Contextual land-cover classification: incorporating spatial dependence in land-cover classification models using random forests and the Getis statistic

Figures & data

Table 1. Number of calibration and validation pixels for different land-cover classes

Class name	Calibration pixels	Validation pixels
Cranberry bogs	23	9
Pasture or row crops	22	10
Forest	157	67
Grassland	91	33
Urban	163	69
Water	81	39
Wetland	133	65
Sand quarry	48	15

Table 2. Accuracy measures of classifiers with and without spatial dependence

Classification method	Overall accuracy (%)	Overall Kappa	Mean per class Kappa ± standard deviation
Non-spatial random forest	81.76	0.7782	0.7245 ± 0.2417
Non-spatial random forest – 3 × 3 pixels majority filter	90.55	0.8850	0.8215 ± 0.2968
Non-spatial random forest – 7 × 7 pixels majority filter	86.64	0.8363	0.7600 ± 0.3153
Non-spatial random forest – 11 × 11 pixels majority filter	77.52	0.7214	0.6112 ± 0.3205
Random forest Getis – 3 × 3 pixels	87.62	0.8496	0.8123 ± 0.1708
Random forest Getis – 7 × 7 pixels	93.49	0.9209	0.8961 ± 0.1199
Random forest Getis – 11 × 11 pixels	93.49	0.9212	0.9303 ± 0.0629

Table 3. Confusion matrix of non-spatial random forest classifier using validation samples

Class name	Cranberry bogs	Pasture or row crops	Forest	Grassland	Urban	Water	Wetland	Sand quarry	Total	Commission error
Cranberry bogs	6	0	0	0	1	0	0	0	7	0.1429
Pasture or row crops	1	2	0	0	1	0	0	0	4	0.5
Forest	0	0	60	5	2	0	7	0	74	0.1892
Grassland	2	4	0	27	6	0	1	1	41	0.3415
Urban	0	4	2	1	53	0	6	1	67	0.209
Water	0	0	0	0	0	39	0	0	39	0
Wetland	0	0	5	0	5	0	51	0	61	0.1639
Sand quarry	0	0	0	0	1	0	0	13	14	0.0714
Total	9	10	67	33	69	39	65	15	307
Omission error	0.3333	0.8	0.1045	0.1818	0.2319	0	0.2154	0.1333

Figure 1. Land-cover maps produced by (a) non-spatial random forest classifier (top left), (b) random forest Getis classifier using 11 × 11 pixels moving window (top right) and (c) difference map of non-spatial random forest and random forest Getis (11 × 11 pixels) land-cover maps (bottom left).

Table 4. Confusion matrix of random forest Getis classifier with 11 × 11 pixels moving window using validation samples

Class name	Cranberry bogs	Pasture or row crops	Forest	Grassland	Urban	Water	Wetland	Sand quarry	Total	Commission error
Cranberry bogs	8	0	0	0	0	0	0	0	8	0
Pasture or row crops	0	9	0	0	2	0	0	0	11	0.1818
Forest	0	0	62	0	2	0	1	0	65	0.0462
Grassland	0	0	0	33	2	0	0	0	35	0.0571
Urban	0	1	2	0	60	0	3	0	66	0.0909
Water	0	0	0	0	0	39	0	0	39	0
Wetland	1	0	3	0	2	0	61	0	67	0.0896
Sand quarry	0	0	0	0	1	0	0	15	16	0.0625
Total	9	10	67	33	69	39	65	15	307
Omission error	0.1111	0.1	0.0746	0	0.1304	0	0.0615	0

Figure 2. Variable importance contributions of different bands in terms of percent mean reduction in Gini index of the random forest Getis classifier with 11 × 11 pixels moving window.

Table 5. Per class Kappa values of non-spatial and random forest Getis classifiers

Class name	Kappa value (non-spatial random forest)	Kappa value (random forest Getis-11 × 11 pixels)	Increase in Kappa of random forest Getis over non-spatial random forest
Cranberry bogs	0.6589	0.8859	34.45
Pasture or row crops	0.1894	0.8963	373.23
Forest	0.8623	0.9053	4.99
Grassland	0.7902	1	26.55
Urban	0.7034	0.8338	18.54
Water	1	1	0.00
Wetland	0.7312	0.9213	26.00
Sand quarry	0.8603	1	16.24