Ecotourism spatio-temporal models to identify visitation patterns across the Indian Himalayan Region
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Ecotourism spatio-temporal models to identify visitation patterns across the Indian Himalayan Region Priya Bhalla
. Prodyut Bhattacharya . Gopala Areendran . Krishna Raj
Accepted: 8 November 2020 Ó Springer Nature B.V. 2020
Abstract Visitation patterns across protected areas of Uttarakhand, India reflect a unique amalgamation of natural, cultural and religious aspects of vulnerable mountain tourism destinations. These aspects act as predictors in determining visitation rates and identifying destination specific tourism models. Using the mixed methods approach based on field surveys, geotagged photographs and InVEST recreation tool, this study (1) maps the spatio-temporal movement of visitors across ten sampled protected areas of Uttarakhand (2) identifies predictor variables contributing to visitation across Binsar Wildlife Sanctuary (BWLS) of Uttarakhand (3) explores the visitors’ decision to recreate at specific
P. Bhalla (&) University School of Environment Management, Guru Gobind Singh Indraprastha, University, A block, Room ATL-404, Sector 16-C Dwarka, Delhi 110078, India e-mail: [email protected] P. Bhattacharya University School of Environment Management, Guru Gobind Singh Indraprastha University, A block, Room A-101, Sector 16-C Dwarka, Delhi 110078, India e-mail: [email protected] G. Areendran K. Raj Indra Gandhi Conservation and Monitoring Centre, ENVIS and IT, WWF-India, 172 B, Lodhi Estate, New Delhi 110003, India e-mail: [email protected] K. Raj e-mail: [email protected]
locations across BWLS based on four tourism models and (4) determines the prevalent tourism model across BWLS. The visitation pattern assessment suggest Rajaji National Park as the most visited protected area in Uttarakhand, but the highest density of photographed location existed within the Corbett National Park. That, visitation to National Park outnumbers visitation to wildlife sanctuaries in Uttarakhand and preferably over the months of March–April (Spring) and October– November (Winter). Binomial logistic regression analysis on Flickr generated photographs reveals community-based ecotourism as the prevalent tourism model across Binsar. Human settlements and natural water springs of the sanctuary were key predictors affecting visitation in Binsar. The grounded nature of this research presents the ecotourism interacting variables addressing spatial movement of visitors across protected areas of critical importance, to manage tourism destinations sustainably. Keywords Ecotourism Geotagged photographs Indian Himalayan region Protected areas Visitation drivers
Introduction Protected areas’ (PAs) natural characteristics with least human modification have stimulated ecotourism
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focus (Newsome et al. 2013). While generating an inevitable development-conservation argument (Bookbinder et al. 1998; Ghosh and Ghosh 2019), ecotourism is yet growing unprecedentedly. With ever increasing human attraction and visitation to natural areas, Ch
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