| 冬小麦冻害灾情及长势恢复的变化向量分析 |
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| 引用本文： | 王慧芳,顾晓鹤,董莹莹,王纪华,黄文江,郭 伟,王大成,王 堃.冬小麦冻害灾情及长势恢复的变化向量分析[J].农业工程学报,2011,27(11):145-150. |
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| 作者姓名： | 王慧芳 顾晓鹤 董莹莹 王纪华 黄文江 郭 伟 王大成 王 堃 |
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| 作者单位： | 1. 浙江大学农业遥感与信息技术应用研究所,杭州310012;北京农业信息技术研究中心,北京100097
2. 北京农业信息技术研究中心,北京,100097 |
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| 基金项目： | 国家自然科学青年基金项目（41001199）；北京市优秀人才计划项目（PYZZ090416001998）；北京市科技新星计划项目（2010B024） |
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| 摘 要： | 大尺度监测冬小麦冻害灾情，需要结合受冻后长势监测，以提高冻害监测精度。鉴于温度并非唯一冻害因子，且归一化植被指数（NDVI）易高估封垄前冬小麦覆盖度，该文引入基于多时相植被指数的变化向量分析法，进行冬小麦冻害灾情及受灾后长势监测研究。选取河北藁城2010年冬小麦冻害作为研究对象，利用多时相环境小卫星数据提取多种植被指数，构建变化向量并分析其动态变化趋势，结合冬小麦冻害光谱特征敏感性分析，建立冻害灾情遥感监测模型，并展开长势恢复程度监测。结果表明，变化向量分析法能有效地反映冬小麦受冻和长势恢复程度及空间分布，在基于多种植被指数建立的变化向量监测模型中，基于光谱结构不敏感指数SIPI建立的模型较精度最高，其冻害监测及长势恢复监测模型精度分别达83.3%、88.9%。因此，变化向量分析法能有效地监测冬小麦冻害灾情与灾后长势恢复情况，同时对其他作物灾害监测提供了途径。
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| 关 键 词： | 冻害，生长，恢复，冬小麦，变化向量分析 |
| 收稿时间： | 2011/1/18 0:00:00 |
| 修稿时间： | 2011/8/18 0:00:00 |
Monitoring freeze injury and growth recovery of winter wheat based on change vector analysis |
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| Wang Huifang,Gu Xiaohe,Dong Yingying,Wang Jihu,Huang Wenjiang,Guo Wei,Wang Dacheng and Wang Kun.Monitoring freeze injury and growth recovery of winter wheat based on change vector analysis[J].Transactions of the Chinese Society of Agricultural Engineering,2011,27(11):145-150. |
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| Authors: | Wang Huifang Gu Xiaohe Dong Yingying Wang Jihu Huang Wenjiang Guo Wei Wang Dacheng and Wang Kun |
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| Institution: | Wang Huifang1,2,Gu Xiaohe2,Dong Yingying1,Wang Jihua1,Huang Wenjiang2,Guo Wei2,Wang Dacheng1,Wang Kun2(1.Institute of Agriculture Remote Sensing and Information System Application,Zhejiang University,Hangzhou 310012,China,2.Beijing Research Centre for Information Technology in Agriculture,Beijing 100097 China) |
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| Abstract: | Currently, the basic method of monitor winter wheat freeze injury is concentrated on temperature retrieval and compared with normalized difference vegetation index before and after freeze injury. However, temperature is not only reason for freeze injury, and normalized difference vegetation index can lead to overestimate the winter wheat coverage before closing. So this paper selected the analysis of change vector which based on multi-temporal vegetation indexes to improve the monitoring freeze injury accuracy. Winter wheat freeze injury of Gaocheng as study object, various vegetation indexes were extracted from multi-temporal HJ data, change vector was built and the trend of dynamic changing was analyzed, combined with the sensitivity analysis of winter wheat freeze injury spectral character, the model of monitoring freeze injury situation disaster remote sensing was built, and monitoring the degree of growth recover. The result showed that the change vector analysis could reflect the distribution and degree of winter wheat freeze injury and recovery. Meantime the change vector model which based on the structure insensitive pigment index had the highest accuracy during based on the other vegetation indexes model, in addition, the model verification results were 83.3%, 88.9%, respectively. So the method of change vector analysis was effective for monitoring winter wheat freeze injury and growth recovery. This study could supply a new way to monitoring the other crop disaster. |
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| Keywords: | freezing growth recovery winter wheat change vector analysis |
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