玉米农田冠层光合参数的多光谱遥感反演

Estimating canopy photosynthetic parameters in maize field based on multi-spectral remote sensing

冠层光合参数的准确定量遥感反演是生态系统遥感模型的核心与关键。基于2011年玉米(Zea mays)整个生长发育期的冠层光谱反射率、生态系统CO2通量、微气象因子以及玉米光合生理生态指标的观测数据,开展了玉米农田生态系统冠层光合能力(Pmax,最大光合速率)与光合效率(εN,净CO2通量交换/吸收光合有效辐射(NEECO2/APAR);εG,总初级生产力/吸收光合有效辐射(GPP/APAR);α,表观量子效率)参数的多光谱遥感反演能力评估研究。结果表明,Pmax和α在整个生长季呈现单峰型变化趋势,分别于7月底、8月初达到峰值,而光合效率参数εN和εG在玉米营养生长早期数值较高,随着玉米生长发育迅速降低,而后呈现单峰型的变化趋势,峰值出现时间基本与Pmax最大值发生时间一致。基于两波段任意组合的遥感植被指数NDVI(normalized difference vegetation index)、RVI(ratio vegetation index)、WDRVI(wide dynamic range vegetation index)、EVI2(2-band enhanced vegetation index)和CI(chlorophyll index)与玉米冠层4个光合参数的统计分析表明,EVI2对冠层光合效率与光合能力参数的反演与表征效果最佳。研究表明,多光谱遥感信息对玉米生态系统冠层光合参数的变异具有较强的敏感性,可以用来监测玉米冠层光合作用的季节动态变化以及准确定量评估作物生产力和生态系统CO2交换能力。

Aims Determination of canopy photosynthetic parameters is key to accurate simulation of ecosystem function by using remote sensing methods. Currently, remote estimation of vegetation canopy structure characteristics has been widely adopted. However, directly estimating photosynthetic variables（photosynthetic capacity and efficiency） at canopy scale based on field spectrometry combined with CO2 flux measurements is rare. Methods In this study, we remotely estimated solar radiation use efficiency（εN, net ecosystem CO2 exchange/absorbed photosynthetically active radiation（NEECO2/APAR）; εG, gross primary productivity/absorbed photosynthetically active radiation（GPP/APAR）; α, apparent quantum efficiency） and photosynthetic capacity（Pmax） based on in situ measurements of spectral reflectance and ecosystem CO2 fluxes, along with observational data on micrometeorological factors during the entire growing season for a maize canopy in Northeast China. Important findings Results showed that the seasonal variations in Pmax and α exhibited a single peak; whereas the values of εN and εG were higher at the start of vegetative stage and then rapidly decreased with the development of maize until displaying a single peak at the intermediate and late stages of the growing season, coinciding with the occurrence of peak values in Pmax. A comparison was made on the predictive performance based on normalized difference vegetation index（NDVI）, ratio vegetation index（RVI）, wide dynamic range vegetation index（WDRVI）, 2-band enhanced vegetation index（EVI2）, and chlorophyll index（CI） in estimating four canopy photosynthetic parameters with any combination of two separate wavelengths at the range of 400–1 300 nm, which showed that EVI2 was most closely and linearly related to photosynthetic capacity and efficiency. This study demonstrates that multi-spectral remote sensing information is sensitive to the variations in canopy photosynthetic parameters in maize field and can be used to quantitatively monitor seasonal dynamics of canopy photosynthesis, and to accurately assess crop productivity and ecosystem CO2 exchange capacity.