Environmental changes are becoming an important issue in the global agenda. Typical change understanding ecological studies rely on the use of huge volumes of remote sensing image, demanding the definition of effective and efficient services for appropriate storing, retrieval, and knowledge extraction. This lecture will focus on presenting ongoing research initiatives focused on the specification and implementation of appropriate systems to handle large-scale remote sensing image collections. Special attention will be given to recent research results on image processing, machine learning, and time series analysis in the context of the e-Phenology project. The e-Phenology is a multidisciplinary project that combines research efforts in Computer Science and Phenology. Its objective is to address practical and theoretical problems involved in the use of new technologies to the remote observation of phenology, aiming to detect local environmental changes.