Launching remap: our new remote sensing web-app

In 2016 we received funding from Google to develop an online remote sensing application that allows users to quickly develop classified maps for any location on Earth. After 15 months of work, we are pleased to launch remap, the remote ecosystem monitoring and assessment pipeline (https://remap-app.org).

Our idea was to use the immense power of the Google Earth Engine to access freely available satellite imagery, run a map classification, and return maps of land cover. This analysis workflow has been a central component of environmental monitoring programs globally, and has been critical in monitoring threats such as deforestation, land clearing and reclamation of coastal wetlands. In addition, maps of land cover are vital for understanding the distribution and status of ecosystems and how they change over time.

To use remap, simply teach it what you want to map by identifying different ecosystems or land cover types within your study area. Remap then uses the Google Earth Engine to classify the data, returning a highly accurate map that can be analysed within remap or downloaded to your computer.

Remap features built-in methods to calculate the spatial metrics required by the IUCN Red List of Ecosystems, and the ability to develop a map time-series maps from Landsat data acquired over the last 20 years. Because remap can be used to map any type of land cover, it is also useful for quickly developing maps of water distribution, deforestation, urbanisation, and anything else that is observable by Landsat.

Remap was launched at the Convention on Biological Diversity meeting in Montreal in early December 2017. For more information go to the remap website, launch the app and work your way through the quick-start guide and tutorials.

Also read the preprint describing remap on BioRxiv:

Murray, N.J., Keith, D.A., Simpson, D., Wilshire, J.H., Lucas, R.M. (2017) remap: A cloud-based remote sensing application for generalized ecosystem classifications. bioRxiv https://dx.doi.org/10.1101/212464.