Probabilistic Ensemble Machine Learning and Remote Sensing Integration for Betel Vine (Piper betle L.) Site-Suitability Assessment in Purba Medinipur District, India

2026/06/24 by Debabrata Chanda, Sayanti Poddar, Uttam Mukhopadhyay +3 · 1 voice
Environmental Science · #Groundwater and Watershed Analysis #Soil Geostatistics and Mapping #Soil and Land Suitability Analysis

paper · doi:10.1007/s12061-026-09924-x

crossref issued 2026/06/24 · crossref published 2026/06/24 · crossref published-online 2026/06/24 · openalex publication_date 2026/06/24 · crossref created 2026/06/24 · crossref deposited 2026/06/24 · crossref indexed 2026/06/24 · openalex created_date 2026/06/25 · openalex updated_date 2026/07/23 · crossref published-print 2026/09/01

Citations

• Implementation of machine-learning classification in remote sensing: an applied review
• Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review
• Google Earth Engine for geo-big data applications: A meta-analysis and systematic review
• A standard protocol for reporting species distribution models
• ERA5-Land: a state-of-the-art global reanalysis dataset for land applications
• Ensemble deep learning: A review
• SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty

Discussions

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