STRATEGIC SPATIAL PLANNING FOR ENHANCING THE ECONOMIC SUSTAINABILITY OF THE TOURISM SECTOR IN GOA, INDIA

Abstract

Tourism in Goa is concentrated along the coastal belt, generating congestion, environmental stress, and uneven spatial development. This study develops a spatial decision-support framework to identify areas where tourism pressure should be contained and areas where diversification is more feasible. The analysis uses a 1 × 1 km grid across Goa and integrates tourism amenity indicators, environmental conditions, accessibility measures, and regulatory constraints. OpenStreetMap-based tourism and service proxies, Earth observation variables, transport accessibility metrics, and governance overlays are combined to derive three decision dimensions: tourism opportunity, environmental stress, and access. Machine -learning models are used to predict a tourism-opportunity surface, referred to as the Benefit Index, and tourism presence, and these dimensions are then translated into scenario-based development classes for decongestion, diversification, cautious development, and constraint. The results indicate that tourism opportunity is highly concentrated along the coastal belt, where high benefit often coincides with elevated environmental stress and tighter regulatory constraints. In contrast, selected inl and areas exhibit moderate opportunity, lower environmental pressure, and adequate access. Scenario testing also indicates that an environment-first approach strengthens the case for directing marginal tourism growth inland rather than intensifying development in already stressed coastal zones. Overall, the results suggest that spatial targeting, rather than uniform expansion, offers a more robust basis for zoning, project appraisal, and phased tourism investment in Goa.