Assessing the suitability of data from Sentinel-1A and 2A for crop classification

GIScience and Remote Sensing

Volumn 54, Issue 6, 2017, Pages 918-938

  Sonobe, Rei ^a   Yamaya, Yuki ^b   Tani, Hiroshi ^b   Wang, Xiufeng ^b   Kobayashi, Nobuyuki ^c   Mochizuki, Kan ichiro ^d  

^a SHIZUOKA UNIVERSITY   (Japan)

^b HOKKAIDO UNIVERSITY   (Japan)

^c Smart Link Hokkaido   (Japan)

^d PASCO CORPORATION   (Japan)

Author keywords

agricultural fields; classification; Hokkaido; machine learning; Sentinel 1A; Sentinel 2A

Indexed keywords

ALGORITHM; BAYESIAN ANALYSIS; CROP YIELD; DATA ACQUISITION; IMAGE CLASSIFICATION; MACHINE LEARNING; OPTIMIZATION; SATELLITE DATA; SENTINEL;

HOKKAIDO; JAPAN;

SOLANUM TUBEROSUM; TRITICUM AESTIVUM; ZEA MAYS;

EID: 85022216039     PISSN: 15481603     EISSN: None     Source Type: Journal    
DOI: 10.1080/15481603.2017.1351149     Document Type: Article

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