Remote Sensing of Tall Grasslands: Estimating Vegetation Biochemical Contents at Multiple Spatial Scales and Investigating Vegetation Temporal Response to Climate Conditions.

详细信息   

• 作者：Wong ; Kelly Ka Lei.
• 学历：Master
• 年：2013
• 毕业院校：University of Toronto
• ISBN：9780499221766
• CBH：MS22176
• Country：Canada
• 语种：English
• FileSize：4689998
• Pages：79

文摘

This thesis estimated vegetation biochemical properties at multiple spatial scales and investigate vegetation temporal dynamics under climate influences in a heterogeneous tallgrass ecosystem in Southern Ontario using remote sensing data. Ground hyperspectral and space multispectral remote sensing data derived Normalized Difference Vegetation Index (NDVI) and Simple Ratio (SR) were used to estimate biochemical properties at the species,canopy and landscape level. Both vegetation indices explained 32% to 56% of the variations in biochemical properties at the species level,16% to 53% at the canopy level,and over 60% at the landscape level. MODIS NDVI and climate data were also collected to investigate the vegetation-climate relationships during the growing season and the lag effects of climate factors on vegetation at the peak growing season. The findings indicate that temperature is the key climate factor that drives the annual cycle,and there is a time lag effect of climate factors on vegetation.