Monitoring flood extent in the lower Amazon River floodplain using ALOS/PALSAR ScanSAR images

TL;DR: An algorithm to filter out noise from permanent mountain shadow in the flood layer is developed and the result indicates that mountain shadow was significantly removed by using the proposed approach.

TL;DR: This study applies random forest classification to L-band UAVSAR data and ancillary datasets to map inundation extent following Hurricane Florence (2018), achieving an average accuracy of 87% with postclassification refinement and fuzzy logic operations to reduce noise-like features.

TL;DR: Positive correlation among the abundance of the three monogenoideans species were found, thus indicating that there was no competition between the species of these parasites on the gills of hosts, and this host had a metazoan community characterized by high species richness of metazoans, low evenness and high diversity of parasites.

TL;DR: A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.

TL;DR: This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.

TL;DR: This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way.