The aim of this study is to identify the key factors contributing to student dropout and to develop a predictive model that estimates the dropout risk of students based on their entry characteristics and enrolment registration data. Our analysis is based on the registration and academic data of 971 full-time and part-time bachelor’s students in five faculties, who were enrolled in the academic year 2021–2022 at the Latvia University of Life Sciences and Technologies (LBTU). The dropout analysis was done during the 3.5 years of study, when the students started their last semester in engineering and information technology, agriculture and food technology, economics and social sciences, and forest and environmental studies and when veterinary medicine students had completed more than half of their program of study. Survival analysis methods were used during the study. Students’ dropout risk in relation to gender, faculty, priority to study in the program, and secondary school performance (SM) was estimated using the Proportional hazard model (Cox model). The highest student dropout was observed during the first year of study. Secondary school performance was a significant predictor of students’ dropout risk; students with higher SM had a lower dropout risk (HR = 0.66, p < 0.05). As well, student dropout can be explained by faculty or study programme. Students in economics and social sciences were at lower dropout risk than the students from the other faculties. Results show the model’s concordance index was 0.59, and this indicates that additional or stronger predictors may be needed to improve model performance.

For effective management of natural capital, it is necessary to identify all ecosystems provisioning services (supply of food, wood, etc.), evaluating each of them. The article presents ecosystem provisioning services automated valuation process model. As data sources are proposed to use information from the European Union member states institution's data registers, integrating it using classical data base, XML schema definition and geographic information systems technologies. The proposed model provides industry professionals with the opportunity for online decision making, that is based on actual data, and as well fuzzy logic based assessment method for sustainable land management. The article defines the data sources that are available for modeling and describes the specific problems with data integrating. As a result of the study information system architecture for ecosystem provisioning services valuation for land management is developed.