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Comparing and Combining Landsat Satellite Imagery and Participatory Data to Assess Land-Use and Land-Cover Changes in a Coastal Village in Papua New Guinea

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Abstract

In regions lacking socio-economic data, pairing satellite imagery with participatory information is essential for accurate land-use/cover (LULC) change assessments. At the village scale in Papua New Guinea we compare swidden LULC classifications using remote sensing analyses alone and analyses that combine participatory information and remotely sensed data. These participatory remote sensing (PRS) methods include participatory land-use mapping, household surveys, and validation of image analysis in combination with remotely sensed data. The classifications of the swidden area made using only remote sensing analysis show swidden areas are, on average, two and a half times larger than land managers reported for 1999 and 2011. Classifications made using only remote sensing analysis are homogeneous and lack discrimination among swidden plots, fallow land, and non-swidden vegetation. The information derived from PRS methods allows us to amend the remote sensing analysis and as a result swidden areas are more similar to actual swidden area found when ground-truthing. We conclude that PRS methods are needed to understand swidden system LULC complexities.

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Acknowledgements

We would like express gratitude to contributors from the Bishop Museum, Honolulu, HI. A special thanks to the village community members for their knowledge, involvement, and assistance in all aspects of this project. Last, this material is based upon work supported by the National Science Foundation under Grant No. DEB-0950207. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Authors and Affiliations

  1. Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA

    Jamie D. Hoover

  2. Department of Anthropology, Colorado State University, Fort Collins, CO, USA

    Stephen J. Leisz

  3. Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO, USA

    Melinda E. Laituri

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  1. Jamie D. Hoover
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  2. Stephen J. Leisz
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Correspondence to Jamie D. Hoover.

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This study was funded by the National Science Foundation under (Grant No. DEB-0950207).

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Hoover, J.D., Leisz, S.J. & Laituri, M.E. Comparing and Combining Landsat Satellite Imagery and Participatory Data to Assess Land-Use and Land-Cover Changes in a Coastal Village in Papua New Guinea. Hum Ecol 45, 251–264 (2017). https://doi.org/10.1007/s10745-016-9878-x

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