This paper aims to evaluate the accuracy of different ensembles of multiple classifier systems (MCSs) for landslide scar identification.
Ten supervised classifiers were used to identify this severe event and other possible features for the LANDSAT thematic mapper (TM) from June of 2000. The ...
A Comparison of Spectral Angle Mapper and Artificial Neural Network Classifiers Combined with Landsat TM Imagery Analysis for Obtaining Burnt Area Mapping.
In this sense, this paper aims to evaluate the accuracy of different ensembles of multiple classifier systems (MCSs) for landslide scar identification. A severe ...
Supplementary Data. Evaluation of Multiple Classifier Systems for Landslide Identification in LANDSAT Thematic Mapper (TM) Images.
Evaluation of Multiple Classifier Systems for Landslide Identification in LANDSAT Thematic Mapper (TM) Images. ISPRS International Journal of Geo-Information.
Classifier ensembles accuracy evaluation. Evaluation of Multiple Classifier Systems for Landslide Identification in LANDSAT Thematic Mapper (TM) Images.
Oct 27, 2020 · We collected six scenes of recent Landsat Thematic Mapper (TM) data ... Landslide identification and classification by object-based image analysis ...
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Feb 8, 2022 · "Evaluation of Multiple Classifier Systems for Landslide Identification in LANDSAT Thematic Mapper (TM) Images." ISPRS International Journal ...
Apr 20, 2024 · This paper presents a remote sensing-based method to efficiently generate multi-temporal landslide inventories and identify recurrent and persistent landslides.