Course Information

This workshop will address the data products and software tools of the Brazil Data Cube Platform (http://brazildatacube.org/). The Brazil Data Cube (BDC) project is producing more than 2 petabytes of Analysis-Read Data (ARD) and multidimensional data cubes of satellite images Landsat-8/-9, Sentinel-2, CBERS-4/-4A and Amazonia for the entire Brazilian territory. Besides that, the BDC project is developing software tools to deal with big data sets, to extract image time series from Earth observation (EO) data cubes and to produce land use and land cover information using image time series and machine learning.

This workshop will address concepts of EO data cubes and satellite image time series analysis as well as promote hands-on activities using Python language for: (1) Discovering, accessing and viewing EO data cubes; (2) Extraction of satellite image time series from EO data cubes; (3) Analysis of satellite image time series; and (4) Extraction of land use and land cover trajectories. All software tools of the BDC platform will be demonstrated: BDCExplorer, TerraCollect, Satellite Image Time Series (SITS) R package and the web services, SpatioTemporal Asset Catalog (STAC), Web Time Series Service (WTSS) and Web Land Trajectory Service (WLTS).

The main goal of the BDC is to support environmental monitoring, land use and land cover applications, agricultural management, and other applications that require consistent and temporally structured EO satellite images and geospatial information. Image time series extracted from EO data cubes improve our understanding of environmental patterns and processes. Instead of selecting individual images from specific dates and comparing them, researchers can track change continuously. Satellite image time series analysis captures subtle changes in ecosystems and improves the quality of land classification.

BDC provides ARD and multidimensional data cubes of images from sensors onboard Landsat-8, Landsat-9, Sentinel-2, CBERS-4, CBERS-4A and AMAZONIA-1 satellites. Products like MOD13Q1 and MYD13Q1, which are derived from TERRA/MODIS and AQUA/MODIS satellite/sensor are also incorporated into BDC as data cubes. Using the same technologies to produce EO data cubes, BDC also produces Visualization Mosaics. BDC manages more than 2 petabytes of data, which brings big data challenges. Thus, the BDC platform also provides software tools to efficiently deal with these big EO data sets.

Responsibles:

  • Karine Reis Ferreira

  • Baggio Luiz de Castro

  • Rennan Marujo

  • Gabriel Sansigolo

Requirements

Each participand must have access to a computer.

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