Combining Textures and Spatial Features to Extract Tea Plantations Based on Object-Oriented Method by Using Multispectral Image

类别	数据层	对象特征指标	指标数
光谱	蓝绿红近红外	各个波段光谱反射率均值/标准差	14
	归一化植被指数归一化水体指数燃烧面积指数调整土壤亮度的植被指数亮度指数	植被指数均值
	对象内部最大差值	其他指数均值
纹理	对比度相异度角二矩阵相关性熵同质性	灰度共生矩阵	6
空间	分割对象	紧致度面积长/宽	3

Table 2. Comparison of the accuracies of object-oriented supervision classification

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Table 2. Comparison of the accuracies of object-oriented supervision classification

类型	贝叶斯分类		决策树分类		随机森林分类
类型	生产者精度/%	使用者精度/%	生产者精度/%	使用者精度/%	生产者精度/%	使用者精度/%
茶园	67.23	75.33	68.84	83.83	70.54	87.13
森林	96.82	93.72	96.71	91.44	97.83	93.72
农田	44.31	52.74	54.62	66.21	69.68	74.44
不透水层	80.00	65.82	91.42	83.62	98.41	84.93
水体	82.13	88.53	80.86	92.34	88.54	84.64
统计	Kappa=0.70 总体精度/%=87.73		Kappa=0.72 总体精度/%=88.52		Kappa=0.78 总体精度/%=91.23

Table 3. Comparison of the accuracies of pixel-wise RF and object-oriented RF for tea plantations extraction

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Table 3. Comparison of the accuracies of pixel-wise RF and object-oriented RF for tea plantations extraction

类型	基于像元的多分类		类型	面向对象的二分类
类型	生产者精度/%	使用者精度/%	类型	生产者精度/%	使用者精度/%
茶园	55.43	63.71	茶园	76.53	92.74
森林	74.54	80.23	其他	96.81	94.63
农田	49.40	53.74
不透水层	63.63	71.12
水体	78.82	83.94
统计	Kappa=0.58 总体精度/%=71.42			Kappa=0.85 总体精度/%=94.74

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. Combining Textures and Spatial Features to Extract Tea Plantations Based on Object-Oriented Method by Using Multispectral Image[J]. Spectroscopy and Spectral Analysis, 2021, 41(8): 2565

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Paper Information

Category: Research Articles

Received: Jul. 17, 2020

Accepted: --

Published Online: Sep. 8, 2021

The Author Email:

DOI:10.3964/j.issn.1000-0593(2021)08-2565-07

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