JuniperMapper: AI for Shrub Delineation (DATA)

JuniperMapper is a dataset created to individually delineate Juniperus shrubs from satellite images using deep learning models. This data contains two types of datasets collected from the national park of Sierra Nevada, Spain: Photo Interpreted (PI) data: manually created by experts using a visual inspection of satellite images. Field Work (FW) data: manually created by experts using an in-situ inspection. Both datasets contain a set of RGB input images (.tif) at 13 cm resolution downloaded from Google Earth satellites, and their corresponding annotations (shapefiles) delineating each shrub. In addition, a .json file following the COCO dataset structure is also provided to train deep learning models. The PI dataset can be used to develop the deep learning model. It is already partitioned into Train, Validation, and Test sets. While the FW dataset can be used to perform the external validation of the model.