地貌形态多尺度综合分类方法

doi:10.13866/j.azr.2022.02.30

Abstract

Abstract:

Landform objects span a broad range of sizes. Existing automatic landform classification methods do not fully consider size, however, which restricts classification accuracy. This study proposes a multi-scale integrated classification method for landform that considers the size of different features. The method consists of three steps: multi-scale segmentation, screening according to scale order, and multi-scale merging. The screening according to scale order is an iterative confirmation process of classified objects based on multi-scale feature extraction and supervised classification, with small scale (small size) priority and probability maximization as criteria. According to experimental results from the Loess Plateau, the method is simple and reliable (overall accuracy reached 75.16% and the Kappa coefficient reached 0.71) and can be used for detailed classification of landform.

Key words: landforms, classification, multi-scale, Loess Plateau

YANG Weitao,SUN Jianguo,MA Hengli,HUANG Zhuo. A multi-scale integrated classification method for landforms[J].Arid Zone Research, 2022, 39(2): 638-645.

Figures/Tables 8

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References 25

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类别	UA/%	PA/%	类别	UA/%	PA/%
基岩山地	79.70	70.23	残塬沟谷	74.12	89.47
狭梁沟谷	71.01	76.96	宽塬沟谷	73.05	68.67
宽梁沟谷	72.5	84.41	低丘缓谷	72.28	74.12
平梁沟谷	70.38	86.25	河谷阶地	65.74	76.47
缓梁沟谷	69.56	58.94	盆地	76.53	66.58
缓峁沟谷	73.55	87.72	塬	51.6	45.14
总体精度	75.16%		Kappa系数	0.71

	总体精度/%	Kappa系数
尺度100	42.30	0.36
尺度200	48.91	0.45
尺度400	47.84	0.42
尺度800	48.66	0.43
尺度1200	32.19	0.25
尺度2000	24.98	0.16
本文方法	75.16	0.71

	G1		G2		G3
	PA/%	UA/%	PA/%	UA/%	PA/%	UA/%
100	59.43	58	70.61	75.75	80.16	87.95
200	58.95	65.73	71.7	77.68	75.74	73.09
400	61.88	71.57	77.72	75.81	72.8	75.99
800	65.64	65.84	75.03	81.93	60.71	68.14
1200	77.45	77.19	73.5	79.57	55.81	62.9
2000	79.56	77.86	67.25	68.43	46.25	55.54
MSIC	88.89	75.27	80.33	82.77	88.29	88.39

A multi-scale integrated classification method for landforms

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