文章摘要
多时相Sentinel-1影像反演玉溪典型烟区烤烟种植分布的方法
Identifying flue-cured tobacco in a typical cultivated area of Yuxi based on Sentinel-1 time series images
投稿时间:2021-10-19  
DOI:10.13254/j.jare.2021.0714
中文关键词: 烤烟,多时相,Sentinel-1,随机森林,合成孔径雷达
英文关键词: flue-cured tobacco, multi-temporal, Sentinel-1, random forest, synthetic aperture radar
基金项目:红塔烟草(集团)有限责任公司科技项目(S-6019001);土壤与农业可持续发展国家重点实验室开放课题(Y812000002);国家自然科学基金项目(4180070048)
作者单位E-mail
谢新乔 红塔烟草(集团)有限责任公司, 云南 玉溪 653100  
杨继周 红塔烟草(集团)有限责任公司, 云南 玉溪 653100  
邓邵文 红塔烟草(集团)有限责任公司, 云南 玉溪 653100  
李湘伟 红塔烟草(集团)有限责任公司, 云南 玉溪 653100  
秦发侣 玉溪师范学院, 云南 玉溪 653100
土壤与农业可持续发展国家重点实验室 (中国科学院南京土壤研究所), 南京 210008 
qinfl@yxnu.edu.cn 
王美艳 土壤与农业可持续发展国家重点实验室 (中国科学院南京土壤研究所), 南京 210008  
柳成柱 玉溪市烟草公司元江县分公司, 云南 元江 653300  
史学正 土壤与农业可持续发展国家重点实验室 (中国科学院南京土壤研究所), 南京 210008  
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中文摘要:
      为准确识别烤烟种植分布特征,基于2020年玉溪烤烟大田生长期不同时相的11景Sentinel-1卫星影像,结合野外实地调研,分析不同土地利用类型合成孔径雷达(SAR)极化信息的可区分度,并结合70%样地训练随机森林分类方法提取不同土地利用的分布范围,最后用30%调研样地验证烤烟种植的提取精度。结果表明,垂直发射垂直接收(VV)相较于垂直发射水平接收(VH)更能区分不同土地利用类型,VH、VV、VV+VH和VV+VH+VV/VH四种极化信息组合方式中,地物分类精度最高的为VV+VH组合,总体分类精度为87.6%,Kappa系数为0.847,其中,烤烟种植识别的制图精度为96.3%,用户精度为89.4%。在玉溪典型烟区采用多时相SAR识别烤烟种植分布,识别准确率基本能满足区域烤烟种植识别的精度要求。
英文摘要:
      To reveal the spatial distribution of flue-cured tobacco, 11 Sentinel-1 images obtained in the growing season of flue-cured tobacco in Yuxi City, Yunnan Province in 2020 were utilized in combination with field survey data. First, the polarization of the synthetic aperture radar(SAR)with different land use types were compared. Next, the random forest model was trained with 70% field survey data to make a land-use map. Finally, the identification accuracy of the flue-cured tobacco was validated with 30% field survey data. The results indicated that vertical transmit-vertical receive(VV)polarization distinguished land-use types better than the vertical transmit-horizontal receive(VH)polarization. In the four forms of polarization(i.e., VH, VV, VV+VH, and VV+VH+VV/VH), VV+VH produced the most accurate land-use map with a total accuracy of 87.6% and a Kappa coefficient of 0.847. Specifically, the producer accuracy of the fluecured tobacco was 96.3%, and the user accuracy was 89.4%. We conclude that the identification accuracy of the flue-cured tobacco distribution based on the multi-temporal SAR images could fulfill regional application needs.
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