干旱区研究

干旱区研究 >

2022 , Vol. 39 >Issue 2: 638 - 645

DOI: https://doi.org/10.13866/j.azr.2022.02.30

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地貌形态多尺度综合分类方法

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  • 1.兰州交通大学测绘与地理信息学院,甘肃 兰州 730070
    2.地理国情监测技术应用国家地方联合研究中心,甘肃 兰州 730070
    3.甘肃省地理国情监测工程实验室,甘肃 兰州 730070
杨维涛（1994-）,男,硕士研究生,主要从事数字地形分析、环境遥感应用研究. E-mail: 913117597@qq.com

收稿日期: 2021-05-18

  修回日期: 2021-11-19

  网络出版日期: 2022-03-30

基金资助

甘肃省科技计划资助(20YF3GA013);兰州交通大学优秀平台支持(201806)

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A multi-scale integrated classification method for landforms

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  • 1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China
    2. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, Gansu, China
    3. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, Gansu, China

Received date: 2021-05-18

  Revised date: 2021-11-19

  Online published: 2022-03-30

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摘要

地貌形态对象往往大小悬殊,跨越特定的空间尺度。现有的地貌形态自动分类方法尚未充分顾及该特点,分类精度受到制约。利用地貌形态的大小为尺度,提出1种涉及尺度跨越性的地貌形态多尺度综合分类方法,该方法由多尺度分割、按尺度顺序筛选和多尺度合并3个步骤构成。其中,按尺度顺序筛选是1个以多尺度特征提取和监督分类为基础、以小尺度（小尺寸）优先和概率最大化为准则的被分类对象迭代确认过程。以黄土高原为例的试验结果表明,该方法简便可靠（总体精度可以达到75.16%,Kappa系数可以达到0.71）,可用于地貌形态精细化分类。

关键词： 地貌形态; 分类; 多尺度; 黄土高原

本文引用格式

杨维涛,孙建国,马恒利,黄卓 . 地貌形态多尺度综合分类方法[J]. 干旱区研究, 2022 , 39(2) : 638 -645 . DOI: 10.13866/j.azr.2022.02.30

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

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