摘要
为了研究不同水分胁迫和不同时间尺度对拔节期青贮夏玉米水分亏缺指数(WDI)和陆气温差监测效果的影响,利用地面数据结合无人机遥感数据建立植被指数温度梯形空间,计算WDI干旱指数,并生成WDI分布图和陆气温差分布图。在不同的时间尺度和水分胁迫梯度下分析WDI、陆气温差与土壤含水率、气孔导度的相关性。结果表明,植被指数温度梯形空间和WDI分布图对短期降雨事件反应敏感;日间尺度下WDI、陆气温差与土壤含水率、气孔导度均表现了较好的相关性(R2为0.4~0.85);旬间尺度下WDI与土壤含水率、气孔导度的相关性(R2>0.68)明显优于陆气温差(R2<0.6);旬间尺度下100%充分灌溉时,WDI、陆气温差与土壤含水率、气孔导度均无显著相关性(R2<0.12);在不同水分胁迫下,WDI与气孔导度、土壤含水率均显著相关(R2为0.7283~0.82),而陆气温差与气孔导度、土壤含水率的相关性则出现较大差异(R2为0.3566~0.8074);与陆气温差相比,采用WDI实时监测青贮夏玉米旱情更为稳定。研究结果可为大田作物干旱信息的实时监测提供参考。
Vegetation index temperature mixed pixels affects the remote sensing monitoring of drought conditions, Water deficit index (WDI) was compared with surface minus air temperature ( T s T a ) as a water stress indicator which can overcome the difficulty. The experimental field was located in Dalat Banner, Inner Mongolia, and the experimental object was silage summer maize. Normalized difference vegetation index (NDVI) and land surface mixing temperature ( T s ) were extracted from UAV-acquired images (multispectral, thermal infrared). Maize physiological parameters and meteorological data were collected to establish WDI model, under three irrigation regimes. WDI model and remote sensing data (NDVI, T s ) were used to generate vegetation index-temperature trapezoidal space, WDI map, and T s T a map. WDI and T s T a were extracted in the sample area. WDI and T s T a were extracted in sample areas. The relationships between WDI or T s T a and soil water content/stomata conductance were analyzed. Results demonstrated that vegetation index-temperature trapezoidal space, WDI and T s T a map were sensitive to short-term drought response. WDI and T s T a showed similarity, both showed strong correlation with soil water content and stomata conductance ( R2 =0.4~0.85). At scale of ten days, the correlation between WDI and soil water content/stomata conductance ( R2 >0.68) was significantly higher than the correlation between T s T a and soil moisture content/stomata conductance ( R2 <0.6). At the scale of ten days, the effects of different water stress gradients on drought monitoring were analyzed. It was found that under sufficient irrigation, there was no significant correlation between WDI or T s T a and soil water content/stomata conductance ( R2 <0.12). Under different deficit irrigation, the correlation between WDI and stomata conductance/soil water content was significant ( R2 =0.728 3~0.82), the correlation between T s T a and stomata conductance/soil water content showed large fluctuations ( R2 =0.356 6~0.807 4). WDI had greater practicability and stability when monitoring the continuous change of drought compared with the difference in land temperature, at the scale of ten days.
作者
李星恕
程双飞
薛志
熊秀芳
韩文霆
张立元
LI Xingshu;CHENG Shuangfei;XUE Zhi;XIONG Xiufang;HAN Wenting;ZHANG Liyuan(College of Mechanical and Electronic Engineering,Northwest A&F University, Yangling, Shaanxi 712100,China;Institute of Water-saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling, Shaanxi 712100, China)
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2019年第9期177-185,共9页
Transactions of the Chinese Society for Agricultural Machinery
基金
陕西省水利科技项目(2017slk-7)
关键词
玉米
水分亏缺指数
无人机
多光谱
热红外
maize
water deficit index
UAV
multispectrum
thermal infrared