[1]邢东兴,王明军,焦俏,等. 探寻葡萄树遥感辨识的最佳时相与方法[J].西北林学院学报,2019,34(5):179-186.[doi:10.3969/j.issn.1001-7461.2019.05.28]
　XING Dong-xing,WANG Ming-jun,JIAO Qiao,et al. The Best Phase and the Optimal Identification Method for Identifying Grape Tree Species[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2019,34(5):179-186.[doi:10.3969/j.issn.1001-7461.2019.05.28]
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 探寻葡萄树遥感辨识的最佳时相与方法()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第34卷
期数:
2019年第5期
页码:
179-186
栏目:
出版日期:
2019-09-30

文章信息/Info

Title:
 The Best Phase and the Optimal Identification Method for Identifying Grape Tree Species
文章编号:
1001-7461(2019)05-0179-08
作者:
 邢东兴1; 王明军2; 焦俏1; 封建民1; 车自立1
 （1.咸阳师范学院 资源环境学院，陕西 咸阳 712000；2.咸阳师范学院 物理与电子工程学院，陕西 咸阳 712000）
Author(s):
 XING Dong-xing1; WANG Ming-jun2; JIAO Qiao1; FENG Jian-min1; CHE Zi-li1
 (1.Department of Resources and Environment,Xianyang Normal University,Xianyang 712000,Shaanxi,China; 2.Department of Physics and Electronic Engineering,Xianyang Normal University,Xianyang 712000,Shaanxi,China)
关键词:
 ; 葡萄树; 遥感影像; 最佳时相; 果树辨识; 光谱指数
Keywords:
 ; grape tree;  remote sensing image;  the best phase;  fruit tree identification;  spectral index
分类号:
S771.8
DOI:
10.3969/j.issn.1001-7461.2019.05.28
文献标志码:
A
摘要:
 利用41景卫星影像探寻葡萄树遥感辨识的最佳时相与方法。首先对各景影像分别进行了预处理，随后利用6类探试性方法(即地物光谱比较、波段差分或比值分析、光谱指数求算与分析、光谱指数变化追踪、影像复合与辨识方法协同分析)对探试组影像进行了辨识分析，并从中选出3种较佳的辨识方法，最后利用优选的3种方法对验证组影像进行了辨识验证。结果表明：1）在4月中旬至5月初的影像中，仅采用NDVI阈值便可将葡萄树与别种成年果树、小麦予以区分，但低龄的别种果树、有草撂荒地等与葡萄树易混；2）在5月底至6月中旬的影像中，采用(ρBLUE+ρGREEN+ρRED)与NDVI的双重阈值可将葡萄树与其他地物较好的区分开来；3）在上述2时段影像复合、所用辨识方法协同的情况下，可显著提高葡萄树的辨识精度（葡萄树类的正确识别率可达90.42%，总体分类精度可达96.53%）；4）葡萄树遥感辨识的较佳时相为4月中旬至5月初,最佳时相为5月底至6月中旬。
Abstract:
 The paper attempted to find out the best phase and the optimal identification method for identifying grape trees by using 41 satellite remote sensing images.Firstly,the images of each period were preprocessed by using image processing technology.Then,the three better identification methods were selected from the six kinds of tentative identification methods which were used in the test group of image identification and analysis.Finally,the verification group images were verified by using the three better identification methods.The conclusions were as follows.1) From mid-April to early May when grape trees had lower NDVI values,they could be distinguished from other adult fruit tree species and wheat by using NDVI threshold.But they were difficult to be distinguished from other young fruit tree species and abandoned land with grass.2) From the end of May to the middle of June,grape trees had high reflectivity in visible and near infrared bands.They could be distinguished from other ground objects by the double threshold of (ρBLUE+ρGREEN+ρRED) and NDVI.3) The identification precision of grape trees could be improved significantly in the circumstances of the above two periods by the recombination of the images and the collaboration of the identification method (the improved correct recognition rate of grape trees could reach 90.42%,the overall classification accuracy was 96.53%).4) The better phase for remote sensing identification of grape trees was from the middle of April to the beginning of May,from the end of May to the middle of June,and the best phase was from the end of May to the middle of June.

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备注/Memo

备注/Memo:
 收稿日期：2018-11-06修回日期：2019-01-02
基金项目：国家自然科学基金（61771385）；陕西省优势学科建设项目（060103）。
作者简介：邢东兴，男，博士，工程师，研究方向：农业遥感与精准农业。E-mail:3036310771@qq.com
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