DEVELOPMENT OF SPATIAL INFORMATION MODELS OF TERRITORIAL DEVELOPMENT TAKING INTO ACCOUNT ENVIRONMENTAL FACTORS (ON THE EXAMPLE OF THE REPUBLIC OF KARAKALPAKSTAN AND THE ARAL REGION)

Abstract

This study investigates the theoretical and practical aspects of developing and enhancing spatial information models
for sustainable regional development with consideration of environmental factors, using the Republic of Karakalpakstan and the Aral
Sea region as a case study. The relevance of the research is determined by the growing environmental challenges associated with the
desiccation of the Aral Sea, land degradation, water scarcity, climate change, and the increasing pressure on natural ecosystems. These
challenges necessitate the implementation of advanced digital technologies and intelligent decision-support mechanisms to ensure
environmentally balanced and sustainable territorial development.
Drawing upon contemporary scientific literature in the fields of geoinformation systems, environmental monitoring, sustainable
development, and digital transformation, the study proposes an integrated spatial information model that combines Geographic
Information Systems (GIS), the Internet of Things (IoT), Artificial Intelligence (AI), earth observation and remote sensing technologies,
big data analytics, and intelligent decision-support systems. The proposed framework enables the integration of heterogeneous
environmental, socio-economic, and spatial datasets into a unified analytical environment for the comprehensive assessment and
management of regional development processes.
The research methodology encompasses several interconnected stages, including environmental data acquisition, geospatial
data integration, analytical processing, spatial modeling, predictive analysis using machine-learning algorithms, and interactive
communication between users and the decision-support system. Particular attention is given to the application of intelligent forecasting
techniques for assessing environmental risks, monitoring land-use changes, evaluating water resource conditions, and identifying
environmentally sensitive zones.
The findings demonstrate that the integrated use of advanced geospatial and digital technologies significantly improves the
effectiveness of environmental monitoring, natural hazard forecasting, water resource management, and regional sustainability
assessment. The proposed model enhances the accuracy and timeliness of environmental decision-making, supports evidence-based
territorial planning, and contributes to the development of adaptive strategies for mitigating ecological risks. Furthermore, the model
provides a scientific basis for strengthening sustainable development policies in environmentally sensitive regions, particularly in the
Aral Sea basin and other arid territories facing similar ecological challenges.