{"id":"W2082081125","doi":"10.1016/j.rse.2011.11.020","title":"A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery","year":2011,"lang":"en","type":"article","venue":"Remote Sensing of Environment","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":973,"is_retracted":false,"has_abstract":false,"ca_institutions":"Total (Canada); Trent University; University of Saskatchewan","funders":"","keywords":"Support vector machine; Artificial intelligence; Land cover; Pixel; Computer science; Random forest; Decision tree; Statistical classification; Pattern recognition (psychology); Object (grammar); Contextual image classification; Machine learning; Algorithm; Image (mathematics); Land use","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02497637550135123,"score_gpt":0.2432161822838509,"score_spread":0.2182398067824997,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}