Soil property maps are essential resources for agricultural land use. However, soil properties mapping is costly and time-consuming, especially in the regions with complicated topographic conditions. This study was conducted in a hilly region of Central Vietnam with the following objectives: (i) to evaluate the best environmental variables to estimate soil organic carbon (SOC), total nitrogen (TN), and soil reaction (pH) with a regression kriging (RK) model, and (ii) to compare the accuracy of the ordinary kriging (OK) and RK methods. SOC, TN, and soil pH data were measured at 155 locations within the research area with a sampling grid of 2 km × 2 km for a soil layer from 0 to 30 cm depth. From these samples, 117 were used for interpolation, and the 38 randomly remaining samples were used for evaluating accuracy. The chosen environmental variables are land use type (LUT), topographic wetness index (TWI), and transformed soil adjusted vegetation index (TSAVI). The results indicate that the LUT variable is more effective than TWI and TSAVI for determining TN and pH when using the RK method, with a variance of 7.00% and 18.40%, respectively. In contrast, a combination of the LUT and TWI variables is the best for SOC mapping with the RK method, with a variance of 14.98%. The OK method seemed more accurate than the RK method for SOC mapping by 3.33% and for TN mapping by 10% but the RK method was found more precise than the OK method for soil pH mapping by 1.81%. Further selection of auxiliary variables and higher sampling density should be considered to improve the accuracy of the RK method.

Soil erosion is a considerable concern in the upland areas of Central Vietnam. This situation is most serious in regions, where the terrain is sloped and subjected to heavy rainfall. Our research was conducted in a mountainous area, belonging to Central Vietnam, the area of Song Kon commune in the Dong Giang district. The objective of this study is first to estimate the impact of soil erosion risk in these areas, and second to assess the capacity of farming systems which are based on indigenous knowledge (IK) to respond to soil erosion. Our data were collected by Participatory Rural Appraisal (PRA) and processed using Geographical Information System (GIS) methods. We then interpreted this research using the Universal Soil Loss Equation (USLE) in order to calculate the soil erosion rate. The Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) were also used as measurements to compare the difference of land surface covers between different farming systems. The results showed that the lowest soil erosion rate was found in the narrow valley regions, which are populated by both agricultural and residential areas. On the other hand, soil erosion was extremely high in the more northerly quadrant of our research area. Our findings also indicate that local farmers are highly aware of soil erosion, which has positively influenced the adoption of adaptation measures (AMs) in their agricultural activities. The most common AMs are as follows: changes in cropping patterns, the adjustments of their planting calendars, the use of native varieties, and intercropping methods. These AMs are mediated by the cultural observances of the local ethnic minority peoples in relation to their IK. We have concluded that when farmers apply IK in their farming systems, the soil erosion rate tends to decrease as compared with non-indigenous knowledge (NIK) practices. We hope to bring a better understanding of the processes that shape farmers’ AMs and thereby to develop well-targeted adaptation policies that can then be applied at the local level. Our findings may be instrumental in future adaptation planning and policies in regard to climate change, and that they will help to increase awareness not only in matters of the soil erosion but also in other interconnected aspects of climate change in these areas.

The vulnerability assessment of small-scale households on the central coast of Vietnam has been inadequate despite the apparent impacts of climate change. This knowledge gap presents challenges for identifying at-risk individuals and communities and could impede effective public policy and resource allocation for adaptation efforts. To address this issue, this study employed the Livelihood Vulnerability Index referencing IPCC definitions (LVI-IPCC) framework to examine livelihood vulnerability and its determinants among 455 small-scale households in the coastal areas of Phu Vang district, Thua Thien Hue province, Vietnam. The LVI-IPCC calculation utilized a database of 11 major and 33 sub-indicators collected through a household survey conducted in 2021. The findings revealed that these households exhibit moderate vulnerability to natural disasters and climate shocks, as reflected by their high sensitivity index scores. Additionally, the study identified a persistent cycle of poverty and livelihood vulnerability among coastal communities, wherein poverty and reliance on nature-based income serve as the root cause of the exposure and a gateway to this loop. This study strongly advocates for a pro-poor approach that places poverty alleviation at the forefront of community development planning and climate change agendas. Under this approach, developing value chain models in agriculture and aquaculture and diversifying livelihoods through activities such as community-based tourism is highly recommended.

In recent years, there has been growing awareness about the roles and benefits of urban green spaces (UGSs), particularly in the context of mitigating the negative effects of climate change, which have become increasingly serious. In Vietnam, the government has allocated considerable resources to the development of UGSs in many cities. However, regarding implementation, UGS development in Vietnam faces many challenges; many cities find it difficult to meet the set criterion regarding the number of green spaces per capita. This research was conducted in Hue City, which is known as one of the greenest cities in Vietnam. The results show that there are twenty-one UGSs in Hue City (with a total area of 88.67 ha). These are located primarily along the Huong River and around the Hue Imperial Citadel. However, under government stipulations, the current number of UGSs is not considered sufficient in proportion to the local population, and will not accommodate the future growth of the population. We applied the analytic hierarchy process (AHP) along with the participation of local residents, using six criteria to map potential areas for future UGS planning. In this, the distance from existing residential areas to potential UGS locations is the most important criterion. The suitability map identified 684 hectares of Hue City as highly suitable for UGSs. This research also proposes a scenario for UGS planning in Hue based on retaining the existing green spaces combined with creating another 35 green spaces, comprising a total area of 167 hectares. This is to meet the needs of local residents by 2030.