Slide 1

Production, visualization and analysis of large volumes of remote sensing images modeled as multidimensional data cubes for the entire Brazilian territory.

Data Cube


Multidimensional data cubes from analysis-ready data (ARD) of CBERS-4, CBERS-4A, Landsat-8 and Sentinel-2 satellite images

Figure 1. Grids with sizes of 1×1.5, 2×3 and 4×6 degrees

Data cubes are generated from ARD products from the BDC data collections. In the context of the BDC project, three grids with cells of different sizes were defined to contain the products according to the spatial resolution of the ARD images. Grids have sizes of 1×1.5, 2×3 and 4×6 degrees and a cartographic projection is associated with them. Figure 1 depicts these grids.

Data cubes can be categorized into two types: identity and time composite. Identity cube represents acquisitions of images on the original sensor dates, while in a composite cube a pixel value is chosen into a period of time, for example 16 days or 1 month, to compose the final product.

The temporal composition function calculates or selects the value of a pixel within a time interval on an identity cube. The temporal composition function can be mean, median or STACK. For example, given a time interval the average time composition evaluates all free cloud and cloud shadow values given a cloud mask and then calculates the final average value for each spectral band. In the case of STACK, a sorting is made based on the useful area of the images, considering the cloud cover and shadow, so the resulting value of the STACK composition is obtained from the first value found, if there is cloud or shadow in the first ordered image, the values of the pixels are taken from the second image and so on. Figure 2 illustrates these procedures.

WTLSS

BDC products are stored and distributed in COG (Cloud Optimized GeoTIFF) format, the table below illustrates the data cubes generated in the BDC project.

Data cubes generated by the BDC.

Cube CollectionSatelliteSensorsSpatial Resolution (m)Temporal Compositing
CB4_64CBERS-4AWFI64Identity
CB4_64_16D_STKCBERS-4AWFI6416 days Stack
CB4_20_1M_STKCBERS-4MUX201 month Stack
LC8_30Landsat-8OLI30Identity
LC8_30_16D_STKLandsat-8OLI3016 days Stack
MOD13Q1TERRAMODIS25016 days Best Pixel
MYD13Q1AQUAMODIS25016 days Best Pixel
S2_10Sentinel 2A/2BMSI10Identity
S2-SEN2COR_10_16DSentinel 2A/2BMSI1016 days Stack
Brazil Data Cube - 2019 - 2023