Full polarimetric PALSAR-based land cover monitoring in Cambodia for implementation of REDD policies

Figures & data

Table 1. Previous studies related to polarimetric decomposition.

No.	Authors	Polarimetric parameters used
1	Cloude and Pottier 2008	Entropy and Alpha-based classification
2	Lee et al. 1999	H/A/Alpha Wishart classification
3	Ferro-Famil et al. 2001	H/A/Alpha Wishart classification
4	Fang and Wen 2005	Intensity, Alpha, and Entropy
5	Ouarzeddine et al. 2005	Entropy, Alpha, and Anisotropy
6	Fang et al. 2006	Entropy, Alpha, and Span
7	Alberga 2007	Entropy, Alpha, and Anisotropy-based land cover classification
8	Patel et al. 2009	Entropy, Alpha, and Anisotropy
9	Wang et al. 2009	Krogagger decomposition with T matrix
10	Ince 2010	Dynamic clustering of entropy, alpha, and Anisotropy
11	An et al. 2011	Four component decomposition with deorientation
12	Singh et al. 2011	Four component scattering power decomposition

Figure 1.  Location of the study area.

Figure 2.  Land cover of the study area.

Table 2. Percentage of different types of land cover.

	AVNIR-2-based classes		Cloude-Pottier-based classes		Freeman–Durden three component-based classes		Yamaguchi four component-based classes
Land cover classes	Area (Km^2)	% of land cover	Area (Km^2)	% of land cover	Area (Km^2)	% of land cover	Area (Km^2)	% of land cover
Evergreen forest	550.1	29.7	637.4	34.40	808.4	43.6	617.9	33.4
Deciduous forest	388.1	21.0	477.9	25.80	264.5	14.3	391.1	21.1
Sparsely deciduous forest	387.8	20.9	232.6	12.60	309.6	16.7	456.5	24.6
Wood and shrub land	245.3	13.2	261.9	14.14	233.8	12.6	176.7	9.5
Water body	38.4	2.1	62.8	3.39	66.1	3.6	26.4	1.4
Deforested area	161.0	8.7	95.1	5.13	56.5	3.1	55.3	3.0
Agricultural land	81.4	4.4	84.4	4.56	113.2	6.1	128.2	6.9
Total	1852.1	100	1852.1	100	1852.1	100	1852.1	100

Figure 3.  Flow chart of the methodology adopted for polarimetric classification.

Figure 4.  (a) Alpha, (b) entropy, and (c) anisotropy images of PALSAR data.

Figure 5.  (a) H/A/Alpha (H-Green; A-Red; Alpha-Blue) color image and (b) H/A/Alpha-based land use map (MLC).

Figure 6.  (a) Freeman–Durden three component-based image of PALSAR and (b) Yamaguchi four component-based image of PALSAR (R: double-bounce scattering, G: volume scattering, and B: surface scattering).

Figure 7.  Deciduous forest covered by grass (>50 cm height).

Figure 8.  (a) Freeman–Durden three component-based land use map and (b) Yamaguchi four component-based land use map (MLC).

Table 3. Confusion matrix of Cloude–Pottier H/A/Alpha-based MLC.

	Evergreen forest	Deciduous forest	Water body	Sparsely deciduous forest	Wood and shrub land	Deforested area	Agricultural land	Total	Users accuracy
Evergreen forest	60	3	0	0	0	0	0	63	95.2%
Deciduous forest	1	43	4	1	0	0	0	49	87.7%
Water body	0	2	61	0	0	0	0	63	96.8%
Sparsely deciduous forest	0	0	5	49	2	0	1	57	85.9%
Wood and shrub land	0	1	0	1	29	1	2	34	85.3%
Deforested area	0	0	2	0	0	49	6	57	85.9%
Agricultural land	0	0	0	0	1	2	16	19	84.2%
Total	61	49	72	51	32	52	25	342	–
Producer's accuracy	98.4%	87.8%	84.7%	96.1%	90.6%	94.2%	64%	–	–

Table 4. Confusion matrix of Freeman–Durden three component-based MLC.

	Evergreen forest	Deciduous forest	Water body	Sparsely deciduous forest	Wood and shrub land	Deforested area	Agricultural land	Total	Users accuracy
Evergreen forest	61	4	0	0	1	0	0	66	92.4%
Deciduous forest	0	44	0	0	3	0	0	47	93.6%
Water body	0	0	66	0	0	7	9	82	80.5%
Sparsely deciduous forest	0	0	0	53	0	0	0	53	100%
Wood and shrub land	0	1	0	0	29	0	0	30	96.6%
Deforested area	0	0	6	0	0	44	2	52	84.6%
Agricultural land	0	0	0	0	0	0	12	12	100%
Total	61	49	72	53	33	51	23	342	–
Producer's accuracy	100%	90%	92%	100%	87%	86%	52%	–	–

Table 5. Confusion matrix of Yamaguchi four component-based MLC.

	Evergreen forest	Deciduous forest	Water body	Sparsely deciduous forest	Wood and shrub land	Deforested area	Agricultural land	Total	Users accuracy
Evergreen forest	61	0	0	0	0	0	0	61	100%
Deciduous forest	0	49	0	0	0	0	0	49	100%
Water body	0	0	64	0	0	0	0	64	100%
Sparsely deciduous forest	0	0	0	53	0	0	0	53	100%
Wood and shrub land	0	0	0	0	33	0	0	33	100%
Deforested area	0	0	8	0	0	46	7	61	75.4%
Agricultural land	0	0	0	0	0	5	16	21	76.2%
Total	61	49	72	53	33	51	23	342	–
Producer's accuracy	100%	100%	89%	100%	100%	90%	70%	–	–

Table 6. Accuracy assessment of MLC.

	Overall accuracy	Kappa coefficient
Cloude–Pottier-based classification	89.7%	0.88
Freeman–Durden-based classification	90.3%	0.88
Yamaguchi based-classification	94.1%	0.93

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