Inspect a Layer’s Projection, Extent and Bands

Before you can symbolize, filter or reproject data with confidence, it helps to know what the data actually is: which Coordinate Reference System it is stored in, what area it covers, how many bands it has and what range of values those bands hold.

JupyterGIS reports all of this in the Metadata tab of the Layer Properties dialog.

Open the Metadata tab

Right-click a layer in the Layers panel and choose Layer Metadata.

You can also open Layer Properties (by right-clicking the layer, or by double-clicking it) and switch to the Metadata tab.

Note

Metadata is read when you open the tab, not when you select the layer. For a remote file this means a short pause the first time while JupyterGIS reads the file’s header.

What you will see

Which sections appear depends on what the data format is able to tell us.

General — the layer’s name, the layer and source types, and where the data is loaded from.

Coordinate reference system — the EPSG code the data is stored in, its name, its units, and its proj4 definition. The code links to epsg.io, where you can read a full description of the projection.

Note

JupyterGIS does not bundle a projection database, so a well-known-text (WKT) definition is only shown when the file itself carries one. The EPSG code and proj4 string are enough to identify the Coordinate Reference System unambiguously.

Extent — the bounding box of the data, given both in the data’s own coordinate reference system and in EPSG:4326 longitude/latitude. Where JupyterGIS could not read an extent from the data itself, it falls back to the extent the layer occupies on the map and says so.

Features — for vector layers: how many features there are, which geometry types they use, and the columns of the attribute table with their types.

Bands — for raster layers: one row per band, with its data type, its no data value and its range of values. This is the quickest way to find the numbers you need when configuring symbology.

Note

Not every raster stores band statistics. When they are missing, JupyterGIS estimates the range from a downsampled overview and tells you it has done so; for a very large file with no overviews it reports no range at all rather than downloading the whole raster.

Tile pyramid — the reduced-resolution copies stored inside the file (the overviews that make a GeoTIFF a Cloud-Optimized GeoTIFF), or, for a tiled web service, the range of zoom levels it serves.

Supported formats

GeoTIFF, GeoZarr, GeoJSON, shapefiles, GeoParquet, XYZ raster tiles, vector tiles and WMS are read in detail.

Any other source type still shows its General section and the extent JupyterGIS computed when it drew the layer.