# Interactive tools

Tools showcasing the use of sits concepts in various domains. Use to learn and feel the possibilities.

- [Create a data cube](/interactive-tools/create-cube.md): How do images taken at irregular times become a regular cube? A regular data cube made in your browser by [gdalcubes.py](https://github.com/spatial-tools/gdalcubes.py) compiled to WebAssembly. A quick flavour of how images taken on irregular dates become one image per regular interval, from live Sentinel-2 L2A or Landsat 8/9 L2 imagery. Select an area on the map, choose the settings and press Regularize; nothing is fetched before. Journey: [Building data cubes from image collections, step 4: What does sits_regularize() do?](/regular-cubes#regularize).
- [Regularization settings](/interactive-tools/regularization-settings.md): What does sits_regularize() make of the images when you change the period or the cell? `sits_regularize()` turns the irregular Sentinel-2 images of two tiles into a cube with one image per period, on one grid of cells. Choose the period, the cell size and the tile to see every date of the cube it makes, from a recorded run of the pipeline. Open a date to see which images it was made from, in sits' order, and how each filled the cells. Journey: [Building data cubes from image collections, step 4: What does sits_regularize() do?](/regular-cubes#regularize).
- [Similar places](/interactive-tools/similarity.md): Which places look like this one to the encoder? Each pixel of a 256 × 256 window in the Cerrado, near 13.8° S, 57.8° W, has an embedding: 64 numbers the LeJEPA encoder from sits (`sits_ssl_lejepa`, pretrained on 647,967 time series) gives its time series, for the 2018 map. Pick a pixel and the page finds the pixels whose embeddings are closest to it, by Euclidean or cosine distance, and shows their land cover on the map sits made from the same embeddings. Journey: [From series to embeddings, step 5: What are these 64 numbers?](/embeddings#vector).