Remap is an online mapping platform for people with little technical background in remote sensing. We developed remap to enable you to quickly map and report the status of ecosystems, contributing to a global effort to assess all ecosystems on Earth under the IUCN Red List of Ecosystems.
The general workflow of Remap is:
Development of Remap is split into two halves:
Located in the
/backend directory, this is a Python2.7 webapp2 running on Google App Engine. It provides the front facing app (in the
/app directory) the endpoints starting with
/api that call the Google Earth Engine's python API and allow the client to create maps, visualise predictors.
It also serves the companion site (ie home, about).
Located in the
/app directory, this is Remap.
It needs the Python Backend to be running to work locally.
Follow the instructions found on: Earth engine apps to install the Google Cloud SDK.
Additionally you will need an Earth Engine service account.
Add secrets to secrets folder
wsgi.txtA file with the wsgi key on the first line and an empty second line.
ee_account.txtA file with the Earth Engine service account name on the first line and an empty second line.
client_secrets.jsonA json file that has the OAuth2 details in it. You should download it when you configure the OAuth2 details in the google cloud console.
gee_service_account_secrets.jsonA json file that has the earth engine service account details in it. You should download it when you create the service account.
npm installto install the required packages.
In one terminal run
sh das.sh to start the dev appserver.
In a new terminal run
sh remap_dev.sh to start the webpack dev server.
You should be able to find the local site at: http://localhost:8090
If you have made some changes in
/app you will need to build remap by running
sh build.sh then you can deploy the built app by running
The Remap app was developed with funding from a Google Earth Engine Research Award. To find further information about the background, inner workings and methods of Remap please refer to our preprint manuscript on bioRxiv. https://www.biorxiv.org/content/early/2017/11/01/212464
Or email: [email protected]
Murray, N.J., Keith, D.A., Simpson, D., Wilshire, J.H. & Lucas, R.M. (2017) REMAP: An online remote sensing application for land cover classification and monitoring. bioRxiv. DOI: 10.1101/212464