摘要
叶面积指数（LAI）作为陆地植被的重要生物物理参数,对农作物长势监测与产量估计具有重要的意义。本研究选取了华北平原一块玉米地为实验区,分设A、B、C、D四个样点,利用图像像素法和长宽法分别计算叶面积,比较二者异同,分析叶长、叶宽、长宽积与叶面积的协同关系,再结合样区植株的测量信息,计算LAI,并分析LAI（真测值）与仪器测量有效值LAIe之间的差异。结果表明：样区玉米叶面积基本处于200~800cm2之间;叶长、叶宽与叶面积呈现幂函数关系,长宽积与叶面积呈现线性关系,长宽积比叶长和叶宽能更好地模拟玉米叶面积。通过长宽积与叶面积模型反算得到长宽法修正系数为0.7017;A、B、C、D四个样点LAI分别为4.40、3.61、4.00、3.42;仪器测量值LAIe比真测值LAI小8.68%。这对LAI田间量测及小区域尺度有效扩展和农作物大面积遥感监测具有重要作用。
It is very important for corps growth monitoring and their yield estimation to measure Leaf Area Index （LAI） as an useful biophysical parameter of plant community. In this paper, a corn field over the North China Plain was chose as the study area, and A, B, C and D four sample points were arranged, and then the leaf areas of corn were calculated through a image pixel method of and a length-and-width method of plant leaf-area measurement respectively, based on color image gray processing and binarization, while they were analysed comparatively. The relationships between leaf area and length, width, and product of length and width of leaf were studied, and thus, the LAIs of corn leaf were calculated by using the surveying information （i.e., planting distance and row spacing） of corn plants over the sample subareas, which were compared with the effective LAIe values meanred by the LAI-2200C Plant Canopy Analyzer. The results showed that the leaf areas of the sample subareas were between 200- 800cm2; and the relationships between length, width of leaf and leaf area were power functions, respectively, while there was a linear relationship between product of length and width of leaf and leaf area, and the latter model could be used to simulate the corn leaf areas better than that of the two former where the correction coefficient of the previous length-and-width method was retrieved with the value of 0.7017 through it. The LAIs of A, B, C, D four sample subareas were 4.40, 3.61, 4.00 and 3.42, respectively, the average value of which was 8.68% higher than that of LAIes. This research would play a significant role in the LAI measurement in different fields, scale extent of sample areas and crops remote sensing monitoring.
出处
《农业网络信息》
2015年第11期30-37,共8页
Agriculture Network Information
基金
国家自然科学基金项目(编号:41171340
41101390)
中国科学院战略性先导科技专项(编号:XDB05020104)
中国农业科学院农业信息研究所科技创新工程项目(编号:CAAS-ASTIP-201X-AII-05)
关键词
玉米
叶面积
LAI
灰度化
二值化
回归分析
corn
leaf area
LAI
gray processing
image binarization
regression analysis
