Spatial characterization of non-material values across multiple coastal production landscapes in the Indian Sundarban delta

• Published in: Sustainability science 2022-05, Vol.17 (3), p.725-738
• Main Authors: Dasgupta, Rajarshi, Hashimoto, Shizuka, Basu, Mrittika, Okuro, Toshiya, Johnson, Brian Alan, Kumar, Pankaj, Dhyani, Shalini
• Format: Article
• Language: English
• Subjects: Aquaculture; Climate Change Management and Policy; Cultural heritage; Culture; Earth and Environmental Science; Ecosystems; Education; Empirical analysis; Environment; Environmental Economics; Environmental Management; Laboratories; Land use; Landscape; Landscape Ecology; Mapping; Mud flats; Public Health; Rural areas; Spatial analysis; Spatial data; Special Feature: Original Article; Special Feature: Valuation of Nature and Nature’s Contributions to People; Statistical analysis; Sustainable Development
• ISSN: 1862-4065; 1862-4057
• DOI: 10.1007/s11625-020-00899-3

The paper narrates an empirical study of participatory mapping and spatial characterization of six non-material landscape values across multiple coastal production landscapes in the Indian Sundarban delta. The methodology relies on an inexpensive rapid rural appraisal technique that integrates the conventional notion of place preference and participatory mapping. 168 respondents living in the study area were provided six georeferenced maps with 30 pre-identified landmarks, and were asked to mark and rank at least three preferred locations (with no upper limit) for each of the six non-material landscape values category (i.e. spiritual, recreational, heritage, aesthetic, educational, and negative values). A total of 65 locations, depicting all the six landscape values, were identified from the survey. Corresponding scores against these points were calculated by multiplying the frequency of occurrence and assigned preference weights. We thereafter conducted a series of statistical and spatial analysis to understand the demographic patterns in the observed intangible values and their spatial association with different production landscapes. Regression modeling revealed significant influence of the age and educational profile of the respondents on the number of points marked viz .-a- viz . appreciation for non-material landscape values. Also, the Spearman correlation revealed a strong positive pairwise association between recreational and aesthetic values, spiritual and heritage as well as educational and heritage values. Finally, we computed landscape-wise availability of non-material values using a recent land use map of the delta, and found that agriculture/cultivated areas, rural settlements, and mudflats/beaches were associated with high non-material values, while aquaculture was minimally attributed to non-material landscape values. As such, the study facilitates a comparative understanding of non-material benefits from multiple rural production landscapes/waterscapes, besides providing valuable spatial information for policy-planners and administrative officials.