[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Hyperspectral Image Classification Based on Spectral Mixture Analysis for Crop Type Determination

摘要： For the application of agricultural area, remote sensing techniques were studied and applied for its advantages for continuous and quantitative monitoring. Especially, hyperspectral images have been studied for the precise agriculture since they provide chemical and physical information of vegetation. In this study, we analyzed crop types using hyperspectral image data collected by a ground scanner. Spectral mixture analysis, which is widely used for processing hyperspectral images, was adopted for the crop discrimination. Endmember extraction algorithms used in this study were N-FINDR, Vertex Component Analysis (VCA), and Simplex Identification via variable Splitting and Augmented Lagrangian (SISAL), and classification was processed using fully constrained linear spectral unmixing (FCLSU). This study presents the application of spectral mixture analysis for hyperspectral scanner data at canopy level and optimal endmember extraction algorithms for different crop types for precise agriculture.