Recommendations to guide sampling effort for polygon-based participatory mapping used to identify perceived ecosystem services hotspots.
Recommendations to guide sampling effort for polygon-based participatory mapping used to identify perceived ecosystem services hotspots.
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DOI:
10.1016/j.mex.2022.101921
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发表时间:
2022
期刊:
影响因子:
1.9
通讯作者:
Quinn, Claire H.
中科院分区:
文献类型:
--
作者:
Carrie, Rachael H.;Stringer, Lindsay C.;Thi Van Hue Le;Nguyen Hong Quang;Hackney, Christopher R.;Van Tan Dao;Thi Thanh Nga Pham;Quinn, Claire H.
关键词:
Prioritises spatial agreement (polygon overlap) rather than polygon count and participant numbers to assess data sufficiency Uses narratives to triangulate outputs generated from participatory mapping data to reduce uncertainty related to low polygon counts Participatory mapping is increasingly used to map spatial variation in people's perceptions about ecosystem services. It has growing use in the identification of locations where places perceived to be important converge. Few recommendations have been published to navigate decisions about sampling effort in participatory mapping research when polygon data is collected, although one recommendation is for ≥ 25 participants assuming each participant maps c. 4–5 polygons per ecosystem service. Underlying data informing this recommendation reflects a particular context: collected using postal questionnaires to map a vast spatial area in southern Australia. Although not intended as definitive or suited to all contexts, the 25 participant (or 100-125 polygon) minimum sometimes informs participatory mapping research. Our empirical work, undertaken using face-to-face questionnaires in a small Vietnamese coastal study area, suggests the recommendation may not be appropriate in all contexts. We propose a modified stepwise approach which: A graphical abstract is mandatory. The graphical abstract should summarize the contents of your article in a concise, pictorial form. Authors must provide images that clearly represent the work described in the article. Graphical abstracts should be submitted as a separate file. Image size: please provide an image with a minimum of 531 × 1328 pixels (h × w) or proportionally more. The image should be readable at a size of 5 × 13 cm using a regular screen resolution of 96 dpi. Preferred file types: TIFF, EPS, PDF or MS Office files.
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