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| 基于GF-1/WFV影像的青海祁连山地区地表覆被自动分类应用研究 |
| Study on Automatic Classification of Land Cover in Qinghai Qilian Mountain Area Based on GF-1/WFV Images |
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| DOI： |
| 中文关键词: GF-1/WFV 地表覆被 分类规则 自动提取 祁连山地区 |
| 英文关键词: GF-1/WFV Land cover Classification rules Automatic extraction Qilian |
| 基金项目:国家科技重大专项中国科学院“祁连山南坡矿区及周边受损生态系统植被修复技术研究与示范”基金资助项目（KFJ-EW-STS-125）；国家发改委“十二五”规划《祁连山生态保护与建设综合治理规划（2012—2020）》基金资助项目 |
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| 中文摘要: |
| 基于GF-1/WFV影像的地表覆被自动提取方法，利用青海祁连山地区复杂、独特的地表覆被垂直变化特征，建立以祁连山地区为例的水源涵养区地表覆被分类规则。结果表明，总体分类精度为9573%，Kappa值为0889 6，分类精度优于80%。尝试将网络远程视频监控系统应用在遥感解译中，选取样本点近距离验证典型地物类型，包括生态脆弱区（冰川）、生物多样性重点保护区（青海小叶杨原种保护地）等，分类精度为948%，应用潜力大。 |
| 英文摘要: |
| The classification rules for land cover in water source conservation area were established based on GF-1/WFV image automatic extraction and the complex unique vertical variation characteristics in Qilian mountain area. Results showed that the total classification accuracy was 95.73%， the Kappa was 0.889 6， the classification accuracy was greater than 80%. As an attempt of applying remote network video monitoring system on remotely sensing interpretation， and carrying out close verification for the typical objects at selected sample points， including ecological fragile area（glacier）and key protection area of biodiversity （Qinghai Populus simonii origin area）， the classification accuracy was 94.8%， showing it had vast potential on application. |
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