This thesis presents the design, evaluation, and application of the MERIS Terrestrial Chlorophyll Index (MTCI), a new index for estimating chlorophyll content in vegetation canopies using data from the Medium Resolution Imaging Spectrometer (MERIS). The MTCI uses data from three red and near-infrared (NIR) wavebands (681.25 nm, 708.75 nm, and 753.75 nm) to locate the red edge position, which is sensitive to chlorophyll content. The MTCI is easy to calculate and can be automated, and preliminary evaluations suggest it is sensitive to chlorophyll content, particularly at high levels, and relatively insensitive to spatial resolution and atmospheric effects. It is now an ESA level-2 product. The MTCI was evaluated using two data sets: one from controlled greenhouse experiments with spinach and poplar, and another from field data for crops in southern Spain. The results suggest a stronger MTCI-chlorophyll content relationship than the red edge position (REP)-chlorophyll content relationship. However, due to a lack of spatial and temporal chlorophyll content data at MERIS resolution, the MTCI could not be validated with ground data. Comparisons with other vegetation indices from space-borne sensors suggest that MTCI is more sensitive to changes in canopy chlorophyll content. The MTCI was successfully used to (i) infer salt stress in coastal vegetation affected by the 2004 Indian Ocean Tsunami, (ii) monitor the condition of southern Vietnamese forests contaminated by herbicides in the 1960s and 1970s, and (iii) map land cover in Wisconsin, USA. Future work should focus on regional to global applications of the MTCI and validation with real ground data at MERIS resolution. The thesis also reviews the literature on red edge estimation techniques, spectral properties of vegetation, and the role of chlorophyll in determining plant physiological status. It discusses the performance of the MTCI under varying conditions, including soil background reflectance, viewing geometry, and atmospheric effects. The MTCI was evaluated for a wide range of chlorophyll content data from greenhouse experiments and for the first time, the effect of changing levels of irradiance on leaf reflectance spectra was reported. The MTCI was also compared with other vegetation indices from space-borne spectrometers, including the MERIS Global Vegetation Index (MGVI) and Enhanced Vegetation Index (EVI). The MTCI was shown to be a useful tool for land cover classification and for monitoring vegetation conditions in affected areas. The thesis concludes with a summary of the research and suggestions for future work on the MTCI.This thesis presents the design, evaluation, and application of the MERIS Terrestrial Chlorophyll Index (MTCI), a new index for estimating chlorophyll content in vegetation canopies using data from the Medium Resolution Imaging Spectrometer (MERIS). The MTCI uses data from three red and near-infrared (NIR) wavebands (681.25 nm, 708.75 nm, and 753.75 nm) to locate the red edge position, which is sensitive to chlorophyll content. The MTCI is easy to calculate and can be automated, and preliminary evaluations suggest it is sensitive to chlorophyll content, particularly at high levels, and relatively insensitive to spatial resolution and atmospheric effects. It is now an ESA level-2 product. The MTCI was evaluated using two data sets: one from controlled greenhouse experiments with spinach and poplar, and another from field data for crops in southern Spain. The results suggest a stronger MTCI-chlorophyll content relationship than the red edge position (REP)-chlorophyll content relationship. However, due to a lack of spatial and temporal chlorophyll content data at MERIS resolution, the MTCI could not be validated with ground data. Comparisons with other vegetation indices from space-borne sensors suggest that MTCI is more sensitive to changes in canopy chlorophyll content. The MTCI was successfully used to (i) infer salt stress in coastal vegetation affected by the 2004 Indian Ocean Tsunami, (ii) monitor the condition of southern Vietnamese forests contaminated by herbicides in the 1960s and 1970s, and (iii) map land cover in Wisconsin, USA. Future work should focus on regional to global applications of the MTCI and validation with real ground data at MERIS resolution. The thesis also reviews the literature on red edge estimation techniques, spectral properties of vegetation, and the role of chlorophyll in determining plant physiological status. It discusses the performance of the MTCI under varying conditions, including soil background reflectance, viewing geometry, and atmospheric effects. The MTCI was evaluated for a wide range of chlorophyll content data from greenhouse experiments and for the first time, the effect of changing levels of irradiance on leaf reflectance spectra was reported. The MTCI was also compared with other vegetation indices from space-borne spectrometers, including the MERIS Global Vegetation Index (MGVI) and Enhanced Vegetation Index (EVI). The MTCI was shown to be a useful tool for land cover classification and for monitoring vegetation conditions in affected areas. The thesis concludes with a summary of the research and suggestions for future work on the MTCI.