[1]董亚坤,王钰,何紫玲,等. 基于GEE的洱海流域土地利用/覆被分类算法对比研究[J].西北林学院学报,2024,39(1):28-35.[doi:10.3969/j.issn.1001-7461.2024.01.04]
　DONG Ya-kun,WANG Yu,HE Zi-ling,et al. Comparison of Land Use/Cover Classification Algorithms in the Erhai Watershed Based on GEE[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2024,39(1):28-35.[doi:10.3969/j.issn.1001-7461.2024.01.04]
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 基于GEE的洱海流域土地利用/覆被分类算法对比研究()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第39卷
期数:
2024年第1期
页码:
28-35
栏目:
出版日期:
2024-01-31

文章信息/Info

Title:
 Comparison of Land Use/Cover Classification Algorithms in the Erhai Watershed Based on GEE
文章编号:
1001-7461(2024)01-0028-08
作者:
 董亚坤1; 3; 王钰1; 3; 何紫玲1; 3; 王鹏1; 3; 赵昊2; 3; 曾维军1; 3*
 （1.云南农业大学 水利学院，云南 昆明 650201；2.云南农业大学 资源与环境学院，云南 昆明 650201；3.自然资源部 云南山间盆地土地利用野外科学观测研究站，云南 昆明 650201）
Author(s):
 DONG Ya-kun1; 3; WANG Yu1; 3; HE Zi-ling1; 3; WANG Peng1; 3; ZHAO Hao2; 3; ZENG Wei-jun1; 3*
 (1.College of Water Resources,Yunnan Agricultural University,Kunming 650201,Yunnan,China; 2.College of Resources and Environment,Yunnan Agricultural University,Kunming 650201,Yunnan,China; 3.Yunnan Intermountain Basin Land Use Field Scientific Observation and Research Station,Ministry of Natural Resources,Kunming 650201,Yunnan,China)
关键词:
 ; GEE; 洱海流域; 土地利用/覆被变化; 分类算法; RF
Keywords:
 ; GEE;  Erhai watershed;  land use/cover change;  classification algorithm;  RF
分类号:
S714.9
DOI:
10.3969/j.issn.1001-7461.2024.01.04
文献标志码:
A
摘要:
 快速准确地进行复杂高原山区的土地覆被长时序自动分类，可为国土规划、资源利用提供依据。利用GEE云平台，选取Landsat影像地表反射率、植被指数、水体指数、DEM 4种空间数据集作为土地覆被分类的基础和辅助数据，分别运用CART、RF和SVM 3种分类算法，实现洱海流域土地覆被信息的自动提取和精度对比。结果表明：1）3种分类算法中，RF的总体分类精度最高，SVM的总体精度最低；RF是洱海流域LULC的最适宜分类算法。2）采用光谱指数、地形特征等辅助数据集会进一步提高解译精度，而样本点的选取是最主要的影响因素。3）Erhai_RF能够达到较高的精度，同时更加突出细节特征，在局部实际分类精度上会更高。研究结果可为洱海流域长时序土地覆被数据产品智能快速提取以及最优分类算法筛选提供方法和技术支撑。
Abstract:
 In complex highland and mountainous areas,rapid and accurate long-term automatic land cover classification can serve as a foundation for land planning and resource utilization.In this paper,four spatial datasets,namely Landsat image surface reflectance,vegetation index,water body index,and DEM,were selected as the basis and supporting data for land cover classification by using the GEE platform.Three classification algorithms,CART,RF,and SVM,were applied to automatically extract and compare the accuracy of land cover type information in the Erhai watershed.The results showed that 1) the classification accuracy of RF was the highest,and the overall accuracy of SVM was the lowest among the three classification algorithms.RF was a optimal classification algorithm for LULC in the Erhai basin.2) The use of supporting data sets further improved the accuracy of the interpretation.The selection of sample points was the key influence.3) Erhai_RF was capable of achieving higher accuracy.Meanwhile,the detailed features were more prominent.It will be more accurate in terms of local actual classification.This study can provide methodological and technical support for intelligent and rapid extraction of long-time series land cover data products and screening of optimal classification algorithms in the Erhai watershed.

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备注/Memo

备注/Memo:
 收稿日期：2022-12-31修回日期：2023-02-17
基金项目：国家自然科学基金地区项目(41961040)；云南省农业联合专项面上项目（202101BD070001-101）；云南省中青年学术和技术带头人后备项目（2023HB）。
第一作者：董亚坤。研究方向：资源与环境遥感。E-mail:2447849115@qq.com
*通信作者：曾维军，硕士生导师，副教授。研究方向：资源与环境遥感。E-mail:zengweijunde@163.com
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