Community-based monitoring has demonstrated potential in the collection and interpretation of forest monitoring data. However effective implementation of community-based forest monitoring systems is currently lacking due to two reasons: 1) the role of communities in national forest monitoring system (NFMS) is unclear and 2) tools that can support local communities to explore opportunities and facilitate forest monitoring are still scarce. The main goal of this thesis, therefore, is to develop an approach that combines emerging technologies and community-based observations for tropical forest monitoring. The overall conclusion is that the emerging technologies, such as smartphones, Web-GIS and social media, incorporated with user friendly interface improve the interactive participation of local communities in forest monitoring and decrease errors in data collection. The results show that CBM can provide data on forest carbon stocks, forest area changes as well as data that help to understand local drivers of emissions. The thesis also shows, in theory and in practice, how local data can be used to link with medium and high resolution remote sensing satellite images for an operational near real-time forest monitoring system at a local scale. The methods presented in this thesis are applicable to a broader geographic scope. Hence, this thesis emphasizes that policies and incentives should be implemented to empower communities and to create institutional frameworks for community-based forest monitoring in the tropics.