Journal
EUROPEAN JOURNAL OF REMOTE SENSING
Volume 49, Issue -, Pages 361-380Publisher
ASSOC ITALIANA TELERILEVAMENTO
DOI: 10.5721/EuJRS20164920
Keywords
Early mapping; crop type; multi-temporal data; supervised classification; Landsat 8 OLI
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Funding
- AQ CNR-Regione Lombardia (CNR, Convenzione Operativa) [18091/RCC]
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This study investigated the feasibility of delivering a crop type map early during the growing season. Landsat 8 OLI multi-temporal data acquired in 2013 season were used to classify seven crop types in Northern Italy. The accuracy achieved with four supervised algorithms, fed with multi-temporal spectral indices (EVI, NDFI, RGRI), was assessed as a function of the crop map delivery time during the season. Overall accuracy (Kappa) exceeds 85% (0.83) starting from mid-July, five months before the end of the season, when maximum accuracy is reached (OA=92%, Kappa=0.91). Among crop types, rice is the most accurately classified, followed by forages, maize and arboriculture, while soybean or double crops can be confused with other classes.
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