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We found large spatial variability in individual place attachment and mapped landscape values using both area and distance-based measures.
The spatial distribution of mapped landscape values or values home range is related to, but not identical to mapped place attachment with just over half of landscape values located outside the area of mapped place attachment.
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We demonstrate the use of these values in mapping landscape structure and their potential for monitoring and modelling the effects of disturbance at this scale, including impacts on heterogeneity, connectivity, individual faunal species and particular forest communities.
We argue that survey mapping of landscape values and special places provides a reasonable proxy for scale-based measures of place attachment while providing richer, place-based information for land use planning.
We prepare and present maps of seven landscape values for the entire country of New Zealand to demonstrate the method.
We present a novel method for mapping and modeling landscape values and perceptions that leverages viewshed analysis of georeferenced social media data.
The lived values approach identified that the natural environment, scenery, relaxed lifestyle and safety are highly important to local residents, while the landscape values mapping approach revealed that Kingston Main Beach is the most highly valued of eight coastal landscape units.
We found little to weak spatial association from the two participatory mapping methods on most landscape values.
While some studies explore the things people value about their everyday lives generally the lived values approach, others locate specific social and cultural values in geographic space the landscape values mapping approach.
Incorporating the landscape values mapping into the lived values cluster analysis revealed that while Kingston Main Beach is highly important for its recreational value to some members of the community, for others manmade features such as community halls or sports ovals may be of higher importance because they facilitate social interactions.
The density maps reveal that: (1) landscape values vary over space; (2) aesthetic value was most widespread (not surprising given typical uses of the Instagram platform); (3) town areas, especially the old ones, and popular viewpoints were most likely to be attractors for multiple values.
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