以高光谱植被指数研究草坪色泽

Turf Color Evaluation by Hyperspectral Vegetation Indices

色泽是草坪外观质量重要的评价指标之一,叶绿素密度是影响色泽的重要因素。对警犬高羊茅(Festucaarundinacea Schreb.cv.Watchdog)、解放者草地早熟禾(Poa pratensis L.cv.Liberator)、普通狗牙根(Cynodon dac-tylon(L.)Pars.cv.Common)和普特匍匐翦股颖(Agrostis stolonifera L.cv.Putter)等4种草坪进行叶面喷施氮、铁试验,研究反射光谱特征及植被指数与叶绿素密度的相关性。结果显示:喷施氮肥(尿素6 g/m2)或氮肥+铁(尿素6 g/m2+0.6 L/m2EDTA-Fe)能降低草坪在可见光区光谱反射率,提高叶绿素密度,改善草坪色泽;草坪叶绿素密度与可见光波段反射率呈负相关,其中绿波段反射率R(530.94 nm)与叶绿素密度呈极显著相关;由绿波段及蓝绿波段组合的植被指数与草坪叶绿素密度呈显著相关;逐步回归分析结果显示,应用由DVI(530.94 nm,500.12 nm)和NDVI(561.64 nm,520.53 nm)构建的回归方程能够快速定量估测草坪色泽,其结果与目测评分值相关极显著;利用高光谱植被指数可以准确估测叶绿素密度,并对草坪色泽进行定量评价。

Color is a key component of the aesthetic quality of turf and often evaluated in field studies. Hyperspectral indices could be used to measure turf canopy chlorophyll density and evaluate turf color based on the correlation between vegetation index values and visual ratings. The correlativity between hyperspectral characteristics,vegetation index and chlorophyll density of tall fescue （Festuca arundinacea Schreb. cv. Watchdog）, kentucky bluegrass （Poa pratensis L. cv. Liberator）, bermudagrass （Cynodon dactylon （L.） Pars. cv. Common） and creeping bentgrass （Agrostis stolonifera L. cv. Putter） under leaf surface spraying nitrogen and Fe fertilizers were studied during the growing season in 2007. The results show that nitrogen （urea 6g·m^-2） or nitrogen ＋ Fe （urea 6g - m^-2＋ EDTA-Fe 0. 6 L · m^-2） significantly in- creased chlorophyll density,decreased spectral reflectance in visible wavebands, and improved the color of turfgrass. There was a negative correlation between turf chlorophyll density and the reflectance in visible waveband with an extreme-significance at green band （530.94 nm） and an significant correlation between turf chlorophyll density and vegetation index derived from green and blue band. A significant relationship was established between vegetation indices of DVI （530. 94 nm, 500. 12 nm） and NDVI （561. 64 nm, 520.53 nm） and turf chlorophyll density and a strong agreement existed between hyperspectral vegetation indices and visual ratings. This evaluation technique may facilitate objective and quantitative assessments of turf color across researchers,locations and years when hyperspectral reflectance are measured and collected under equal conditions.