基于 GEE 和多维特征集的锡林浩特露天矿区近 30 a 土地利用分类

金属矿山 ›› 2023, Vol. 52 ›› Issue (03): 234-241.

基于 GEE 和多维特征集的锡林浩特露天矿区近 30 a 土地利用分类

张来红¹秦婷婷² 泽仁卓格²张海涛¹ 佘长超¹ 李军² 张成业²

1. 神华北电胜利能源有限公司,内蒙古锡林浩特 026015;2. 中国矿业大学(北京) 地球科学与测绘工程学院,北京 100083

出版日期:2023-03-15 发布日期:2023-04-12
基金资助:
煤炭开采水资源保护与利用国家重点实验室 2020 年开放基金项目(编号:GJNY-20-113-14);中央高校基本科研业务费专项(编号:2022JCCXDC04,2022YQDC08)。

Land Use Classification of Xilinhot Open-pit Mining Area Based on GEE and Multi-dimensional Features in Recent 30 Years

ZHANG Laihong¹ QIN Tingting² ZEREN Zhuoge² ZHANG Haitao¹SHE Changchao¹ LI Jun² ZHANG Chengye²

1. Shenhua Beidian Shengli Energy Co. ,Ltd. ,Xilinhot 026015,China;2. College of Geoscience and Surveying Engineering,China University of Mining and Technology-Beijing,Beijing 100083,China

Online:2023-03-15 Published:2023-04-12

摘要/Abstract

摘要： 随着矿产资源的不断开采,矿区地表土地利用会发生频繁的变化,快速获取矿区开采过程中长时间序列连续的土地利用分类结果对于矿区土地治理与生态重建具有重要意义。基于 Google Earth Engine ( GEE)遥感云平台,对 Sentinel-2 和 Landsat 数据从光谱特征、纹理特征、地形特征 3 个方面构建多维特征集,采用随机森林算法分别建立了不同特征模型并测试精度以筛选出适合矿区场景的最优分类模型。以锡林浩特市露天矿区为研究区,开展了近 30 a(1991—2020 年)长时序土地利用分类研究。结果表明:① 基于 GEE 遥感云平台,能够高效、快速、准确地提取研究区 1991—2020 年近 30 a 的土地利用分类结果;② 光谱特征对分类精度具有决定性作用,融入纹理特征和地形特征能够有效提高矿区土地利用分类模型精度;③ Sentinel-2 数据特有的红边波段对植被具有较高的敏感性,能有效提高分类精度。长时间连续的监测结果能够有效了解锡林浩特市露天矿区土地利用的变化情况及规律,为进一步分析人类生产生活和环境变化对土地利用的影响提供了坚实的数据支撑。

关键词: 土地利用分类, GEE, 随时森林算法, 长时间序列, 多维特征

Abstract: With the continuous exploitation of mineral resources,land use types in mining areas change frequently. Obtaining the results of long-term land use classification in mining areas is of great significance to land management and ecological reconstruction in mining areas. Based on the Google Earth Engine,this paper constructs a multidimensional feature set for sentinel-2 and Landsat data from three aspects:spectral features,texture features,and terrain features. The random forest algorithm was used to build different feature models separately and test the accuracy to filter out the optimal classification model for the mining areas. A long-time series land use classification study was conducted by using the open-pit mine in Xilinhot as the study area in recent 30 years (from 1991 to 2020). The results indicate that:① Based on the GEE remote sensing cloud platform, the land use classification results of the study area in the past 30 years from 1991 to 2020 can be extracted efficiently,quickly and accurately. ② The spectral features play a decisive role in classification accuracy,and the incorporation of texture features and terrain features can effectively improve the accuracy of the land use classification model in mining areas. ③ The unique red-edge band of Sentinel-2 has a high sensitivity to vegetation,which can effectively improve the classification accuracy. The long-term continuous monitoring results can effectively understand the changes and laws of land use in Xilinhot open-pit mining area,and provide a solid data support for further analysis of the impact of human production and living and environmental changes on land use.

张来红, 秦婷婷, 泽仁卓格, 张海涛, 佘长超, 李军, 张成业. 基于 GEE 和多维特征集的锡林浩特露天矿区近 30 a 土地利用分类[J]. 金属矿山, 2023, 52(03): 234-241.

ZHANG Laihong, QIN Tingting, ZEREN Zhuoge, ZHANG Haitao, SHE Changchao, LI Jun, ZHANG Chengye. Land Use Classification of Xilinhot Open-pit Mining Area Based on GEE and Multi-dimensional Features in Recent 30 Years[J]. Metal Mine, 2023, 52(03): 234-241.

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