updated change log

Author: print-sid8

docs/changelog.md

@@ -1,21 +1,30 @@
 # Changelog
 
-## v0.3.0
+## v0.3.0 (unreleased)
 
 ### Highlights
 
 - License changed from AGPL-3.0-only to **Apache-2.0**.
-- **Dataset catalog**: `build()` with 13 pre-registered datasets across
+- **Dataset catalog**: `build()` with 12 pre-registered datasets across
   Earth Search, Planetary Computer, and AlphaEarth Foundation.
+  Catalog entries can point to a STAC API or a GeoParquet file.
   `register_local()` for adding your own.
+- **`build_from_stac()`** and **`build_from_table()`**: build a Collection
+  from any STAC API or any Parquet/GeoParquet file with COG URLs (Source
+  Cooperative exports, STAC GeoParquet, custom catalogs). No STAC API
+  required for the table path. Optional `enrich_cog=True` parses COG
+  headers for accelerated reads.
 - **Multi-cloud obstore backend**: S3, Azure Blob, and GCS routing via URL
   auto-detection, with automatic fallback to anonymous access.
 - **`create_backend()`** for authenticated reads with obstore credential
   providers (e.g., Planetary Computer SAS tokens).
 - **TorchGeo adapter**: `collection.to_torchgeo_dataset()` returns a
   `GeoDataset` backed by Rasteret's async COG reader. Supports
-  `time_series=True` (`[T, C, H, W]` output), multi-CRS reprojection,
-  and works with all TorchGeo samplers and collation helpers.
+  `time_series=True` (`[T, C, H, W]` output), `label_field` for
+  per-sample labels, `target_crs` for cross-CRS reprojection,
+  `allow_resample=True` for mixed-resolution bands, and `is_image=False`
+  for mask-style datasets. Works with all TorchGeo samplers, collation
+  helpers, and dataset composition (`IntersectionDataset`, `UnionDataset`).
 - **Native dtype preservation**: COG tiles return in their source dtype
   (uint16, int8, float32, etc.) instead of forcing float32.
 - **Rasterio-aligned masking**: AOI reads default to `all_touched=False`
@@ -29,16 +38,41 @@
 - **Multi-CRS auto-reprojection**: queries spanning multiple UTM zones
   reproject to the most common CRS using GDAL's
   `calculate_default_transform`.
+- **`get_numpy()`**: lightweight NumPy output path returning `[N, H, W]`
+  (single band) or `[N, C, H, W]` (multi-band) arrays. No extra
+  dependencies beyond NumPy. Accepts bbox tuples, Arrow arrays, Shapely
+  objects, or raw WKB.
+- **`get_gdf()`**: GeoDataFrame output path for analysis workflows.
+- **Enriched Parquet workflows**: append arbitrary columns (splits, labels,
+  AOI polygons, model scores) to a Collection's Parquet, query with
+  DuckDB/PyArrow, and fetch pixels for matching rows on demand. See
+  [Enriched Parquet Workflows](how-to/enriched-parquet-workflows.md).
+- **Major TOM on-the-fly**: example workflow rebuilding Major TOM-style
+  patch-grid semantics from source Sentinel-2 COGs instead of
+  payload-in-Parquet. Benchmarked 3.9-6.5x faster than HF `datasets`
+  Parquet-filter reads.
+- **`earthdata` optional extra**: `pip install rasteret[earthdata]` for
+  NASA Earthdata auto-credential detection.
 
 ### Collection API
 
+- **Output paths**: `get_xarray()`, `get_numpy()`, `get_gdf()`,
+  `to_torchgeo_dataset()`. All share the same async tile I/O underneath.
 - **Inspection**: `.bands`, `.bounds`, `.epsg`, `len()`, `__repr__()`,
   `.describe()`, `.compare_to_catalog()`.
 - **Filtering**: `collection.subset(cloud_cover_lt=..., date_range=...,
   bbox=..., geometries=..., split=...)` and `collection.where(expr)` for
   raw Arrow expressions.
 - **Sharing**: `collection.export("path/")` writes a portable copy;
-  `rasteret.load("path/")` reloads it.
+  `rasteret.load("path/")` reloads it. `list_collections()` discovers
+  cached collections in the workspace.
+- **Three-tier schema**: required columns (`id`, `datetime`, `geometry`,
+  `assets`), COG acceleration columns (per-band tile offsets and metadata),
+  and user-extensible columns (`split`, `label`, `cloud_cover`, custom
+  metadata). See [Schema Contract](explanation/schema-contract.md).
+- **Public exports**: `Collection`, `CloudConfig`, `BandRegistry`,
+  `DatasetDescriptor`, `DatasetRegistry` are all importable from
+  `rasteret`.
 
 ### Other changes
 
@@ -49,12 +83,24 @@
 - TorchGeo `time_series=True` uses spatial-only intersection, matching
   TorchGeo's own `RasterDataset` behaviour where all spatially overlapping
   records are stacked regardless of the sampler's time slice.
+- Cloud workspace URIs (e.g. `s3://bucket/path`) are preserved correctly
+  in `CollectionBuilder` base class.
 
 ### Tested
 
-- All three output paths (xarray, GeoDataFrame, TorchGeo) tested against
-  direct rasterio reads across 12 datasets (Sentinel-2, Landsat, NAIP,
-  Copernicus DEM, ESA WorldCover, AEF, and more).
+- All four output paths (xarray, GeoDataFrame, NumPy, TorchGeo) tested
+  against direct rasterio reads across 12 datasets (Sentinel-2, Landsat,
+  NAIP, Copernicus DEM, ESA WorldCover, AEF, and more).
+- TorchGeo adapter verified against the full GeoDataset contract:
+  `IntervalIndex`, samplers, collation, dataset composition, cross-CRS
+  reprojection, and export/reload roundtrips.
+
+### Requirements
+
+- **Python 3.12+** required.
+- `rasterio>=1.4.3,<1.5.0` is a core dependency (used for geometry
+  masking, CRS reprojection, and TorchGeo query-grid placement; not in
+  the tile-read path).
 
 ### Breaking changes