Abstract
The growing recognition of the importance of ecosystem services of urban forests requires sustainable management of urban forests, which requires timely and accurate information on the status, trends and interactions between socio-economic and environmental processes related to urban forests. The world is experiencing accelerated urbanization and the growth of cities that have radically changed the urban landscape, collectively all forests and trees within the urban boundary are defined as urban forest. In this regard, remote sensing, especially with its recent advances in sensors and data processing techniques, has become a major and useful tool for observation and analysis. This study summarizes recent applications of remote sensing in urban forestry in terms of three distinctive themes: multi-source, multi-temporal, and multi-scale source data. It examines how various remote sensing data sources provide a fast, reproducible and scalable way to quantify the dynamics of urban forests at different spatial and temporal scales in each case. Combined optical images and LiDAR data are the most promising among the input data from multiple sources; in addition, future efforts should be focused on improving data processing efficiency.