Abstract:Mangrove trees form a community of woody plants in intertidal areas periodically immersed by sea water, and are located in tropical and sub-tropical zones. Mangrove forests are complicated ecological systems with characteristics of both land and sea, and form coastal ecologically critical areas (ECA). Monitoring ecological parameters of mangrove ecological systems has gained increased attention from governments and scholars. Ground-based investigation can lead to comprehensive understanding of the structure and functions of the mangrove ecosystem. However, because of spatial and temporal limitations, information on ecological changes of mangrove trees over long periods and large regions cannot be obtained in this way. Advancements in modern remote sensing technology, modeling and simulation, and landscape pattern analysis have provided important technological means for discerning spatiotemporal ecological ecosystem changes. In particular, remote sensing has become an important tool for obtaining temporal and spatial dimensions of ecological parameters of the mangrove forest ecological system. Statistics show that by May 2012, a total of 233 academic papers had been published outside China on remote sensing for monitoring mangrove forests, a number which is increasing yearly. This research mainly focuses on dynamic monitoring, inter-species classification, and structural monitoring of those forests. Especially since 2000, structural monitoring of mangrove communities and investigation of their driving forces and other aspects (sea level changes and comprehensive investigations) have become primary research topics. The application of remote sensing to mangrove forest ecosystem monitoring in China began in the 1990s and has been increasing remarkably in recent years, particularly during the period 2008-2011. This paper summarizes the status of such application and current problems. Specifically, the work expounds on the following aspects: 1) Theories and methods of dynamic monitoring of mangrove-covered wetlands. 2) Theories and methods of inter-species classification technology, as well as requirements of image data. In particular, classification of mangrove trees does not rely only on spectral characteristics, but also requires consideration of structural information that helps enhance classification precision. 3) Theories and methods of remote monitoring of structural parameters of mangrove communities (LAI, crown diameter, tree height and others). In addition, investigations of the relationship between the radar backscattering coefficient and crown diameter and vertical structure of mangrove trees, through establishing a model of their quantitative relationships; this facilitates remote monitoring of mangrove forest growth by applying C-band, L-band, P-band, C-VV and C-HH bands of NASA/JPL. 4) Theories and methods of remote monitoring and inversion of primary production of mangrove forests. Comparative analysis shows that the radar backscattering coefficient is more precise than the NDVI model in estimating vegetation biomass. 5) The status of disasters affecting mangrove forests (diseases, insect infestation and storm surges) and of monitoring theories. 6) Remote dynamic monitoring of and comments on the mangrove-covered region and inter-species landscape patterns. 7) Remote sensing of and comments on driving mechanisms of dynamic evolution of mangrove-covered wetlands. 7) Status and methods of application of remote sensing technology in protection and management of mangrove-covered wetlands. This paper points out existing deficiencies and challenges in remote monitoring of elements of the mangrove forest ecosystem, and emphasizes the need for more research into standardization of classification systems and enhancement of classification precision. Also needed is research into parameters of the ecological characteristics of mangrove forests (diversity and species dominance), spatial evolution of the ecological system, and dimensional effects of remote monitoring. Remote monitoring of the mangrove forest ecosystem lags behind in China, so more such studies should be undertaken in the country.