The thesis by Jadunandan Dash, titled "The MERIS Terrestrial Chlorophyll Index," focuses on the design, evaluation, and application of a new index called the MERIS Terrestrial Chlorophyll Index (MTCI) for estimating chlorophyll content in vegetation canopies using spectral data from the Medium Resolution Imaging Spectrometer (MERIS). The MTCI is designed to address the limitations of existing techniques, which are often tailored for small volumes of continuous spectral data and produce inconsistent results. The MTCI uses data from three red and near-infrared bands (681.25 nm, 708.75 nm, and 753.75 nm) to locate the red edge, a feature in the reflectance spectrum that moves to longer wavelengths as chlorophyll content increases. The thesis includes a literature review on spectral properties of vegetation, the role of chlorophyll, and various methods for estimating the red edge position (REP). It evaluates the MTCI using model, field, and MERIS data, demonstrating its sensitivity to chlorophyll content, especially at high levels, and its insensitivity to spatial resolution and atmospheric effects. The MTCI is validated through comparisons with other vegetation indices and is implemented as an ESA level-2 product. The MTCI is applied to infer salt stress in coastal and near-coastal vegetation affected by the 2004 Indian Ocean tsunami, monitor the condition of forests contaminated by herbicides in southern Vietnam, and map land cover in Wisconsin, USA. Future work is suggested to further understand the MTCI, validate it with ground data, and explore its applications at regional to global scales.The thesis by Jadunandan Dash, titled "The MERIS Terrestrial Chlorophyll Index," focuses on the design, evaluation, and application of a new index called the MERIS Terrestrial Chlorophyll Index (MTCI) for estimating chlorophyll content in vegetation canopies using spectral data from the Medium Resolution Imaging Spectrometer (MERIS). The MTCI is designed to address the limitations of existing techniques, which are often tailored for small volumes of continuous spectral data and produce inconsistent results. The MTCI uses data from three red and near-infrared bands (681.25 nm, 708.75 nm, and 753.75 nm) to locate the red edge, a feature in the reflectance spectrum that moves to longer wavelengths as chlorophyll content increases. The thesis includes a literature review on spectral properties of vegetation, the role of chlorophyll, and various methods for estimating the red edge position (REP). It evaluates the MTCI using model, field, and MERIS data, demonstrating its sensitivity to chlorophyll content, especially at high levels, and its insensitivity to spatial resolution and atmospheric effects. The MTCI is validated through comparisons with other vegetation indices and is implemented as an ESA level-2 product. The MTCI is applied to infer salt stress in coastal and near-coastal vegetation affected by the 2004 Indian Ocean tsunami, monitor the condition of forests contaminated by herbicides in southern Vietnam, and map land cover in Wisconsin, USA. Future work is suggested to further understand the MTCI, validate it with ground data, and explore its applications at regional to global scales.