Automated Land Use Identification Using Hyper Spectral Data and Machine Learning Algorithms

this paper discusses the usage of devices, gaining knowledge of algorithms and hyper spectral facts to discover land use routinely. Hyper spectral information is used to broaden land use classifiers with the use of numerous machine-gaining knowledge techniques, which include aid Vector device (SVM) and Random forest (RF). These land use classifiers are then used to identify land use sorts from hyper spectral photographs. It is miles proven that the land use classifiers that are developed with the use of those gadget mastering algorithms provide correct and efficient identification of land use sorts with excessive type accuracy while compared to different conventional methods. The outcomes reveal the potential of the machine learning algorithms for automatic land use identity from hyper spectral pictures.