Classifying and evaluating the structure of tropical forest plant biomes based on up-to-date remote sensing data, remains a great challenge due to the species diversity, changes in the stages of seasonal growth. Remote sensing has long been a useful tool for classification and assessment of vegetation. For data from unmanned aerial vehicles (UAVs), the ability to receive high-resolution data also partly solves this problem. The development of vegetation based on natural conditions includes: topographic, geomorphology, geologic conditions, climate, human impacts. Based on the red-green-blue colour model (RGB) obtained from UAV, analysis of VARI (visible atmospherically resistant Index) and TGI (triangulation greenness index), combined with the development characteristics of each group and type of biomes on different topography and geologic types, the researchers were able to give some characteristics of some tropical forest vegetation in Ngoc Linh Nature Reserve, Kon Tum province, Vietnam.

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Mangroves play an important role in coastal estuarine areas with different ecological functions, such as reducing the impact of waves and currents, accumulating biomass and sequestering carbon. However, estimation of terrestrial biomass in mangrove areas, especially in Vietnam, has not been fully studied. The application of unmanned aerial vehicles (UAV), mounted with multispectral cameras combined with field verification is an effective method for estimating terrestrial biomass for mangroves, as it reduces field survey time and allows for greater spatial range research. In this study, ground biomass was estimated for the mangrove area in the Dong Rui commune, based on multispectral image data obtained from UAV and survey results in 16 standard cells measuring actual biomass according to four regression models: Log-Log, Log-Lin, Lin-Log and Lin-Lin. The results of comparing the data from these four models show that the log-log model has the highest accuracy with a high correlation coefficient (R2 = 0.831). Based on the results of the analysis and selection of ground-based biomass estimation models, a biomass map was established for the UAV flying area in the Dong Rui mangrove forest with biomass values ranging from 20 Mg/ha to 150 Mg/ha. In summary, we present a biomass estimation method through four basic linear regression models for mangrove areas, based on multispectral image data obtained from ultrahigh-resolution UAV. The resulting research results can serve as a basis for managers to calculate and synchronise the payment of carbon services, thus contributing to effectively promoting the livelihoods of local people.