Phenological period identification of oilseed rape based on time-series PolSAR image and decision tree model

doi:10.3969/j.issn.1004-1524.2021.11.14

Acta Agriculturae Zhejiangensis ›› 2021, Vol. 33 ›› Issue (11): 2116-2127.DOI: 10.3969/j.issn.1004-1524.2021.11.14

• Environmental Science • Previous Articles Next Articles

Phenological period identification of oilseed rape based on time-series PolSAR image and decision tree model

LI Shitao^a(), ZHANG Wangfei^b^,^*(), ZHAO Lixian^b, WANG Xiyuan^b

a. School of Geography and Ecotourism, Southwest Forestry University, Kunming 650224, China
b. Forest College, Southwest Forestry University, Kunming 650224, China

Received:2020-12-15 Online:2021-11-25 Published:2021-11-26
Contact: ZHANG Wangfei

Abstract

Abstract:

Crop phenological period identification plays an important role in agricultural condition monitoring. Timely and accurate crop phenological period identification is of great significance for evaluating crop growth trend and improving the agricultural information management level effectively.In this study, we selected oilseed rape as an example and proposed a crop phenological period identification method through polarimetric synthetic aperture radar (PolSAR) data and decision tree algorithms. First, polarimetric SAR parameters were extracted through three popular polarimetric decomposition methods. Their dynamic responses to oilseed rape phenological periods were also analyzed. Then, the parameters extracted by the three polarimetric decomposition methods were used to train and validate the decision tree models, five oilseed rape phenological periods were identified. Finally, confusion matrices were used to verify feasibility of the constructed decision models.The results showed that polarimetric SAR decomposition parameters, including scattering angle(Alpha), eigenvalue(L2, L3), pseudo-entropy(P2) and target azimuth (Beta1) parameters from H/A/alpha decomposition method; ground scattering (Ground) and odd scattering (Odd) parameters from Freeman-Durden decomposition method; odd scattering (Odd_Y) and helix scattering (Helix) parameters from Yamaguchi decomposition method showed great sensitivity to changes of oilseed rape phenological period.The decision tree models were more accurate to classify the phenology of rapeseed. Among the results, primitive decision tree model established based on the combination of extracted parameters from three polarimetric decomposition methods had the highest classification accuracy, the overall classification accuracy was 94%. The results also showed the sensitivity of PolSAR parameters to phenological changes of oilseed rape and the effectiveness of decision tree model in identification of oilseed rape phenological period.

Key words: rape, phenological identification, Radarsat-2, polarimetric decomposition, decision-tree

CLC Number:

S565.4
TP75

LI Shitao, ZHANG Wangfei, ZHAO Lixian, WANG Xiyuan. Phenological period identification of oilseed rape based on time-series PolSAR image and decision tree model[J]. Acta Agriculturae Zhejiangensis, 2021, 33(11): 2116-2127.

Figures/Tables 10

References 27

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生长发育时期 Growth period	播后时间 Days after sowing/d	物候阶段 Phenological phase
苗期Growth period	1-15	S1
蕾薹期Grey moss period	16-39	S2
花期Flowering period	40-63	S3
角果成熟期Ripening stage of pod	64-87	S4
成熟衰落期Maturity and decay period	88-110	S5

生长发育时期 Growth period	播后时间 Days after sowing/d	物候阶段 Phenological phase
苗期Growth period	1-15	S1
蕾薹期Grey moss period	16-39	S2
花期Flowering period	40-63	S3
角果成熟期Ripening stage of pod	64-87	S4
成熟衰落期Maturity and decay period	88-110	S5

分解方法 Decomposition methods	分解参数 Decomposition parameters	描述 Description
H/A/alpha分解 H/A/alpha decomposition	Alpha、Anisotropy、Entropy、 Lambda (Span)	基于H/A/alpha的参数:目标散射角、反熵、散射熵、散射特征值(功率) Parameters based on H/A/alpha: target scattering angle, inverse entropy, scattering entropy, scattering eigenvalue (power)
	Alpha1、Alpha2、Alpha3;Beta1、 Beta2、Beta3;Delta1、Delta2、 Delta3;Gamma1、Gamma2、 Gamma3	基于特征向量的参数:3种散射机制对应的散射角,目标方位角,相位角差 Parameters based on eigenvectors: scattering angles corresponding to the three scattering mechanisms, target azimuth, phase angle difference
	L1、L2、L3;P1、P2、P3;Pedestal; RVI	基于特征值的参数:3种散射机制对应的特征值,3种散射机制对应的熵,极化特征的基准高度,雷达植被指数 Parameters based on eigenvalues: eigenvalues corresponding to the three scattering mechanisms, entropy corresponding to the three scattering mechanisms, reference height of the polarization characteristics, radar vegetation index (RVI)
Freeman-Durden 二、三分量分解 Freeman-Durden two-and three-component decomposition	Ground、Canopy、Odd、Dbl、Vol	地面散射、冠层散射分量、奇次散射、偶次散射与体散射分量 Ground scattering, canopy scattering component, odd scattering, even scattering and volume scattering component
Yamaguchi四分量分解 Yamaguchi four- component decomposition	Odd_Y、Dbl_Y、Vol_Y、Helix	奇次散射、偶次散射、体散射与螺旋体散射分量 Odd scattering, even scattering, volume scattering and helix scattering components

分解方法 Decomposition methods	分解参数 Decomposition parameters	描述 Description
H/A/alpha分解 H/A/alpha decomposition	Alpha、Anisotropy、Entropy、 Lambda (Span)	基于H/A/alpha的参数:目标散射角、反熵、散射熵、散射特征值(功率) Parameters based on H/A/alpha: target scattering angle, inverse entropy, scattering entropy, scattering eigenvalue (power)
	Alpha1、Alpha2、Alpha3;Beta1、 Beta2、Beta3;Delta1、Delta2、 Delta3;Gamma1、Gamma2、 Gamma3	基于特征向量的参数:3种散射机制对应的散射角,目标方位角,相位角差 Parameters based on eigenvectors: scattering angles corresponding to the three scattering mechanisms, target azimuth, phase angle difference
	L1、L2、L3;P1、P2、P3;Pedestal; RVI	基于特征值的参数:3种散射机制对应的特征值,3种散射机制对应的熵,极化特征的基准高度,雷达植被指数 Parameters based on eigenvalues: eigenvalues corresponding to the three scattering mechanisms, entropy corresponding to the three scattering mechanisms, reference height of the polarization characteristics, radar vegetation index (RVI)
Freeman-Durden 二、三分量分解 Freeman-Durden two-and three-component decomposition	Ground、Canopy、Odd、Dbl、Vol	地面散射、冠层散射分量、奇次散射、偶次散射与体散射分量 Ground scattering, canopy scattering component, odd scattering, even scattering and volume scattering component
Yamaguchi四分量分解 Yamaguchi four- component decomposition	Odd_Y、Dbl_Y、Vol_Y、Helix	奇次散射、偶次散射、体散射与螺旋体散射分量 Odd scattering, even scattering, volume scattering and helix scattering components

精度Accuracy	S1	S2	S3	S4	S5
制图精度	90.28	95.79	94.74	94.74	89.47
Mapping accuracy
用户精度	94.20	92.86	90.90	97.83	90.42
User accuracy

Phenological period identification of oilseed rape based on time-series PolSAR image and decision tree model

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物候期 Phenological phase	S1	S2	S3	S4	S5	总计 Total
S1	65	7	0	0	0	72
S2	4	91	0	0	0	95
S3	0	0	90	0	5	95
S4	0	0	1	90	4	95
S5	0	0	8	2	85	95
总计Total	69	98	99	92	94

决策树模型 Decision tree model	极化分解方法Polarization decomposition method
决策树模型 Decision tree model	Freeman-Durden分解 Freeman decomposition	Yamaguchi分解 Yamaguchi decomposition	H/A/alpha分解 H/A/alpha decomposition	3种分解组合 Three kinds of decomposition synthesis
原始决策树Primitive decision tree	89.45	89.34	93.40	94.00
minleaf决策树Minleaf decision tree	82.96	84.87	88.63	89.54
剪枝决策树Pruning decision tree	86.13	87.83	92.21	91.61

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