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First Large Extent and High Resolution Cropland and Crop Type Map of Argentina
Resumen
The availability of spatially explicit information about agricultural crops for large regions in Argentina is scarce. In particular, due to temporal dynamics of agricultural production (i.e. changes in planted crops from year to year) and spectral similarities among herbaceous crops it is difficult to generate crop type maps from remote sensing. Large regions with marked climatic variations, like the main agricultural areas of Argentina, represent an
[ver mas...]
The availability of spatially explicit information about agricultural crops for large regions in Argentina is scarce. In particular, due to temporal dynamics of agricultural production (i.e. changes in planted crops from year to year) and spectral similarities among herbaceous crops it is difficult to generate crop type maps from remote sensing. Large regions with marked climatic variations, like the main agricultural areas of Argentina, represent an additional challenge. Here we generated a map based on supervised classifications using field samples along 14 agricultural zones. Best classification accuracies were obtained by combining seasonal indices (year, summer and winter), with indices that describe the temporal dynamics of vegetation. Accuracy was increased at regions with high and balanced number of samples and with longer growing seasons. The map allows to identify areas with clusters of one, two or three crops and to characterize areas with different spatial distribution between cropland and no cropland areas.
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Autor
De Abelleyra, Diego;
Veron, Santiago Ramón;
Banchero, Santiago;
Mosciaro, Maria Jesus;
Propato, Tamara Sofia;
Ferraina, Antonella;
Gómez Taffarel, Maria Cielo;
Dacunto, Luciana;
Franzoni, Agustin;
Volante, Jose Norberto;
Descripción
Trabajo presentado al 2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS 2020), 22–26 March 2020, Santiago, Chile.
Fuente
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W12-2020 (2020)
Fecha
2020-03-22
Editorial
International Society of Photogrammetry and Remote Sensing
Formato
pdf
Tipo de documento
artículo
Palabras Claves
Derechos de acceso
Abierto
Excepto donde se diga explicitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)