Crops classification based on GF-3 satellite data and Η/Α/α- decomposition characteristic parameters

doi:10.3969/j.issn.1004-1524.2022.11.18

Acta Agriculturae Zhejiangensis ›› 2022, Vol. 34 ›› Issue (11): 2491-2503.DOI: 10.3969/j.issn.1004-1524.2022.11.18

• Environmental Science • Previous Articles Next Articles

Crops classification based on GF-3 satellite data and Η/Α/α- decomposition characteristic parameters

ZHAO Lixian(), ZHANG Wangfei(), LI Yun, ZHANG Tingwei, HUANG Guoran

College of Forestry, Southwest Forestry University, Kunming 650224, China

Received:2021-09-09 Online:2022-11-25 Published:2022-11-29
Contact: ZHANG Wangfei

Abstract

Abstract:

Based on the civil C-band synthetic aperture radar data of GF-3 satellite, Shannon entropy (SE) and its intensity components (SE_I) and polarization components (SE_P), single bounce eigenvalue relative difference (SERD), double bounce eigenvalue relative difference (DERD), polarization fraction (PF), pedestal height (PH), polarimetric asymmetry (PA) and radar vegetation index (RVI) were extracted from GF-3 full polarimetric data by Η/Α/ $α -$ polarization decomposition method. With application of support vector machine (SVM) and random forest (RF), the potential of these parameters extracted by Η/Α/ $α -$ decomposition from GF-3 data in crops classification was preliminarily explored. The results showed that when SERD, PH, PF, RVI and SE_P parameters were used alone, the classification accuracies were relatively high (82%-92%). When PA, DERD, SE and SE_I parameters were used alone, the classification accuracy was less than 80%. However, the combination of PA, DERD, SE and SE_I parameters improved the classification accuracies to 93.02% and 92.05%, respectively, under SVM and RF, and the Kappa coefficients were all greater than 0.8. Therefore, the nine characteristic parameters extracted by Η/Α/ $α -$ polarization decomposition from GF-3 data could well characterize the scattering characteristics of crops and could be used in crops classification.

Key words: extended parameters, GF-3 satellite, crops classification

CLC Number:

S127
P237

ZHAO Lixian, ZHANG Wangfei, LI Yun, ZHANG Tingwei, HUANG Guoran. Crops classification based on GF-3 satellite data and Η/Α/α- decomposition characteristic parameters[J]. Acta Agriculturae Zhejiangensis, 2022, 34(11): 2491-2503.

Figures/Tables 12

Fig.1 Schematic diagram of location of study area

Fig.2 Flowchart of crop classification based on Η/Α/ α - decomposition parameters and GF-3 polarimetric images

Fig.3 Statistical diagram of polarization scattering characteristics of 9 parameters derived fromΗ/Α/ α - decomposition DN, Digital number, the photopixel brightness value of the remote sensing image.

Table 1 List of polarization scattering characteristic statistics

参数 Parameter	小麦 Wheat	油菜 Rape	植被 Vegetation
DERD	0.62±0.06	0.55±0.03	0.57±0.03
PF	0.69±0.06	0.32±0.06	0.49±0.05
PA	0.78±0.06	0.56±0.14	0.71±0.08
PH	0.14±0.03	0.48±0.07	0.29±0.04
RVI	0.41±0.08	0.91±0.09	0.69±0.07
SERD	0.72±0.07	0.32±0.08	0.53±0.05
SE	1.54±0.43	0.58±0.32	2.92±0.96
SE_I	0.53±0.41	0.67±0.36	2.49±0.94
SE_P	1.06±0.22	0.15±0.06	0.43±0.11

Fig.4 Images of various parameters before and after segmentation

Fig.5 SVM classification results based on single parameter

Fig.6 RF classification results based on single parameter

Fig.7 Overall accuracy of SVM and RF classification based on single parameter

Table 2 Kappa coefficient of SVM and RF classification based on single parameter

参数Parameter	SVM	RF
DERD	0.33	0.23
PF	0.74	0.81
PA	0.43	0.34
PH	0.81	0.86
RVI	0.86	0.82
SERD	0.78	0.84
SE	0.58	0.57
SE_I	0.40	0.32
SE_P	0.89	0.87

Fig.8 Producer’s accuracy and user’s accuracy of SVM and RF classification based on single parameter

Table 3 Classification accuracy of combined parameters

参数组合 Combination of parameters	总体精度 Overall accuracy/%		Kappa系数 Kappa coefficient
参数组合 Combination of parameters	SVM	RF	SVM	RF
PA+SE	78.80	74.03	0.68	0.60
PA+SE_I	82.90	82.82	0.74	0.74
PA+SE+SE_I	86.00	86.44	0.79	0.80
PA+DERD+SE+SE_I	93.02	92.05	0.89	0.88

Fig.9 SVM and RF classification result based on combined parameters

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Crops classification based on GF-3 satellite data and Η/Α/α- decomposition characteristic parameters

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