Understanding the Spatial Distribution of Ecotourism in Indonesia and Its Relevance to the Protected Landscape

Saraswati Sisriany and Katsunori Furuya ()
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Saraswati Sisriany: Graduate School of Horticulture, Chiba University, Chiba 271-8510, Japan
Katsunori Furuya: Graduate School of Horticulture, Chiba University, Chiba 271-8510, Japan

Land, 2024, vol. 13, issue 3, 1-23

Abstract: Ecotourism, a dynamic force in global tourism, holds promise for conserving the environment while ensuring benefits for local economies. In this study, we developed an ecotourism distribution map of Indonesia. We utilized location-based social networks (LSBNs) data derived from Google Maps API to map 172 ecotourism sites in Indonesia. Furthermore, we investigated the distribution patterns of ecotourism within Indonesia’s protected landscapes and ecoregions. The factors that influenced ecotourism distribution in the region were analyzed using the MaxEnt model (because of its application for presence-only data). The key findings revealed that ecotourism sites are predominantly distributed across national parks and protected forest areas, and generally consist of mountainous and hilly terrain according to the ecoregion types. The MaxEnt model results indicated that population density was the most influential factor in ecotourism distribution. The significance of our study lies in its methodologies and results, which offered novel approaches to nationwide mapping and addressed the lack of an ecotourism site map of Indonesia. Notably, the proposed model can be customized for other regions with limited ecotourism data; thus, our study can serve as a foundation for future interdisciplinary studies on ecotourism, sustainability, and landscape planning.

Keywords: ecotourism; Indonesia; spatial distribution; protected landscapes; geospatial analysis; MaxEnt model; Google Maps; spatial mapping; location-based social networks (LSBNs) (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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