fix the quickstart documentation for export_embedding_geotiffs

the current interface is a bit suboptimal as it should use a Tiles
list but saving that for a future rev of the interface (#122).

fixes #115
reported by @GieziJo

Author: avsm

.github/copilot-instructions.md

@@ -197,7 +197,7 @@ tiles = gt.registry.load_blocks_for_region(bounds=bbox, year=2024)
 embeddings = gt.fetch_embeddings(tiles)
 
 # Export as GeoTIFF
-files = gt.export_embedding_geotiffs(bbox=bbox, output_dir="./output", year=2024)
+files = gt.export_embedding_geotiffs(tiles_to_fetch=tiles, output_dir="./output")
 ```
 
 ### Registry Operations

README.md

@@ -236,10 +236,14 @@ for year, tile_lon, tile_lat, embedding_array, crs, transform in embeddings:
 
 ```python
 # Export embeddings for a region as individual GeoTIFF files
+# Step 1: Get the tiles for the region
+bbox = (-0.2, 51.4, 0.1, 51.6)
+tiles_to_fetch = gt.registry.load_blocks_for_region(bounds=bbox, year=2024)
+
+# Step 2: Export those tiles as GeoTIFFs
 files = gt.export_embedding_geotiffs(
-    bbox=(-0.2, 51.4, 0.1, 51.6),
+    tiles_to_fetch=tiles_to_fetch,
     output_dir="./output",
-    year=2024,
     bands=None,  # Export all 128 bands (default)
     compress="lzw"  # Compression method
 )
@@ -248,9 +252,8 @@ print(f"Created {len(files)} GeoTIFF files")
 
 # Export specific bands only (e.g., first 3 for RGB visualization)
 files = gt.export_embedding_geotiffs(
-    bbox=(-0.2, 51.4, 0.1, 51.6),
+    tiles_to_fetch=tiles_to_fetch,
     output_dir="./rgb_output",
-    year=2024,
     bands=[0, 1, 2]  # Only export first 3 bands
 )
 ```

docs/quickstart.rst

@@ -428,17 +428,15 @@ Complete analysis workflow::
     selected_tiles = [r for r in results if r['mean_band_50'] > threshold]
     
     print(f"Exporting {len(selected_tiles)} tiles above threshold")
-    
-    files = []
-    for tile in selected_tiles:
-        file = gt.export_embedding_geotiffs(
-            bbox=(tile['lon']-0.05, tile['lat']-0.05, 
-                  tile['lon']+0.05, tile['lat']+0.05),
-            output_dir="./selected_tiles",
-            year=2024,
-            bands=[40, 50, 60]  # Bands around band 50
-        )
-        files.extend(file)
+
+    # Prepare tiles for export
+    tiles_to_export = [(2024, tile['lon'], tile['lat']) for tile in selected_tiles]
+
+    files = gt.export_embedding_geotiffs(
+        tiles_to_fetch=tiles_to_export,
+        output_dir="./selected_tiles",
+        bands=[40, 50, 60]  # Bands around band 50
+    )
     
     # Create PCA visualization from selected tiles
     # CLI: geotessera visualize ./selected_tiles pca_selected.tif
@@ -468,17 +466,16 @@ Use both numpy and GeoTIFF formats in the same workflow::
             selected_coords.append((lon, lat))
     
     print(f"Selected {len(selected_coords)} interesting tiles")
-    
-    # Step 2: Export selected tiles as GeoTIFF  
-    all_files = []
-    for lon, lat in selected_coords:
-        files = gt.export_embedding_geotiffs(
-            bbox=(lon-0.05, lat-0.05, lon+0.05, lat+0.05),
-            output_dir="./interesting_tiles",
-            year=2024,
-            bands=[60, 64, 68]  # Bands around interesting band 64
-        )
-        all_files.extend(files)
+
+    # Step 2: Export selected tiles as GeoTIFF
+    # Prepare tiles for export
+    tiles_to_export = [(2024, lon, lat) for lon, lat in selected_coords]
+
+    all_files = gt.export_embedding_geotiffs(
+        tiles_to_fetch=tiles_to_export,
+        output_dir="./interesting_tiles",
+        bands=[60, 64, 68]  # Bands around interesting band 64
+    )
     
     # Step 3: Create PCA visualization from selected tiles
     print("Creating PCA visualization...")