随机森林协同Sentinel-1/2的东营市不透水层信息提取

doi:10.6046/zrzyyg.2020310

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摘要

不透水层是表征人类活动的重要指标,及时精确的不透水层信息对区域生态环境保护有重要意义。以山东省东营市为研究区,探索了一种基于多源Sentinel-1/2影像和随机森林的不透水层提取方法。通过对比实验发现,随机森林结合地表反射率特征、纹理特征和后向散射系数能够降低暗不透水层和亮不透水层与裸土的混淆现象,可以有效改善不透水层的估算精度(总体精度达到93.37%,Kappa系数达到0.925 8)。研究结果揭示了随机森林协同Sentinel-1和Sentinel-2数据在不透水层信息提取方面有着广泛的应用前景,为融合多源数据对黄河三角洲区域遥感监测提供了参考。

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	刘春亭
	冯权泷
	金鼎坚
	史同广
	刘建涛
	朱明水

关键词 ：东营市, 不透水层, Sentinel-2, Sentinel-1, 纹理, 随机森林

Abstract：

An impervious layer is an important indicator of human activities. Timely and accurate information of impervious layers is of great significance for the protection of the ecological environment. Taking the Yellow River Delta (Dongying City) as the study area, this study explores a novel extraction method of impervious layers by combining the random forest classification with Sentinel-1/2 data. According to comparative experiments, the confusion between dark and light impervious layers and bare soil can be reduced through the combination of the random forest algorithm with surface reflectance characteristics, texture characteristics, and backscatter coefficient, thus effectively improving the estimation accuracy of impervious layers (overall accuracy: 93.37%, Kappa coefficient: 0.925 8). The results of this study reveal that the random forest algorithm combined with Sentinel-1/2 data is a promising approach in the information extraction of impervious layers, which will provide a reference for the remote sensing monitoring of the Yellow River Delta through the integration of multi-source data.

Key words： Dongying City impervious layer Sentinel-2 Sentinel-1 texture random forest

收稿日期: 2020-09-27 出版日期: 2021-09-24

ZTFLH:

TP79

基金资助:国家自然科学基金项目“多策略协同的区域乡村聚落遥感识别及演化机制和生态环境影响分析研究”(42171113);国家重点研发计划-政府间国际科技创新合作重点专项“中蒙牧草多源遥感监测关键技术研发”(2018YFE0122700);山东建筑大学校内博士基金“多策略协同的城市典型地表要素遥感提取”(XNBS1903)

通讯作者: 刘建涛

作者简介: 刘春亭(1996-),女,硕士研究生,主要从事遥感信息提取及应用研究。Email: ctliu96@163.com。

引用本文:

刘春亭, 冯权泷, 金鼎坚, 史同广, 刘建涛, 朱明水. 随机森林协同Sentinel-1/2的东营市不透水层信息提取[J]. 自然资源遥感, 2021, 33(3): 253-261.
LIU Chunting, FENG Quanlong, JIN Dingjian, SHI Tongguang, LIU Jiantao, ZHU Mingshui. Application of random forest and Sentinel-1/2 in the information extraction of impervious layers in Dongying City. Remote Sensing for Natural Resources, 2021, 33(3): 253-261.

链接本文:

https://www.gtzyyg.com/CN/10.6046/zrzyyg.2020310 或 https://www.gtzyyg.com/CN/Y2021/V33/I3/253

Fig.1 研究区Sentinel-2 B4(R),B3(G),B2(B)波段合成影像

Tab.1 Sentinel-2波段信息

Fig.2 技术流程

Tab.2 分类体系及样本数量

Fig.3 样本点分布

Tab.3 分类结果混淆矩阵

Fig.4 不透水层提取结果

Tab.4 Sentinel数据组合方案

Tab.5 分类精度统计

Fig.5 不同数据方案分类结果

Tab.6 随机森林、支持向量机、决策树分类精度比较

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