A framework based on spectral similarity to estimate hydrological connectivity in Juruá River floodplain lakes using 3-m PlanetScope data

•First approach for hydrological connectivity mapping using spectral similarity and machine learning.•Procedures for large training dataset generation for lake connectivity mapping.•L-CONNECT framework achieved 88% overall accuracy in connectivity mapping.•River-lake spectral similarity indices are reliable proxy for connectivity analysis.