{"id":"W4224010467","doi":"10.1080/07038992.2022.2056435","title":"A Comparison between Sentinel-2 and Landsat 8 OLI Satellite Images for Soil Salinity Distribution Mapping Using a Deep Learning Convolutional Neural Network","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Normalized Difference Vegetation Index; Convolutional neural network; Soil salinity; Satellite; Remote sensing; Deep learning; Salinity; Satellite imagery; Environmental science; Artificial neural network; Vegetation (pathology); Computer science; Artificial intelligence; Pattern recognition (psychology); Soil science; Geography; Soil water; Geology; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001330969,0.0005585616,0.0002701532,0.0010556,0.0001489832,0.0004870096,0.0004929155,0.0004928314,0.0006383072],"category_scores_gemma":[0.001901964,0.0001607747,0.0003149435,0.0006499871,0.0001643954,0.001137447,0.0004649134,0.000259887,0.0002168598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005402806,"about_ca_system_score_gemma":0.0003950139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01161283,"about_ca_topic_score_gemma":0.02259547,"domain_scores_codex":[0.9996883,0.00006387955,0.00001757953,0.00008350189,0.00009380191,0.00005291702],"domain_scores_gemma":[0.9994967,0.0001455837,0.00004765942,0.00005343423,0.0002185553,0.00003814012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001604649,0.0005218831,0.3072,0.0004030617,0.0005480096,0.0004269817,0.0002408403,0.2289612,0.06943035,0.001388541,0.003990674,0.3852839],"study_design_scores_gemma":[0.00002213788,0.0001464498,0.07799043,0.00003176405,0.0000706127,0.0000986349,0.0001443786,0.9059747,0.01407502,0.000374441,0.001042288,0.0000291863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9575742,0.0006060243,0.03604006,0.0002270235,0.00006886185,0.00004184616,0.0009382031,0.000690362,0.003813401],"genre_scores_gemma":[0.9800182,0.000190259,0.01753578,0.00006160253,0.00001040034,0.00001337993,0.001435542,0.00002715335,0.0007076373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01161283,"threshold_uncertainty_score":0.02309048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03039248484520905,"score_gpt":0.255508552685914,"score_spread":0.2251160678407049,"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."}}