Remap: An online remote sensing application for land cover classification and monitoring

Murray, Nicholas J., Keith, David A., Simpson, Daniel, Wilshire, John H., and Lucas, Richard M. (2018) Remap: An online remote sensing application for land cover classification and monitoring. Methods in Ecology and Evolution, 9 (9). pp. 2019-2027.

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Recent assessments of progress towards global conservation targets have revealed a paucity of indicators suitable for assessing the changing state of ecosystems. Moreover, land managers and planners are often unable to gain timely access to the maps they need to support their routine decision-making. This deficiency is partly due to a lack of suitable data on ecosystem change, driven mostly by the considerable technical expertise needed to develop ecosystem maps from remote sensing data. We have developed a free and open-access online remote sensing and environmental modelling application, the Remote Ecosystem Monitoring and Assessment Pipeline (Remap;, that enables volunteers, managers and scientists with little or no experience in remote sensing to generate classifications (maps) of land cover and land use change over time. Remap utilizes the geospatial data storage and analysis capacity of Google Earth Engine and requires only spatially resolved training data that define map classes of interest (e.g. ecosystem types). The training data, which can be uploaded or annotated interactively within Remap, are used in a random forest classification of up to 13 publicly available predictor datasets to assign all pixels in a focal region to map classes. Predictor datasets available in Remap represent topographic (e.g. slope, elevation), spectral (archival Landsat image composites) and climatic variables (precipitation, temperature) that are relevant to the distribution of ecosystems and land cover classes. The ability of Remap to develop and export high-quality classified maps in a very short (<10 min) time frame represents a considerable advance towards globally accessible and free application of remote sensing technology. By enabling access to data and simplifying remote sensing classifications, Remap can catalyse the monitoring of land use and change to support environmental conservation, including developing inventories of biodiversity, identifying hotspots of ecosystem diversity, ecosystem-based spatial conservation planning, mapping ecosystem loss at local scales and supporting environmental education initiatives.

Item ID: 60288
Item Type: Article (Research - C1)
ISSN: 2041-210X
Keywords: ecosystem monitoring, Google Earth Engine, image classification, IUCN Red List of Ecosystems, land cover mapping, Landsat Archive, remote sensing, satellite mapping
Copyright Information: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Funders: Google Earth (GE), Australian Research Council (ARC)
Projects and Grants: GE Engine Research Award, ARC LP130100435
Date Deposited: 19 Sep 2019 00:55
FoR Codes: 41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410402 Environmental assessment and monitoring @ 70%
41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410401 Conservation and biodiversity @ 30%
SEO Codes: 96 ENVIRONMENT > 9605 Ecosystem Assessment and Management > 960501 Ecosystem Assessment and Management at Regional or Larger Scales @ 100%
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