Author Correction: Ground reference data for sugarcane biomass estimation in São Paulo state, Brazil (Scientific Data, (2018), 5, 1, (180150), 10.1038/sdata.2018.150)

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Erratum: Author Correction: Ground reference data for sugarcane biomass estimation in São Paulo state, Brazil (Scientific data (2018) 5 (180150))

Following publication, it was noticed that the horizontal brackets labelling the two groups of precisions present in Equation 7 are incorrectly rendered in the PDF version of this Data Descriptor. The correct Equation 7 is as follows: (Formula presented.) (Formula presented.) In addition, in the Biomass subsection of the Methods section in...

Sugarcane productivity mapping through C-band and L-band SAR and optical satellite imagery

Space-based remote sensing imagery can provide a valuable and cost-effective set of observations for mapping crop-productivity differences. The effectiveness of such signals is dependent on several conditions that are related to crop and sensor characteristics. In this paper, we present the dynamic behavior of signals from five Synthetic...

Data descriptor: Ground reference data for sugarcane biomass estimation in São Paulo state, Brazil

In order to make effective decisions on sustainable development, it is essential for sugarcane-producing countries to take into account sugarcane acreage and sugarcane production dynamics. The availability of sugarcane biophysical data along the growth season is key to an effective mapping of such dynamics, especially to tune agronomic models...

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Current space-based SAR offers unique opportunities to classify vegetation types and to monitor vegetation growth due to its frequent acquisitions and its sensitivity to vegetation geometry. However, SAR signals also experience frequent temporal fluctuations caused by precipitation events, complicating the mapping and monitoring of vegetation....

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The paper debates the impact of sensor configuration diversity on the crop classification performance. More specifically, the analysis accounts for multi-temporal and polarimetric C-Band SAR information used individually and in synergy with Multispectral imagery. The dataset used for the investigation comprises several multi-angle Radarsat-2 ...