MAPLE Initial Release

Mapping Application for Arctic Permafrost Land Environment (MAPLE) serves as the main container/pipeline harboring multiple mapping workflows. The MAPLE is essentially an extensible pipeline that centers on DL and high performance computing. It allows users to interlace different deep learning convolutional neural net algorithms to conveniently analyze remote sensing imagery and geospatial data. This release uses a trained Mask-RCNN to map the Ice Wedge Polygons from high spatial resolution remote sensing data (sub-meter imagery) acquired by commercial satellite sensors

Primary contributor:

• Rajitha Udawapola @rajithaud

Other Contributors:

• Amith Hasan @amit-eee
• Elias Manos @eliasm56
• Amal Shehan Perera @amalshehan