Sago palm (Metroxylon sagu) is a palm tree species originating in Indonesia. In the future, this starch-producing tree will play an important role in food security and biodiversity. Local governments have begun to emphasize the sustainable development of sago palm plantations; therefore, they require near-real-time geospatial information on palm stands. We developed a semi-automated classification scheme for mapping sago palm using machine learning within an object-based image analysis framework with Pleiades-1A imagery. In addition to spectral information, arithmetic, geometric, and textural features were employed to enhance the classification accuracy. Recursive feature elimination was applied to samples to rank the importance of 26 input features. A support vector machine (SVM) was used to perform classifications and resulted in the highest overall accuracy of 85.00% after inclusion of the eight most important features, including three spectral features, three arithmetic features, and two textural features. The SVM classifier showed normal fitting up to the eighth most important feature. According to the McNemar test results, using the top seven to 14 features provided a better classification accuracy. The significance of this research is the revelation of the most important features in recognizing sago palm among other similar tree species.

Solving complex system challenges such as natural resource management in social-ecological systems (SESs) is fraught with great uncertainty. To cope with these challenges, socially vulnerable people in developing countries have created various autonomous innovations. This study focuses on the concept of leverage point (LP) to understand the emergence of innovations and the transformation mechanism of SESs. An LP is a part of a complex system where a small change can cause transformations in the entire system and can be identified from causal networks in an SES. This study analyzed the emergence processes of autonomous innovations as causal networks through transdisciplinary collaboration with innovators in communities and succeeded in visualizing the initial conditions, outcomes, and challenges. We constructed a new definition of LPs based on graph theory and classified LPs into three types based on their characteristics. The network analysis of the causal networks of two innovations in developing countries revealed that the three types of LPs functioned synthetically in complex systems to promote transformation. Based on these results, we propose the potential ways of interventions for the transformation of complex system networks including plural LPs and discuss their effectiveness as boundary objects in transdisciplinary processes collaborating with diverse stakeholders. Further research is expected to accumulate knowledge for solving the various challenges faced by SESs.

The most important issue in food security in Indonesia is limited land area which suitable for food crops. While production already reached its highest potency. Eastern part of Indonesia seems to have hidden answer for the food security issues. Sago plant is origin from Indonesia. Sulawesi is known by its unique semi-cultivated system in food production. This paper will describe the transdisciplinary approach in developing a model of sago plant development based on local community. The model is derived based on the research findings related to characteristic of semi-cultivation of sago plant as follows: (a) Sago in Tana Luwu only 3463,36 ha, most of the land already converted to fishpond, and plantation (b) Semi cultivated sago forest produce 24 tons dry sago/year, 4 times than paddy in dryland, (c) Transdisciplinary research method enables the triple helix collaboration of University, Industry and Government, and (d) Collaborative action is a key to bind the stakeholders, in this case the Plan and Design of Sago Science techno park worked effectively. (e) Several government regulations and local community activities have been born at different level.

Sago palm, one of the dominant wetland vegetation in the Rongkong Watershed, contributes to groundwater recharge through its ability to pass water into the ground. This study aims to determine the effect of sago forest canopy density on the infiltration rate in the middle and downstream zones of the Rongkong Watershed in South Sulawesi. Other independent variables were soil texture, permeability, bulk density, porosity, soil organic matter, initial soil moisture, water level, air temperature, and air humidity. The relationship between the independent variables on the infiltration rate was analyzed using multiple linear regression. Infiltration rate observes with ponded infiltration method at five density classes of sago forest. The results showed that the infiltration rate in the middle stream increased along with the increase of density classes of sago forests. The downstream, on the other hand, has an insignificant difference between density classes. The result of the regression analysis showed that the coefficient of determination in the middle and downstream zones was 64.5 % and 38.5 %, respectively. The simultaneous test of variable significance in the middle stream shows that the sago forest canopy density, groundwater level, initial soil moisture, and air humidity significantly affect a p-value <0.05.

Sago (Metroxylon sagu Rottb.) is a traditional staple food and a strategic bioresource with growing relevance in Southeast Asia’s transition toward a sustainable bioeconomy. This study provides a bibliometric analysis of sago product research published between 2015 and 2025 to examine research growth, key contributors, and evolving thematic trends. The analysis is based on 99 English-language journal articles, conference papers, and reviews indexed in the Scopus database. Bibliometric methods were used to map publication trends, leading institutions, key outlets, and research themes using Microsoft Excel, VOSviewer, and Biblioshiny. This approach is well-suited for sago research because of its interdisciplinary nature, covering food science, agriculture, environmental science, and bioenergy. The results reveal a notable increase in research output after 2019, reaching a peak in 2023, which reflects rising scientific interest in sago-based applications for food technology, bioenergy, biomaterials, and environmental sustainability. The IOP Conference Series: Earth and Environmental Science emerged as the most productive outlet, highlighting the role of conference proceedings in disseminating emerging research. Contributions were predominantly from Southeast Asia, particularly Indonesian institutions, with Malaysia also playing a significant role.Keyword co-occurrence analysis reveals dominant themes, including sago starch, bioenergy, bioplastics, and genetic diversity, indicating a shift from traditional processing studies toward sustainability-oriented innovations. Overall, the findings underscore the increasing scientific recognition of sago’s potential to support sustainable production systems and contribute to the achievement of the Sustainable Development Goals (SDGs).