摘要
以江苏省高邮市汤庄镇2013年水稻田为研究区,以相同时期HJ-1A/1B卫星影像为数据源,提取研究区内水稻全生育期受稻纵卷叶螟危害的归一化植被指数(NDVI)、增强型植被指数(EVI)、近红外反射率(NIR)的光谱特征参数,揭示虫害发生及其演变特征,分析这些光谱特征参数与虫害发生、发展和危害程度之间的关系。结果表明:(1)稻纵卷叶螟虫害发生越严重,光谱特征参数变化越明显;(2)定性分析表明稻纵卷叶螟危害程度与两个田块的光谱特征参数差异均呈正相关关系。(3)对3个衡量指标和水稻卷叶率的定量相关分析表明,DNIR(正常水稻与受害水稻的NIR差值)与水稻卷叶率呈极显著相关(P<0.01),DEVI(正常水稻与受害水稻的EVI差值)与水稻卷叶率呈显著相关(P<0.05),而DNDVI(正常水稻与受害水稻的NDVI差值)与水稻卷叶率相关性不明显。可见,利用环境小卫星影像动态监测和预警稻纵卷叶螟的发生发展状况是可行的,可为虫害动态监测提供一种可能的方法。
Two experimental rice fields（one was used as a reference and the other was for target analysis） were conducted in Tangzhuang, Gaoyou of Jiangsu Province in 2013, and the Normalized Difference Vegetation Index（NDVI）, Enhanced Vegetation Index（EVI）, and Near-infrared Spectroscopy（NIR） were used to characterize the occurrence and evolution of C. medinalis, which were calculated from the satellite HJ-1A/1B retrieval data. A series of analyses were performed to disclose the relationship among these three indices and the occurrence frequency, severity, and evolution of C. medinalis. The results showed as follows：（1） The more the numbers of C. medinalis, the higher the changes of such characteristic parameters.（2） The positive correlations were found between the damage of C. medinalis and the discrepancy of characteristic parameters in these two experimental fields.（3） Quantitative correlation analyses showed that DNIR and folding leaf rate had a highly significant correlation（P0.01）, and DEVI and folding leaf rate had a significant correlation（P0.05）. While there was not significant between DNDVI and folding leaf rate. Therefore, it was feasible to using HJ satellite images to monitor and warn the outbreak and development of C. medinalis, which provided a new possible method to monitor dynamically the damage of C. medinalis.
出处
《中国农业气象》
CSCD
北大核心
2016年第4期464-470,共7页
Chinese Journal of Agrometeorology
基金
国家自然科学基金面上项目(41475106
41075086)
国家公益性行业(气象)科研专项(GYHY201306053)
江苏省农业科技自主创新项目(SCX(12)3058)
江苏省高校优势学科建设工程
关键词
稻纵卷叶螟
HJ-1A/1B卫星
归一化植被指数
增强型植被指数
高邮
Cnaphalocrocis medinalis
HJ-1A/1B satellite
Normalized Difference Vegetation Index
Enhanced Vegetation Index
Gaoyou
