Laser-induced breakdown spectroscopy (LIBS) is an analytical method with optical emission spectroscopy that uses a laser pulse to vaporize, atomize, and excite a hot plasma as the spectroscopic emission source. Although LIBS has demonstrated its versatility and attractive features in many fields, the quantitative analysis ability of LIBS is considered as its Achilles' heel. From a fundamental point of view, this can be due to the complex nature of laserinduced plasma as the spectroscopic emission source for LIBS application. The temporal and spatial characterization of laser-induced plasma is considered as one of the key points for the LIBS technique. On the other hand, from the analytical point of view, LIBS is usually characterized by direct laser ablation. This can be however quite limiting, especially for some types of materials such as powders or liquids. Proper sample preparation or treatment allowing the deposition of a thin homogeneous film on a metallic surface could greatly improve the analytical performance of LIBS for these types of materials. Since the metallic surface is expected to contribute to increase the temperature and the density of the plasma and, consequently, to a better overall sensitivity, we call this technique surface-assisted LIBS. The present thesis work is therefore motivated by two basic aspects of LIBS analysis: the need of an improved knowledge of laser-induced plasma as a spectroscopic emission source, and new methods to improve the analytical performance of LIBS, including a higher sensibility and a reduced matrix effect. The first part of this thesis (Chapter 2) is dedicated to an extensive characterization of the plasma induced on glass samples, as a function of the laser wavelength, infrared (IR) or ultraviolet (UV), and the ambient gas, air or argon. Both the spectroscopic imaging and time- and space-resolved emission spectroscopy are used for plasma diagnostics in this work. The second part of this thesis is to develop a surface-assisted LIBS method for the elemental analysis in powders, and in wines as examples of liquids. We applied the surface-assisted LIBS for the quantitative elemental analysis in cellulose powders, alumina powders, and soils (Chapter 3). Special attentions are paid on the figures-of-merit, matrix effects, and normalization approaches in LIBS analysis. We also used the surfaceassisted LIBS for the classification of French wines according to their production regions (Chapter 4). Two classification models based on the principal component analysis (PCA) and random forest (RF) are used for the classification. Through these applications, this thesis work demonstrates the efficiency of the surface-assisted LIBS method for the analysis of powders (cellulose, alumina and soils) and of liquids (wines), with ppm or sub-ppm sensitivities and a reduced matrix effect.