Surface wave methods, commonly applied in diverse fields, encounter challenges in complex subsurface environments due to limitations inherent in traditional inversion techniques. Conventional one-dimensional inversion (1DI), with its reliance on fixed grids and deterministic linear approaches, often introduces biases, diminishing lateral resolution. Laterally constrained inversion (LCI) improves robustness by addressing lateral coherency but falls short in delineating arbitrary interfaces due to its dependency on fixed grid models. The advent of Distributed Acoustic Sensing (DAS) technology offers extensive seismic data, yet its potential for high-resolution imaging remains underutilized. We introduce a Multigrid Spatially Constrained Dispersion Curve Inversion (MCI) method to overcome these challenges, aiming to harness high-resolution DAS surface wave imaging capabilities. The package includes essential scripts and models required to replicate key figures from the study by Guan et al. (2023, currently under review). These codes are designed to help readers evaluate the effectiveness of the MCI approach using synthetic demonstrations. Additionally, the package includes a refined 2D Vs (shear wave velocity) model derived from a DAS (Distributed Acoustic Sensing) field study conducted in Imperial Valley, California. This model offers new insights into the regional fault system, underscoring the importance of enhanced spatial resolution in large-scale geophysical investigations. It is organized into three directories and contains a total of 14 files. The directory structure is as follows:├── DAS field data│ ├── Pltmodels.m│ ├── README.txt│ ├── field_models.pdf│ ├── model_1DI.mat│ ├── model_LCI.mat│ └── model_MCI.mat├── MCI_Main│ ├── DisForward.p│ ├── InvForward.p│ ├── InvJacobian.p│ ├── MCI.p│ ├── readme.txt│ └── whitejet3.m└── Synthetic demos ├── MCI_Main.m └── syndata.mat