Earth Observation time-series data are valuable information to monitor the change of the environment. But access to data and the execution of analysis tools are often time-consuming tasks and data processing knowledge is required. In order to allow user-friendly applications to be built, tools are needed to simplify the access to data archives and the analysis of such time-series data. In this work, web services for accessing and analyzing MODIS, Landsat, and Sentinel time-series data have been developed based on the Web Processing Service specification of the Open Geospatial Consortium and made available within the Earth Observation Monitor framework. The Python library "pyEOM" has been developed to combine access and analysis tools for Earth Observation time-series data. Algorithms developed to analyze vegetation changes are provided as web-based processing services in connection to the prior developed access services as well. Using the services developed, users only need to provide the geometry and the name of the dataset the user is interested in; any processing is done by the web service. The services and applications (web and mobile) are based on geospatial open source software.