To realize the accurate extraction of surface water in complex environment, this study takes Sri Lanka as the study area owing to the complex geography and various types of water bodies. Based on Google Earth engine and Sentinel-2 images, an automatic water extraction model in complex environment(AWECE) was developed. The accuracy of water extraction by AWECE, NDWI, MNDWI and the revised version of multi-spectral water index (MuWI-R) models was evaluated from visual interpretation and quantitative analysis. The results show that the AWECE model could significantly improve the accuracy of water extraction in complex environment, with an overall accuracy of 97.16%, and an extremely low omission error (0.74%) and commission error (2.35%). The AEWCE model could effectively avoid the influence of cloud shadow, mountain shadow and paddy soil on water extraction accuracy. The model can be widely applied in cloudy, mountainous and other areas with complex environments, which has important practical significance for water resources investigation, monitoring and protection.

Herein, surface-enhanced Raman spectroscopy (SERS) combined with principal component analysis (PCA) has been successfully applied in the evaluation of cigarette flavoring quality using monolayer films of Au nanoparticles as substrates. With such a method, even a slight difference in the formula of the essence that cannot be directly identified by SERS can be distinguished.

An IR/RAMAN spectra simulation system is reported. The development of this software was based on the substructure/subspectrum relationships established for four different structural classes: small molecules, special fragments, atom-centered FRELs, and bond-centered FRELs (FREL: Fragment centered on an Environment which is Limited). Four corresponding knowledge-bases (now, at a pilot stage) are constructed from usual correlation charts or data analyses of large populations of compounds using data mining techniques.