In the context of climate change, the occurrence of water stress in forest ecosystems, which are solely dependent on precipitation, has exhibited a rising trend, even among species that are typically regarded as drought-tolerant. Remote sensing techniques offer an efficient, comprehensive, and timely approach for monitoring forests at local and regional scales. These techniques also enable the development of diverse indicators of plant water status, which can play a critical role in evaluating forest water stress. This review aims to provide an overview of remote sensing applications for monitoring water stress in forests and reveal the potential of remote sensing and geographic information system applications in monitoring water stress for effective forest resource management. It examines the principles and significance of utilizing remote sensing technologies to detect forest stress caused by water deficit. In addition, by a quantitative assessment of remote sensing applications of studies in refereed publications, the review highlights the overall trends and the value of the widely used approach of utilizing visible and near-infrared reflectance data from satellite imagery, in conjunction with classical vegetation indices. Promising areas for future research include the utilization of more adaptable platforms and higher-resolution spectral data, the development of novel remote sensing indices with enhanced sensitivity to forest water stress, and the implementation of modelling techniques for early detection and prediction of stress.

High revenues from rubber latex exports have led to a rapid expansion of commercial rubber cultivation and, as a consequence, the conversion of different land use types (e.g., natural forests) into rubber plantations, which may lead to a decrease in soil health. In this study in Quang Tri Province, Vietnam, we determined: (1) the variation of soil health parameters along a chronosequence of rubber tree stands and natural forests and (2) the relationships and potential feedback between vegetation types, vegetation structures and soil health. Our results revealed that: (1) soil health was higher in natural forests than in rubber plantations with a higher values in higher biomass forests; (2) soil health was lower in younger rubber plantations; (3) soil health depends on vegetation structure (with significantly positive relationships found between soil health and canopy cover, litter biomass, dry litter cover and ground vegetation cover). This study highlights the need for more rigorous land management practices and land use conversion policies in order to ensure the long-term conservation of soil health in rubber plantations.

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Incursions of Mimosa pigra L., a super-invasive plant, were detected in Hoa Vang district, Da Nang city, Vietnam. This invasive species posed threats to the local agricultural and natural areas, especially to Ba Na - Nui Chua Nature Reserve located in the district. In this study, a habitat model was developed to predict potential areas for the upcoming occurrences of the plant. Detected locations of the species were analyzed in association with seven environmental layers (15 m spatial resolution), which characterized the habitat conditions facilitating the plant incursion, to calculate a multivariate statistic, Mahalanobis distance (D2). Mimosa occurrences were divided into subsets of modelling (for model construction) and validating data (for selecting the best model from replicate runs). The model performance was tested using a null model of 1,000 random points and indicated a significant relationship between D2 values and mimosa occurrence. The D2 model performed markedly better than the random model. The null model in combination with the entire dataset of mimosa locations was also used to identify the threshold D2 value. Using that threshold value, 99.5% of existing mimosa locations were detected and 20.3% of the study area was determined as high-risk areas for mimosa occurrence. These identified high risk areas would make an important contribution to the local alien invasive species management. Given the potential threats to these species from illegal harvesting, that information may serve as an important benchmark for future habitat and population assessments. The spatial modelling techniques in this study can easily be applied to other species and areas.