases, it is found that “MLP_Markov” gives the best results among the three modeling techniques. Fuzzy set theory is the method that seems best able to distinguish areas of minor spatial errors from major spatial errors. Based on the outcome of this paper, it is recommended that scientists should try to use the Kappa, three map comparison and fuzzy methods for model validation. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of model validation techniques and articulates priorities for future research. model validation map comparison land cover change Kappa fuzzy Markov chain cellular automata artificial neural network three map comparison Geography (General) Raquib Ahmed verfasserin aut Bayes Ahmed verfasserin aut In ISPRS International Journal of Geo-Information MDPI AG, 2012 2(2013), 3, Seite 577-597 (DE-627)689130961 (DE-600)2655790-3 22209964 nnns volume:2 year:2013 number:3 pages:577-597 https://doi.org/10.3390/ijgi2030577 kostenfrei https://doaj.org/article/42c5d78661bf42e483d351851e5a0ff9 kostenfrei http://www.mdpi.com/2220-9964/2/3/577 kostenfrei https://doaj.org/toc/2220-9964 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2 2013 3 577-597
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callnumber-first	G - Geography, Anthropology, Recreation
author	Xuan Zhu
spellingShingle	Xuan Zhu misc G1-922 misc model validation misc map comparison misc land cover change misc Kappa misc fuzzy misc Markov chain misc cellular automata misc artificial neural network misc three map comparison misc Geography (General) Evaluation of Model Validation Techniques in Land Cover Dynamics
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topic_title	G1-922 Evaluation of Model Validation Techniques in Land Cover Dynamics model validation map comparison land cover change Kappa fuzzy Markov chain cellular automata artificial neural network three map comparison
topic	misc G1-922 misc model validation misc map comparison misc land cover change misc Kappa misc fuzzy misc Markov chain misc cellular automata misc artificial neural network misc three map comparison misc Geography (General)
topic_unstemmed	misc G1-922 misc model validation misc map comparison misc land cover change misc Kappa misc fuzzy misc Markov chain misc cellular automata misc artificial neural network misc three map comparison misc Geography (General)
topic_browse	misc G1-922 misc model validation misc map comparison misc land cover change misc Kappa misc fuzzy misc Markov chain misc cellular automata misc artificial neural network misc three map comparison misc Geography (General)
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title	Evaluation of Model Validation Techniques in Land Cover Dynamics
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title_full	Evaluation of Model Validation Techniques in Land Cover Dynamics
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title_sort	evaluation of model validation techniques in land cover dynamics
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title_auth	Evaluation of Model Validation Techniques in Land Cover Dynamics
abstract	This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as “Stochastic Markov (St_Markov)”, “Cellular Automata Markov (CA_Markov)” and “Multi Layer Perceptron Markov (MLP_Markov)” models. Various model validation techniques such as per category method, kappa statistics, components of agreement and disagreement, three map comparison and fuzzy methods have then been applied. A comparative analysis of the validation techniques has also been discussed. In all cases, it is found that “MLP_Markov” gives the best results among the three modeling techniques. Fuzzy set theory is the method that seems best able to distinguish areas of minor spatial errors from major spatial errors. Based on the outcome of this paper, it is recommended that scientists should try to use the Kappa, three map comparison and fuzzy methods for model validation. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of model validation techniques and articulates priorities for future research.
abstractGer	This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as “Stochastic Markov (St_Markov)”, “Cellular Automata Markov (CA_Markov)” and “Multi Layer Perceptron Markov (MLP_Markov)” models. Various model validation techniques such as per category method, kappa statistics, components of agreement and disagreement, three map comparison and fuzzy methods have then been applied. A comparative analysis of the validation techniques has also been discussed. In all cases, it is found that “MLP_Markov” gives the best results among the three modeling techniques. Fuzzy set theory is the method that seems best able to distinguish areas of minor spatial errors from major spatial errors. Based on the outcome of this paper, it is recommended that scientists should try to use the Kappa, three map comparison and fuzzy methods for model validation. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of model validation techniques and articulates priorities for future research.
abstract_unstemmed	This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as “Stochastic Markov (St_Markov)”, “Cellular Automata Markov (CA_Markov)” and “Multi Layer Perceptron Markov (MLP_Markov)” models. Various model validation techniques such as per category method, kappa statistics, components of agreement and disagreement, three map comparison and fuzzy methods have then been applied. A comparative analysis of the validation techniques has also been discussed. In all cases, it is found that “MLP_Markov” gives the best results among the three modeling techniques. Fuzzy set theory is the method that seems best able to distinguish areas of minor spatial errors from major spatial errors. Based on the outcome of this paper, it is recommended that scientists should try to use the Kappa, three map comparison and fuzzy methods for model validation. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of model validation techniques and articulates priorities for future research.
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title_short	Evaluation of Model Validation Techniques in Land Cover Dynamics
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