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Mapping Regional Landscape by Using OpenstreetMap (OSM): A Case Study to Understand Forest Patterns in Maya Zone, Mexico

Mapping Regional Landscape by Using OpenstreetMap (OSM): A Case Study to Understand Forest Patterns in Maya Zone, Mexico

Di Yang
Copyright: © 2017 |Pages: 20
ISBN13: 9781522524465|ISBN10: 1522524460|EISBN13: 9781522524472
DOI: 10.4018/978-1-5225-2446-5.ch008
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MLA

Yang, Di. "Mapping Regional Landscape by Using OpenstreetMap (OSM): A Case Study to Understand Forest Patterns in Maya Zone, Mexico." Volunteered Geographic Information and the Future of Geospatial Data, edited by Cláudio Elízio Calazans Campelo, et al., IGI Global, 2017, pp. 138-157. https://doi.org/10.4018/978-1-5225-2446-5.ch008

APA

Yang, D. (2017). Mapping Regional Landscape by Using OpenstreetMap (OSM): A Case Study to Understand Forest Patterns in Maya Zone, Mexico. In C. Calazans Campelo, M. Bertolotto, & P. Corcoran (Eds.), Volunteered Geographic Information and the Future of Geospatial Data (pp. 138-157). IGI Global. https://doi.org/10.4018/978-1-5225-2446-5.ch008

Chicago

Yang, Di. "Mapping Regional Landscape by Using OpenstreetMap (OSM): A Case Study to Understand Forest Patterns in Maya Zone, Mexico." In Volunteered Geographic Information and the Future of Geospatial Data, edited by Cláudio Elízio Calazans Campelo, Michela Bertolotto, and Padraig Corcoran, 138-157. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-2446-5.ch008

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Abstract

A forest patterns map over a large extent at high spatial resolution is a heavily computation task but is critical to most regions. There are two major difficulties in generating the classification maps at regional scale: large training points sets and expensive computation cost in classifier modelling. As one of the most well-known Volunteered Geographic Information (VGI) initiatives, OpenstreetMap contributes not only on road network distributions, but the potential of justify land cover and land use. Google Earth Engine is a platform designed for cloud-based mapping with a strong computing power. In this study, we proposed a new approach to generating forest cover map and quantifying road-caused forest fragmentations by using OpenstreetMap in conjunction with remote sensing dataset stored in Google Earth Engine. Additionally, the landscape metrics produced after incorporating OpenStreetMap (OSM) with the forest spatial pattern layers from our output indicated significant levels of forest fragmentation in Yucatan peninsula.

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