Assessing land use and land cover change detection using remote sensing in the Lake Tana Basin, Northwest Ethiopia

Figures & data

Figure 1. Location of Lake Tana Basin.

Table 1. Kappa coefficient agreement

No.	Kappa coefficient	Rate
1	Less than 0.4	Poor
2	0.4 < KC < 0.5	Fair
3	0.55 < KC < 0.7	good
4	0.7 < KC < 0.85	Very good
5	KC > 0.85	Excellent

Table 2. Confusion matrixes for the classification of 1986

1986	Reference Data
Classification Data	classes	Forest	Bush	Grass	Cultivated	Residential	Water	Total	User’s Accuracy
	Forest	21	2	0	1	0	0	24	87.50 %
	Bush	2	14	2	0	0	0	18	77.70 %
	Grass	0	1	12	1	1	1	16	75.00 %
	Cultivated	0	0	2	10	4	0	16	62.50 %
	Residential	0	0	0	1	16	0	17	94.10 %
	Water	0	0	2	0	0	23	25	92.00 %
	Total	23	17	18	13	21	24	116
	Producer’s Accuracy	91.3	82.4	75.0	76.92	76.19	95.83		84.20 %

Table 3. Summary of accuracy assessment from 1986–2018 (%)

Land cover class	1986		2002		2018
	Producer’s Accuracy	User’s Accuracy	Producer’s Accuracy	User’s Accuracy	Producer’s Accuracy	User’s Accuracy
Forest	91.30	87.5	88.89	92.31	93.75	93.75
Bush	82.35	77.78	85.00	80.95	92.31	88.89
Grass	75.00	75.00	77.78	82.35	86.36	86.36
Cultivated	76.92	62.50	90.48	73.10	87.50	84.00
Residential	76.19	94.12	81.48	95.65	89.66	96.30
Water body	95.83	92.00	96.15	96.15	96.55	96.55
Overall Accuracy	84.21		87.05		90.36
Kappa statistics	79.02		83.32		89.66

Figure 2. Land use land cover map of 1986 and 2002 of the Tana basin.

Figure 3. Tana basin land cover map of 2018.

Table 4. Summaries of land cover classes in the Tana basin from 1986–2018

Class Name	1986		2002		2018		Change (1986–18)
	Area (km^2)	%	Area (km^2)	%	Area (km^2)	%	Area (km^2)	%
Water Body	2156.2	14.3	2156.2	14.3	2152.7	14.3	−3.5	0.0
Forest land	887.5	5.9	741.6	4.9	546.9	3.6	−340.6	−2.3
Bush land	2918.9	19.4	2381.4	15.8	1438.9	9.6	−1480.0	−9.8
Grass land	2742.1	18.2	1964.7	13.1	1242.1	8.3	−1500.0	−10.0
Agriculture	5654.7	37.6	6491.5	43.1	7608.7	50.5	1954.0	13.0
Residential	694.2	4.6	1318.2	8.8	2064.3	13.7	1370.1	9.1
Total	15,053.6	100.0	15,053.6	100.0	15,053.6	100.0	0.0	0.0