Assessment of Land - Use Change Effects on Future Beekeeping Suitability Via CA-Markov Prediction Model

Fatih Sari

Uneingeschränkter Zugang

Assessment of Land - Use Change Effects on Future Beekeeping Suitability Via CA-Markov Prediction Model

Fatih Sari

| 16. Aug. 2020

Journal of Apicultural Science

Band 64 (2020): Heft 2 (December 2020)

Über diesen Artikel

Vorheriger Artikel

Nächster Artikel

Zitieren

Article Category: Original Article

Online veröffentlicht: 16. Aug. 2020

Seitenbereich: 263 - 276

Eingereicht: 23. Dez. 2019

Akzeptiert: 21. Mai 2020

DOI: https://doi.org/10.2478/jas-2020-0020

Schlüsselwörter
beekeeping suitability, CA-Markov land use change model, land use change modeling, Multi-Criteria Decision Analysis

© 2020 Faith Sari, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Predicted 2025, 2030, 2040, 2050 LUCC maps.

Changes of LUCC classes from 2006 to 2050.

Annual rates of gain/loss for each LUCC class in prediction periods.

Recent 2018 and predicted 2018 beekeeping suitability maps.

Predicted 2025, 2030, 2040 and 2050 beekeeping suitability maps.

Suitability clusters for area changes (km2).

Accuracy assessment of LUCC change model

Information for Location	Information for Quantity

			No[n]		Medium[m]		Perfect[p]
Perfect[P(x)]	P(n)=		0.4417		0.6737		1.0000
PerfectStratum[K(x)]	K(n)=		0.3584		0.6737		0.6790
MediumGrid[M(x)]	M(n)=		0.3584		0.6531		0.6790
MediumStratum[H(x)]	H(n)=		0.0833		0.1690		0.2719
No[N(x)]	N(n)=		0.0833		0.1690		0.2719
AgreementChance =	0.0833		DisagreeQuantity =		0.3263		Kstandard =			0.5825
AgreementQuantity =	0.0856		DisagreeStrata =		0.0000		Klocation =			0.9592
AgreementStrata =	0.0000		DisagreeGridcell =		0.0206		KlocationStrata =			0.9592
AgreementGridcell =	0.4841						Kno =			0.6215

	UA	AG	GR	SC	FR	SV	BE	FT	CC	WT

Error of Commission	0.145	0.043	0.130	0.030	0.023	0.072	0.054	0.125	0.614	0.906
Producer Accuracy	90.75	95.05	93.26	91.52	97.74	94.27	85.56	93.10	94.66	94.41
User Accuracy	85.42	95.64	86.96	96.92	97.70	92.78	94.51	87.49	93.86	90.93
Kappa Index	0.906	0.949	0.931	0.912	0.972	0.942	0.854	0.930	0.944	0.943
Overall Kappa	0.973
Overall Accuracy	0.986

Area change of land covers (km2) and rates (%)

	2006		2012		2018		2018 Predicted

	Area	%	Area	%	Area	%	Area	%
Urban (UA)	298.36	2.1	352.92	2.5	357.66	2.5	379.86	2.7
Agriculture (AG)	779.98	5.6	641.06	4.6	629.85	4.5	626.14	4.5
Grasslands (GR)	310.93	2.2	427.48	3.0	396.28	2.8	425.00	3.0
Sclerophyll (SC)	1447.04	10.3	1481.95	10.5	1561.26	11.1	1474.05	10.5
Forests (FR)	7594.41	54.0	7884.13	56.1	7905.13	56.2	7908.50	56.3
Sparse Vegetation (SV)	723.81	5.2	326.39	2.3	317.21	2.3	322.37	2.3
Beaches (BE)	325.80	2.3	251.67	1.8	243.59	1.7	220.67	1.6
Fruit Tree (FT)	363.94	2.6	479.49	3.4	477.25	3.4	507.84	3.6
Complex Cultivation (CC)	2052.24	14.6	2036.88	14.5	1991.78	14.2	2008.88	14.3
Water (WT)	157.08	1.1	171.64	1.2	173.68	1.2	180.25	1.3

AHP pairwise comparison matrix

Criteria	Aspect	Elevation	Land Use	Dist. to Roads	Dist.to Wates	Dist. to Sett.	Slope	Natural Disasters	Power Lines	Railways	W

	(AS)	(EL)	(LU)	(DtR)	(DtW)	(DtS)	(SL)	(ND)	(PL)	(RL)
Aspect	1	1.6	0.3	4	0.9	4	3	3	4	3	0.139
Elevation		1	0.3	2	0.9	2	1.9	2	2.7	2	0.094
Land Use			1	9	2.5	9	9	8.2	9	8.2	0.366
Dist. to Roads				1	0.2	1.2	1	1	0.9	1	0.041
Dist. to Water					1	4.8	3.2	3	4	3	0.149
Dist. to Sett.						1	0.8	0.8	1	1.2	0.039
Slope							1	1	1.6	1	0.046
N. Disasters								1	1.2	1	0.045
Power lines									1	1.3	0.039
Railways										1	0.042

(CR=0.091) Total 1.0000

Transition probability matrix from 2006 to 2012

LUCC	UA	AG	GR	SC	FR	SV	BE	FT	CC	WT
UA	0.993	0.001	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.003
AG	0.001	0.971	0.000	0.000	0.000	0.000	0.000	0.024	0.002	0.000
GR	0.008	0.001	0.974	0.000	0.013	0.000	0.000	0.000	0.001	0.000
SC	0.001	0.000	0.001	0.992	0.000	0.000	0.002	0.000	0.000	0.001
FR	0.001	0.000	0.000	0.000	0.997	0.000	0.000	0.000	0.000	0.000
SV	0.001	0.000	0.000	0.000	0.005	0.984	0.006	0.000	0.000	0.002
BE	0.003	0.002	0.001	0.000	0.141	0.000	0.850	0.000	0.000	0.000
FT	0.005	0.000	0.000	0.000	0.000	0.000	0.000	0.9943	0.000	0.000
CC	0.003	0.000	0.000	0.000	0.000	0.000	0.000	0.007	0.985	0.002
WT	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.991

Area changes of suitability classes (km2)

Suitability Classes	2018	2025	2030	2040	2050
1 (Non-Suitable)	466.2	490.5	499.76	519.9	545.0
2	164.4	163.1	163.03	165.1	168.1
3	115.5	113.5	112.12	110.6	108.9
4	896.0	904.0	908.16	917.3	926.4
5 (Moderately Suitable)	1066.8	1047.4	1050.56	1055.1	1058.2
6	2951.6	2918.2	2916.42	2909.8	2903.6
7	4851.7	4853.9	4844.27	4825.9	4805.7
8	2003.3	2012.5	2008.93	1999.9	1989.1
9 (Extremely Suitable)	236.5	248.9	249.20	248.5	247.1

eISSN:: 2299-4831
Sprache:: Englisch

Zeitrahmen der Veröffentlichung:: 2 Hefte pro Jahr
Fachgebiete der Zeitschrift:: Biologie, Zoologie, andere

Zeitschrift RSS Feed

Assessment of Land - Use Change Effects on Future Beekeeping Suitability Via CA-Markov Prediction Model

Article Category: Original Article

Online veröffentlicht: 16. Aug. 2020

Seitenbereich: 263 - 276

Eingereicht: 23. Dez. 2019

Akzeptiert: 21. Mai 2020

DOI: https://doi.org/10.2478/jas-2020-0020

Schlüsselwörter
beekeeping suitability, CA-Markov land use change model, land use change modeling, Multi-Criteria Decision Analysis

© 2020 Faith Sari, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Accuracy assessment of LUCC change model

Area change of land covers (km2) and rates (%)

AHP pairwise comparison matrix

Transition probability matrix from 2006 to 2012

Area changes of suitability classes (km2)

Assessment of Land - Use Change Effects on Future Beekeeping Suitability Via CA-Markov Prediction Model

Article Category: Original Article

Online veröffentlicht: 16. Aug. 2020

Seitenbereich: 263 - 276

Eingereicht: 23. Dez. 2019

Akzeptiert: 21. Mai 2020

DOI: https://doi.org/10.2478/jas-2020-0020

Schlüsselwörterbeekeeping suitability, CA-Markov land use change model, land use change modeling, Multi-Criteria Decision Analysis

© 2020 Faith Sari, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Accuracy assessment of LUCC change model

Area change of land covers (km2) and rates (%)

AHP pairwise comparison matrix

Transition probability matrix from 2006 to 2012

Area changes of suitability classes (km2)

Schlüsselwörter
beekeeping suitability, CA-Markov land use change model, land use change modeling, Multi-Criteria Decision Analysis