GOOGLE EARTH ENGINE
MapBiomas uses technology from the Google Earth Engine platform. We provide scripts to facilitate access to the MapBiomas collections.
To access and run follow the instructions below:
- With a Gmail account, sign up for the Google Earth Engine Platform through this link https://earthengine.google.com
- In a few days, you will receive authorization to access the platform.
- Once registered in Google Earth Engine, insert the link of the scripts you want to run.
- Change the parameters to get the map you want.
We encourage SCRIPT MAPBIOMAS users to send us their suggestions for innovation so that we can constantly improve it.
Access to MapBiomas collection on Google Earth Engine
Images and Maps collections are available to be accessed as an asset directly from Google Earth Engine, without the need to download or upload data. Here are the available products and their access IDs in Google Earth Engine:
Integrated Final Maps of Collection 8
Transition area maps (change of coverage or use) between selected years.
Landsat Imagery Mosaic for each year of Collection 8 8
PLUGIN FOR QGIS
MapBiomas Collections can we accessed direct at QGis through a PlugIn. Watch the instructions to install and use the PlugIn
MapBiomas Processing Codes Depository
The codes used by MapBiomas to produce maps including classification, spatial and temporal filters, data integration, generation of transitions and calculation of statistics, among others, are available in the MapBiomas code repository on GitHub.
Available in: https://github.com/mapbiomas-brazil
TVI (TEMPORAL VISUAL INSPECTION)
Open source online tool for visual inspection of sample points in historical Landsat satellite remote sensing image series. Created by the Image Processing Laboratory of the Federal University of Goiás (LAPIG - UFG), TVI provides subsidies that facilitate and streamline the process of interpreting satellite series for the training and calibration of image classification algorithms. In MapBiomas, TVI was mainly used to obtain validation points of the annual pasture area distribution mappings in the Brazilian territory.