Although urban areas occupy less than 1% of the world’s land surface, they contribute over 90% of the global economy. By 2014, already 50% of the world’s population was living in urban areas, and this figure is increasing (United Nations, 2015). Urban impervious surfaces, such as buildings, parking lots and transportation networks, have been widely recognized as an important indicator of urban expansion and its related environmental and ecological issues. Particularly, the Guangdong-Hong Kong-Macau Greater Bay Area (GBA) has undergone a very strong urbanization process. In the long run, a comprehensive assessment of urban land dynamics will be vital and urgent in the assessment and management of these effects. However, GBA is located in a subtropical climate zone characterized by rainy and cloudy weather throughout the year, and thus requires multiple remote sensing technologies to overcome weather-related difficulties. We aimed to develop a multi-level framework of integrating optical and radar data for monitoring urban land dynamics with spaceborne, airborne and ground observations. The methodological framework consists of various modules of processing, analyzing and integrating the optical and radar data at data (pixel) level, feature level and decision level.
Regarding the ecological impacts of urbanization, we are looking at the mangrove forests. Mangrove forests are ecosystems along tropical and subtropical coastlines, estuaries, lagoons and rivers, with considerable ecological, biological and socioeconomic significance as: 1) vital habitats for a wide variety of animal and plants species, 2) important sources of carbon for detritus-based food webs in adjacent coastal waters, 3) a means of reducing the erosion of shorelines, and 4) buffers against the impact of storm waves and floods. However, mangrove forests have been significantly eroded over the past century due to various human activities such as agriculture conversion, urbanization and tourism. Hong Kong benefits from a number of mangrove forests which continue to play important ecological and socioeconomic roles to local communities. Unfortunately, mangrove forests cover has rapidly decreased in the past few decades due to increasing agricultural exploitation and infrastructural development such as new highways and airport as well as associated construction. We aimed to investigate the spatial and temporal changes in area and above/below ground biomass at the species level, with the assist of our methodological framework of incorporating optical and radar data to overcome the difficulties brought by rainy and cloudy weather in tropical and subtropical areas.
With these motivations, several questions have been guiding our research: