Changelog¶

All notable changes to this project will be documented in this file.

[v0.7.4] - 2025-11-24¶

Added¶

• TifProcessor: Raster Export Methods

  • save_to_file() method: Comprehensive raster export functionality with flexible compression and optimization options.

    • Supports multiple compression algorithms: LZW (default), DEFLATE, ZSTD, JPEG, WEBP, and NONE.
    • Configurable compression parameters: ZLEVEL for DEFLATE (default: 6), ZSTD_LEVEL for ZSTD (default: 9), JPEG_QUALITY (default: 85), WEBP_LEVEL (default: 75).
    • Predictor support for improved compression: predictor=2 for integer data (horizontal differencing), predictor=3 for floating-point data.
    • Tiled output enabled by default (512×512 blocksize) for optimal random access performance.
    • Cloud-Optimized GeoTIFF (COG) support via cog=True parameter with automatic overview generation.
    • Customizable overview levels and resampling methods for COG creation.
    • BigTIFF support for files >4GB via bigtiff parameter.
    • Multi-threading support for compatible compression algorithms via num_threads parameter.
    • Integrates with self.open_dataset() context manager, automatically handling merged, reprojected, and clipped rasters.
    • Writes through self.data_store abstraction layer, supporting both local and remote storage (e.g., ADLS).
    • Preserves all bands from source rasters without skipping.

  • save_array_to_file() method: Export processed numpy arrays while preserving georeferencing metadata.

    • Accepts 2D or 3D numpy arrays (with automatic dimension handling).
    • Inherits CRS, transform, and nodata values from source raster or accepts custom values.
    • Supports same compression options as save_to_file().
    • Enables saving modified/processed raster data while maintaining spatial reference.
    • Writes through self.data_store for consistent storage abstraction.

• TifProcessor: Value-Based Filtering for DataFrame and GeoDataFrame Conversion

  • min_value and max_value parameters: Added optional filtering thresholds to to_dataframe() and to_geodataframe() methods.

    • min_value: Filters out pixels with values ≤ threshold (exclusive).
    • max_value: Filters out pixels with values ≥ threshold (exclusive).
    • Filtering occurs before geometry creation in to_geodataframe(), significantly improving performance for sparse datasets.
    • Supports both single-band and multi-band rasters with consistent behavior.

  • Enhanced _build_data_mask() method: Extended to incorporate value threshold filtering alongside nodata filtering.

    • Combines multiple mask conditions using logical AND for efficient filtering.
    • Maintains backward compatibility when no thresholds are specified.

  • Enhanced _build_multi_band_mask() method: Extended for multi-band value filtering.

    • Drops pixels where ANY band has nodata or fails value thresholds.
    • Ensures consistent filtering behavior across RGB, RGBA, and multi-band modes.

• TifProcessor: Raster Statistics in get_raster_info()

  • Added include_statistics and approx_ok flags to optionally return pixel statistics alongside metadata.
  • New _get_basic_statistics() helper streams through raster blocks to compute per-band and overall min, max, mean, std, sum, and count with nodata-aware masking.
  • Results are cached for reuse within the processor lifecycle to avoid repeated scans.

• BaseHandler: Tabular Load Progress

  • _load_tabular_data() now supports a tqdm progress bar, showing file-level load progress for large tabular batches.
  • Added show_progress and progress_desc parameters so handlers can toggle or customize the indicator while keeping existing callers backward compatible.

• Improved developer usability by enabling easier access to primary components without deep module references:

  • Exposed core handlers, view generators, and processing modules at the top-level gigaspatial package namespace for improved user experience and simplified imports.
  • Added convenient aliases for gigaspatial.core.io as io and gigaspatial.processing.algorithms as algorithms directly accessible from gigaspatial.
  • Declared explicit public API in __init__.py to clarify stable, supported components.

Changed¶

• GHSLDataConfig: Improved SSL Certificate Handling for Tile Downloads

  • Replaced ssl._create_unverified_context approach with a robust two-tier fallback strategy for downloading GHSL tiles shapefile.

  • Primary method: Attempts download via gpd.read_file() with unverified SSL context (fast, direct access).

  • Fallback method: Uses requests.get() with verify=False for environments where gpd.read_file() fails (e.g., cloud compute instances with Anaconda certificate bundles).

  • Downloads tiles to temporary local file before reading when fallback is triggered, ensuring compatibility across different Python environments.

  • Tile caching: Implemented GeoJSON-based caching in base_path/cache/ directory to minimize redundant downloads.

    • Cache checked before any download attempts.
    • Invalid cache automatically triggers re-download.
    • Uses write_dataset() for consistent storage abstraction across local and remote data stores.

  • Enhanced error handling:

    • Logs specific exception types (type(e).__name__) for better debugging.
    • Graceful fallback with informative warning messages.
    • Preserves exception chain for traceback analysis.
  • Improved compatibility with Azure ML compute instances where multiple certificate stores (system, Anaconda, certifi) coexist.
  • Temporary file cleanup guaranteed via finally block, preventing orphaned downloads.

Fixed¶

• GHSLDataConfig: SSL certificate verification failures in cloud environments
  • Resolved CERTIFICATE_VERIFY_FAILED errors when downloading GHSL tiles shapefile on cloud compute instances.

Performance¶

• Reduced network overhead for GHSL tile metadata:
  • Tiles shapefile downloaded only once per coordinate system (WGS84/Mollweide) and cached locally.
  • Subsequent GHSLDataConfig instantiations load from cache, eliminating repeated ~MB shapefile downloads.
  • Benefits scale with number of GHSL queries across application lifecycle.

Documentation¶

• Improved README with clearer key workflows, core concepts, and updated overview text.

[v0.7.3] - 2025-11-11¶

Added¶

• SnowflakeDataStore Support

  • New SnowflakeDataStore class implementing the DataStore interface for Snowflake stages.
  • Supports file operations (read, write, list, delete) on Snowflake internal stages.
  • Integrated with gigaspatial/config.py for centralized configuration via environment variables.
  • Provides directory-like operations (mkdir, rmdir, walk, is_dir, is_file) for conceptual directories in Snowflake stages.
  • Includes context manager support and connection management.
  • Full compatibility with existing DataStore abstraction.

• BaseHandler: Config-Level Data Unit Caching

  • BaseHandlerConfig now maintains internal _unit_cache for data unit and geometry caching.
  • Cache stores tuples of (units, search_geometry) for efficient reuse across handler, downloader, and reader operations.
  • New methods:
    • get_cached_search_geometry(): Retrieve cached geometry for a source.
    • clear_unit_cache(): Clear cached data for testing or manual refreshes.
    • _cache_key(): Generate canonical cache keys from various source types.
  • Benefits all components (handler, downloader, reader) regardless of entry point.

• Unified Geometry Extraction in BaseHandlerConfig

  • New extract_search_geometry() method providing standardized geometry extraction from various source types:
    • Country codes (via AdminBoundaries)
    • Shapely geometries (BaseGeometry)
    • GeoDataFrames with automatic CRS handling
    • Lists of points or coordinate tuples (converted to MultiPoint)
  • Centralizes geometry conversion logic, eliminating duplication across handler methods.

• BaseHandler: Crop-to-Source Feature for Handlers

  • New crop_to_source parameter in BaseHandlerReader.load() and BaseHandler.load_data() methods.
  • Allows users to load data clipped to exact source boundaries rather than full data units (e.g., tiles).
  • Particularly useful for tile-based datasets (Google Open Buildings, GHSL) where tiles extend beyond requested regions.
  • Implemented crop_to_geometry() method in BaseHandlerReader for spatial filtering:
    • Supports (Geo)DataFrame clipping using geometry intersection.
    • Supports raster clipping using TifProcessor's clip_to_geometry method.
    • Extensible for future cropping implementations.
  • Search geometries are now cached alongside data units for efficient cropping operations.

• S2 Zonal View Generator (S2ViewGenerator)

  • New generator for producing zonal views using Google S2 cells (levels 0–30).
  • Supports sources:
    • Country name (str) via CountryS2Cells.create(...)
    • Shapely geometry or gpd.GeoDataFrame via S2Cells.from_spatial(...)
    • Points (List[Point | (lon, lat)]) via S2Cells.from_points(...)
    • Explicit cells (List[int | str], S2 IDs or tokens) via S2Cells.from_cells(...)
  • Uses cell_token as the zone identifier.
  • Includes map_wp_pop() convenience method (auto-uses stored country when available).

• H3 Zonal View Generator (H3ViewGenerator)

  • New generator for producing zonal views using H3 hexagons (resolutions 0–15).
  • Supports sources:
    • Country name (str) via CountryH3Hexagons.create(...)
    • Shapely geometry or gpd.GeoDataFrame via H3Hexagons.from_spatial(...)
    • Points (List[Point | (lon, lat)]) via H3Hexagons.from_spatial(...)
    • Explicit H3 indexes (List[str]) via H3Hexagons.from_hexagons(...)
  • Uses h3 as the zone identifier.
  • Includes map_wp_pop() convenience method (auto-uses stored country when available).

• TifProcessor: MultiPoint clipping support

  • _prepare_geometry_for_clipping() now accepts MultiPoint inputs and uses their bounding box for raster clipping.
  • Enables passing collections of points as a MultiPoint to clip_to_geometry() without pre-converting to a polygon.

Changed¶

• Configuration

  • Added Snowflake connection parameters to gigaspatial/config.py:
    • SNOWFLAKE_ACCOUNT, SNOWFLAKE_USER, SNOWFLAKE_PASSWORD
    • SNOWFLAKE_WAREHOUSE, SNOWFLAKE_DATABASE, SNOWFLAKE_SCHEMA
    • SNOWFLAKE_STAGE_NAME
  • Added Snowflake configuration variables to .env_sample

• BaseHandler

  • Streamlined Data Unit Resolution

    • Consolidated get_relevant_data_units_by_country(), get_relevant_data_units_by_points(), and get_relevant_data_units_by_geometry() into a unified workflow.
    • All source types now convert to geometry via extract_search_geometry() before unit resolution.
    • Subclasses now only need to implement get_relevant_data_units_by_geometry() for custom logic.
    • Significantly reduces code duplication in handler subclasses.

  • Optimized Handler Workflow

    • Eliminated redundant get_relevant_data_units() calls across handler, downloader, and reader operations.
    • ensure_data_available() now uses cached units and paths, preventing multiple lookups per request.
    • Data unit resolution occurs at most once per unique source query, improving performance for:
      • Repeated load_data() calls with the same source.
      • Operations involving both download and read steps.
      • Direct usage of downloader or reader components.

• Enhanced BaseHandlerReader

  • resolve_source_paths() now primarily handles explicit file paths.
  • Geometry/country/point conversion delegated to handler and config layers.
  • load() method updated to support crop_to_source parameter with automatic geometry retrieval from cache.
  • Fallback geometry computation if cache miss occurs (e.g., when reader used independently).

• BaseHandlerConfig Caching Logic

  • get_relevant_data_units() now checks cache before computing units.
  • Added force_recompute parameter to bypass cache when needed (e.g., force_download=True).
  • Cache operations include debug logging for transparency during development.

• TifProcessor temp-file handling

  • Simplified _create_clipped_processor() to mirror _reproject_to_temp_file: write clipped output to the new processor’s _temp_dir, set _clipped_file_path, update dataset_path, and reload metadata.
  • open_dataset() now prioritizes _merged_file_path, _reprojected_file_path, then _clipped_file_path, and opens local files directly.
  • Clipped processors consistently use LocalDataStore() for local temp files to avoid data-store path resolution issues.

Fixed¶

• TifProcessor: clip_to_geometry() open failure after merge
  • Fixed a bug where open_dataset() failed for processors returned by clip_to_geometry() when the source was initialized with multiple paths and loaded via handlers with merge_rasters=True.
  • The clipped raster is now saved directly into the new processor’s temp directory and tracked via _clipped_file_path, ensuring reliable access by open_dataset().
  • Absolute path checks in __post_init__ now use os.path.exists() for absolute paths with LocalDataStore, preventing false negatives for temp files.

Performance¶

• Significant reduction in redundant computations in handlers:
  • Single geometry extraction per source query (previously up to 3 times).
  • Single data unit resolution per source query (previously 2-3 times).
  • Cached geometry reuse for cropping operations.
  • Benefits scale with:
    • Number of repeated queries.
    • Complexity of geometry extraction (especially country boundaries).
    • Number of data units per query.

Developer Notes¶

• Subclass implementations should now:
  • Only override get_relevant_data_units_by_geometry() for custom unit resolution.
  • Use extract_search_geometry() for any geometry conversion needs.
  • Optionally override crop_to_geometry() for dataset-specific cropping logic.

Dependencies¶

• Added snowflake-connector-python>=3.0.0 as a new dependency

[v0.7.2] - 2025-10-27¶

Added¶

• Ookla Speedtest Handler Integration (OoklaSpeedtestHandler)

  • New classes OoklaSpeedtestHandler, OoklaSpeedtestConfig, OoklaSpeedtestDownloader, and OoklaSpeedtestReader for managing Ookla Speedtest data.
  • OoklaSpeedtestHandler.load_data method supports Mercator tile filtering by country or spatial geometry and includes an optional process_geospatial parameter for WKT to GeoDataFrame conversion.
  • In OoklaSpeedtestConfig, year and quarter fields are optional (defaulting to None) and __post_init__ logs warnings if they are not explicitly provided, using the latest available data.
  • In OoklaSpeedtestReader, resolve_source_paths method overridden to appropriately handle None or non-path sources by returning the DATASET_URL.
  • OoklaSpeedtestHandler, the __init__ method requires type as a mandatory argument, with year and quarter being optional.

• S2 Grid Generation Support (S2Cells)

  • Introduced S2Cells class for managing Google S2 cell grids using the s2sphere library.
  • Supports S2 levels 0-30, providing finer granularity than H3 (30 levels vs 15).
  • Provides multiple creation methods:
    • from_cells(): Create from lists of S2 cell IDs (integers or tokens).
    • from_bounds(): Create from geographic bounding box coordinates.
    • from_spatial(): Create from various spatial sources (geometries, GeoDataFrames, points).
    • from_json(): Load S2Cells from JSON files via DataStore.
  • Includes methods for spatial operations:
    • get_neighbors(): Get edge neighbors (4 per cell) with optional corner neighbors (8 total).
    • get_children(): Navigate to higher resolution child cells.
    • get_parents(): Navigate to lower resolution parent cells.
    • filter_cells(): Filter cells by a given set of cell IDs.
  • Provides conversion methods:
    • to_dataframe(): Convert to pandas DataFrame with cell IDs, tokens, and centroid coordinates.
    • to_geoms(): Convert cells to shapely Polygon geometries (square cells).
    • to_geodataframe(): Convert to GeoPandas GeoDataFrame with geometry column.
  • Supports saving to JSON, Parquet, or GeoJSON files via save() method.
  • Includes average_cell_area property for approximate area calculation based on S2 level.

• Country-Specific S2 Cells (CountryS2Cells)

  • Extends S2Cells for generating S2 grids constrained by country boundaries.
  • Integrates with AdminBoundaries to fetch country geometries for precise cell generation.
  • Factory method create() enforces proper instantiation with country code validation via pycountry.

• Expanded write_dataset to support generic JSON objects.

  • The write_dataset function can now write any serializable Python object (like a dict or list) directly to a .json file by leveraging the dedicated write_json helper.

• NASA SRTM Elevation Data Handler (NasaSRTMHandler)

  • New handler classes for downloading and processing NASA SRTM elevation data (30m and 90m resolution).
  • Supports Earthdata authentication via EARTHDATA_USERNAME and EARTHDATA_PASSWORD environment variables.
  • NasaSRTMConfig provides dynamic 1°x1° tile grid generation covering the global extent.
  • NasaSRTMDownloader supports parallel downloads of SRTM .hgt.zip tiles using multiprocessing.
  • NasaSRTMReader loads SRTM data with options to return as pandas DataFrame or list of SRTMParser objects.
  • Integrated with BaseHandler architecture for consistent data lifecycle management.

• SRTM Parser (SRTMParser)

  • Efficient parser for NASA SRTM .hgt.zip files using memory mapping.
  • Supports both SRTM-1 (3601x3601, 1 arc-second) and SRTM-3 (1201x1201, 3 arc-second) formats.
  • Provides methods for:
    • get_elevation(latitude, longitude): Get interpolated elevation for specific coordinates.
    • get_elevation_batch(coordinates): Batch elevation queries with NumPy array support.
    • to_dataframe(): Convert elevation data to pandas DataFrame with optional NaN filtering.
    • Automatic tile coordinate extraction from filename (e.g., N37E023, S10W120).

• SRTM Manager (SRTMManager)

  • Manager class for accessing elevation data across multiple SRTM tiles with lazy loading.
  • Implements LRU caching (default cache size: 10 tiles) for efficient memory usage.
  • Methods include:
    • get_elevation(latitude, longitude): Get interpolated elevation for any coordinate.
    • get_elevation_batch(coordinates): Batch elevation queries across multiple tiles.
    • get_elevation_profile(latitudes, longitudes): Generate elevation profiles along paths.
    • check_coverage(latitude, longitude): Check if a coordinate has SRTM coverage.
    • get_available_tiles(): List available SRTM tiles.
    • clear_cache() and get_cache_info(): Cache management utilities.
  • Automatically handles tile boundary crossings for elevation profiles.

• Earthdata Session (EarthdataSession)

  • Custom requests.Session subclass for NASA Earthdata authentication.
  • Maintains Authorization headers through redirects to/from Earthdata hosts.
  • Required for accessing NASA's SRTM data repository.

Changed¶

• ADLSDataStore Enhancements

  • Modified __init__ method to support initialization using either ADLS_CONNECTION_STRING or a combination of ADLS_ACCOUNT_URL and ADLS_SAS_TOKEN.
  • Improved flexibility for authenticating with Azure Data Lake Storage.

• Configuration

  • Added ADLS_ACCOUNT_URL and ADLS_SAS_TOKEN to gigaspatial/config.py and .env_sample for alternative ADLS authentication.
  • Added EARTHDATA_USERNAME and EARTHDATA_PASSWORD to gigaspatial/config.py and .env_sample for NASA Earthdata authentication.

Fixed¶

• WorldPop: RuntimeError during school_age=True data availability check:
  • Resolved a RuntimeError: Could not ensure data availability for loading that occurred when school_age=True and WorldPop data was not yet present in the data store.
  • WPPopulationConfig.get_data_unit_paths now correctly returns the original .zip URLs to trigger the download/extraction process when filtered .tif files are missing.
  • After successful download and extraction, it now accurately identifies and returns the paths to the local .tif files, allowing BaseHandler to confirm availability and proceed with loading.

• WorldPop: list index out of range when no datasets found:

  • Added a RuntimeError in WPPopulationConfig.get_relevant_data_units_by_country when self.client.search_datasets returns no results, providing a clearer error message with the search parameters.

• WorldPop: Incomplete downloads with min_age/max_age filters for non-school-age age_structures:

  • Fixed an issue where load_data with min_age or max_age filters (when school_age=False) resulted in incomplete downloads.
  • WPPopulationConfig.get_data_unit_paths now returns all potential .tif URLs for non-school-age age_structures during the initial availability check, ensuring all necessary files are downloaded.
  • Age/sex filtering is now deferred and applied by WPPopulationReader.load_from_paths using WPPopulationConfig._filter_age_sex_paths after download, guaranteeing data integrity.

• HealthSitesFetcher

  • Ensured correct Coordinate Reference System (CRS) assignment (EPSG:4326) when returning GeoDataFrame from fetched health facility data.

Dependencies¶

• Added s2sphere as a new dependency for S2 geometry operations

[v0.7.1] - 2025-10-15¶

Added¶

• Healthsites.io API Integration (HealthSitesFetcher):

  • New class HealthSitesFetcher to fetch and process health facility data from the Healthsites.io API.
  • Supports filtering by country, bounding box extent, and date ranges (from_date, to_date).
  • Provides methods for:
    • fetch_facilities(): Retrieves health facility locations, returning a pd.DataFrame or gpd.GeoDataFrame based on output format.
    • fetch_statistics(): Fetches aggregated statistics for health facilities based on provided filters.
    • fetch_facility_by_id(): Retrieves details for a specific facility using its OSM type and ID.
  • Includes robust handling for API pagination, different output formats (JSON, GeoJSON), and nested data structures.
  • Integrates with OSMLocationFetcher and pycountry to standardize country names to OSM English names for consistent querying.
  • Configurable parameters for API URL, API key, page size, flat properties, tag format, output format, and request sleep time.

• OSMLocationFetcher Enhancements:

  • Historical Data Fetching (fetch_locations_changed_between):
    • New method fetch_locations_changed_between() to retrieve OSM objects that were created or modified within a specified date range. This enables historical analysis and change tracking.
    • Defaults include_metadata to True for this method, as it's typically used for change tracking.
  • Comprehensive OSM Country Information (get_osm_countries):
    • New static method get_osm_countries() to fetch country-level administrative boundaries directly from the OSM database.
    • Supports fetching all countries or a specific country by ISO 3166-1 alpha-3 code.
    • Option to include various name variants (e.g., name:en, official_name) and ISO codes.
  • Metadata Inclusion in Fetched Locations:
    • Added include_metadata parameter to fetch_locations() to optionally retrieve change tracking metadata (timestamp, version, changeset, user, uid) for each fetched OSM element.
    • This metadata is now extracted and included in the DataFrame for nodes, relations, and ways.
  • Flexible Date Filtering in Overpass Queries:
    • Introduced date_filter_type (newer, changed) and start_date/end_date parameters to _build_queries() for more granular control over time-based filtering in Overpass QL.
  • Date Normalization Utility:
    • Added _normalize_date() helper method to convert various date inputs (string, datetime object) into a standardized ISO 8601 format for Overpass API queries.

• TifProcessor

  • Comprehensive Memory Management:
    • Introduced _check_available_memory(), _estimate_memory_usage(), and _memory_guard() methods for proactive memory assessment across various operations.
    • Added warnings (ResourceWarning) for potentially high memory usage in batched operations, with suggestions for optimizing n_workers.
  • Chunked DataFrame Conversion:
    • Implemented to_dataframe_chunked() for memory-efficient processing of large rasters by converting them to DataFrames in manageable chunks.
    • Automatic calculation of optimal chunk_size based on target memory usage via _calculate_optimal_chunk_size().
    • New helper methods: _get_chunk_windows(), _get_chunk_coordinates().
  • Raster Clipping Functionality:
    • clip_to_geometry(): New method to clip rasters to arbitrary geometries (Shapely, GeoDataFrame, GeoSeries, GeoJSON-like dicts).
    • clip_to_bounds(): New method to clip rasters to rectangular bounding boxes, supporting optional CRS transformation for the bounds.
    • New helper methods for clipping: _prepare_geometry_for_clipping(), _validate_geometry_crs(), _create_clipped_processor().

• WorldPopDownloader Zip Handling:

  • Modified download_data_unit in WPPopulationDownloader to correctly handle .zip files (e.g., school age datasets) by downloading them to a temporary location and extracting the contained .tif files.
  • Updated download_data_units to correctly flatten the list of paths returned by download_data_unit when zip extraction results in multiple files.
  • Adjusted WPPopulationConfig.get_data_unit_paths to correctly identify and return paths for extracted .tif files from zip resources. It is now intelligently resolves paths. For school-age datasets, it returns paths to extracted .tif files if available; otherwise, it returns the original .zip path(s) to trigger download and extraction.
  • Added filter support to WPPopulationConfig.get_data_unit_paths hence to the WPPopulationHandler for:
    • School-age datasets: supports sex (e.g., "F", "M", "F_M") and education_level (e.g., "PRIMARY", "SECONDARY") filters on extracted .tif filenames.
    • Non-school-age age_structures: supports sex, ages, min_age, and max_age filters on .tif filenames.

• WorldPop: Filtered aggregation in GeometryBasedZonalViewGenerator.map_wp_pop:

  • map_wp_pop now enforces a single country input when handler.config.project is "age_structures".
  • When predicate is "centroid_within" and the project is "age_structures", individual TifProcessor objects (representing age/sex combinations) are loaded, sampled with map_rasters(stat="sum"), and their results are summed per zone, preventing unintended merging.

• PoiViewGenerator: Filtered aggregation in PoiViewGenerator.map_wp_pop:

  • map_wp_pop now enforces a single country input when handler.config.project is "age_structures".
  • When predicate is "centroid_within" and the project is "age_structures", individual TifProcessor objects (representing age/sex combinations) are loaded, sampled with map_zonal_stats(stat="sum"), and their results are summed per POI, preventing unintended merging.

• TifProcessor Multi-Raster Merging in Handlers and Generators:

  • Extended _load_raster_data in BaseHandlerReader to support an optional merge_rasters argument. When True and multiple raster paths are provided, TifProcessor now merges them into a single TifProcessor object during loading.
  • Integrated merge_rasters argument into GHSLDataReader and WPPopulationReader's load_from_paths and load methods, enabling control over raster merging at the reader level.
  • Propagated merge_rasters to GHSLDataHandler's load_into_dataframe, and load_into_geodataframe methods for consistent behavior across the handler interface.

Changed¶

• TifProcessor

  • Unified DataFrame Conversion:
    • Refactored to_dataframe() to act as a universal entry point, dynamically routing to internal, more efficient methods for single and multi-band processing.
    • Deprecated the individual _to_band_dataframe(), _to_rgb_dataframe(), _to_rgba_dataframe(), and _to_multi_band_dataframe() methods in favor of the new unified _to_dataframe().
    • to_dataframe() now includes a check_memory parameter.
  • Optimized open_dataset Context Manager:
    • The open_dataset context manager now directly opens local files when LocalDataStore is used, avoiding unnecessary rasterio.MemoryFile creation for improved performance and reduced memory overhead.
  • Enhanced to_geodataframe and to_graph:
    • Added check_memory parameter to to_geodataframe() and to_graph() for memory pre-checks.
  • Refined sample_by_polygons_batched:
    • Included check_memory parameter for memory checks before batch processing.
    • Implemented platform-specific warnings for potential multiprocessing issues on Windows/macOS.
  • Improved Multiprocessing Initialization:
    • The _initializer_worker() method now prioritizes merged, reprojected, or original local file paths for opening, ensuring workers access the most relevant data.
  • Modular Masking and Coordinate Extraction:
    • Introduced new private helper methods: _extract_coordinates_with_mask(), _build_data_mask(), _build_multi_band_mask(), and _bands_to_dict() to centralize and improve data masking and coordinate extraction logic.
  • Streamlined Band-Mode Validation:
    • Moved the logic for validating mode and band count compatibility into a dedicated _validate_mode_band_compatibility() method for better code organization.

• GigaSchoolLocationFetcher

  • fetch_locations() method:
    • Added process_geospatial parameter (defaults to False) to optionally process geospatial data and return a gpd.GeoDataFrame.
  • _process_geospatial_data() method:
    • Modified to return a gpd.GeoDataFrame by converting the pd.DataFrame with a geometry column and EPSG:4326 CRS.

• OSMLocationFetcher Refactoring:

  • Unified Query Execution and Processing: Refactored the core logic for executing Overpass queries and processing their results into a new private method _execute_and_process_queries(). This centralizes common steps and reduces code duplication between fetch_locations() and the new fetch_locations_changed_between().
  • Enhanced _build_queries: Modified _build_queries to accept date_filter_type, start_date, end_date, and include_metadata to construct more dynamic and feature-rich Overpass QL queries.
  • Updated fetch_locations Signature:
    • Replaced since_year parameter with since_date (which can be a str or datetime object) for more precise time-based filtering.
    • Added include_metadata parameter.
  • Improved Logging of Category Distribution:
    • Modified the logging for category distribution to correctly handle cases where categories are combined into a list (when handle_duplicates='combine').
  • since_year Parameter: Removed since_year from fetch_locations() as its functionality is now superseded by the more flexible since_date parameter and the _build_queries enhancements.

• PoiViewGenerator Mapping Methods (map_zonal_stats, map_nearest_points, map_google_buildings, map_ms_buildings, map_built_s, map_smod):

  • Changed map_zonal_stats and map_nearest_points to return pd.DataFrame results (including 'poi_id' and new mapped columns) instead of directly updating the internal view.
  • Updated map_google_buildings, map_ms_buildings, map_built_s, and map_smod to capture the pd.DataFrame returned by their respective underlying mapping calls (map_nearest_points or map_zonal_stats) and then explicitly call self._update_view() with these results.
  • This enhances modularity and allows for more flexible result handling and accumulation.

• ZonalViewGenerator.map_rasters Enhancements:

  • Modified map_rasters to accept raster_data as either a single TifProcessor or a List[TifProcessor].
  • Implemented internal merging of List[TifProcessor] into a single TifProcessor before performing zonal statistics.
  • Replaced sample_multiple_tifs_by_polygons with the TifProcessor.sample_by_polygons method.

Fixed¶

• TifProcessor:
  • to_graph() Sparse Matrix Creation:
    • Corrected the sparse matrix creation logic in to_graph() to ensure proper symmetric graph representation when graph_type="sparse".
  • Coordinate System Handling in _initializer_worker:
    • Ensured that _initializer_worker correctly handles different data storage scenarios to provide the correct dataset handle to worker processes, preventing RuntimeError due to uninitialized raster datasets.

Removed¶

• OSMLocationFetcher
  • Redundant Category Distribution Logging: Removed the explicit category distribution logging for handle_duplicates == "separate" since the value_counts() method on the 'category' column already provides this.

[v0.7.0] - 2025-09-17¶

Added¶

• TifProcessor Revamp

  • Explicit Reprojection Method: Introduced reproject_to() method, allowing on-demand reprojection of rasters to a new CRS with customizable resampling_method and resolution.
  • Reprojection Resolution Control: Added reprojection_resolution parameter to TifProcessor for precise control over output pixel size during reprojection.
  • Advanced Raster Information: Added get_raster_info() method to retrieve a comprehensive dictionary of raster metadata.
  • Graph Conversion Capabilities: Implemented to_graph() method to convert raster data into a graph (NetworkX or sparse matrix) based on pixel adjacency (4- or 8-connectivity).
  • Internal Refactoring: _reproject_to_temp_file: Introduced _reproject_to_temp_file as a helper for reprojection into temporary files.

• H3 Grid Generation

  • H3 Grid Generation Module (gigaspatial/grid/h3.py):
    • Introduced H3Hexagons class for managing H3 cell IDs.
    • Supports creation from lists of hexagons, geographic bounds, spatial geometries, or points.
    • Provides methods to convert H3 hexagons to pandas DataFrames and GeoPandas GeoDataFrames.
    • Includes functionalities for filtering, getting k-ring neighbors, compacting hexagons, and getting children/parents at different resolutions.
    • Allows saving H3Hexagons to JSON, Parquet, or GeoJSON files.
  • Country-Specific H3 Hexagons (CountryH3Hexagons):
    • Extends H3Hexagons for generating H3 grids constrained by country boundaries.
    • Integrates with AdminBoundaries to fetch country geometries for precise H3 cell generation.

• Documentation

  • Improved tif.md example to showcase multi-raster initialization, explicit reprojection, and graph conversion.

Changed¶

• TifProcessor
• Improved Temporary File Management: Refactored temporary file handling for merging and reprojection using tempfile.mkdtemp() and shutil.rmtree for more robust and reliable cleanup. Integrated with context manager (__enter__, __exit__) and added a dedicated cleanup() method.
• Reprojection during Initialization: Implemented automatic reprojection of single rasters to a specified target_crs during TifProcessor initialization.
• Enhanced open_dataset Context Manager: The open_dataset context manager now intelligently opens the most up-to-date (merged or reprojected) version of the dataset.
• More Flexible Multi-Dataset Validation: Modified _validate_multiple_datasets to issue a warning instead of raising an error for CRS mismatches when target_crs is not set.

• Optimized _get_reprojection_profile: Dynamically calculates transform and dimensions based on reprojection_resolution and added LZW compression to reprojected TIFF files to reduce file size.

• ADLSDataStore Enhancements

  • New copy_file method: Implemented a new method for copying individual files within ADLS, with an option to overwrite existing files.
  • New rename method: Added a new method to rename (move) files in ADLS, which internally uses copy_file and then deletes the source, with options for overwrite, waiting for copy completion, and polling.
  • Revamped rmdir method: Modified rmdir to perform batch deletions of blobs, addressing the Azure Blob batch delete limit (256 sub-requests) and improving efficiency for large directories.

• LocalDataStore Enhancements

  • New copy_file method: Implemented a new method for copying individual files.

Removed¶

• Removed deprecated tabular property and get_zoned_geodataframe method from TifProcessor. Users should now use to_dataframe() and to_geodataframe() respectively.

Dependencies¶

• Added networkx and h3 as new dependencies.

Fixed¶

• Several small fixes and improvements to aggregation methods.

[v0.6.9] - 2025-07-26¶

Fixed¶

• Resolved a bug in the handler base class where non-hashable types (dicts) were incorrectly used as dictionary keys in unit_to_path mapping, preventing potential runtime errors during data availability checks.

[v0.6.8] - 2025-07-26¶

Added¶

• OSMLocationFetcher Enhancements
• Support for querying OSM locations by arbitrary administrative levels (e.g., states, provinces, cities), in addition to country-level queries.
• New optional parameters:
  • admin_level: Specify OSM administrative level (e.g., 4 for states, 6 for counties).
  • admin_value: Name of the administrative area to query (e.g., "California").

• New static method get_admin_names(admin_level, country=None):

  • Fetch all administrative area names for a given admin_level, optionally filtered by country.
  • Helps users discover valid admin area names for constructing precise queries.

• Multi-Raster Merging Support in TifProcessor

• Added ability to initialize TifProcessor with multiple raster datasets.
• Merges rasters on load with configurable strategies:
  • Supported merge_method options: first, last, min, max, mean.
• Supports on-the-fly reprojection for rasters with differing coordinate reference systems via target_crs.
• Handles resampling using resampling_method (default: nearest).
• Comprehensive validation to ensure compatibility of input rasters (e.g., resolution, nodata, dtype).
• Temporary file management for merged output with automatic cleanup.
• Backward compatible with single-raster use cases.

New TifProcessor Parameters: - merge_method (default: first) – How to combine pixel values across rasters. - target_crs (optional) – CRS to reproject rasters before merging. - resampling_method – Resampling method for reprojection.

New Properties: - is_merged: Indicates whether the current instance represents merged rasters. - source_count: Number of raster datasets merged.

Changed¶

• OSMLocationFetcher Overpass Query Logic
• Refactored Overpass QL query builder to support subnational queries using admin_level and admin_value.
• Improved flexibility and precision for spatial data collection across different administrative hierarchies.

Breaking Changes¶

• None. All changes are fully backward compatible.

[v0.6.7] - 2025-07-16¶

Fixed¶

• Fixed a bug in WorldPopHandler/ADLSDataStore integration where a Path object was passed instead of a string, causing a quote_from_bytes() expected bytes error during download.

[v0.6.6] - 2025-07-15¶

Added¶

• AdminBoundaries.from_global_country_boundaries(scale="medium")
• New class method to load global admin level 0 boundaries from Natural Earth.

• Supports "large" (10m), "medium" (50m), and "small" (110m) scale options.

• WorldPop Handler Refactor (API Integration)

• Introduced WPPopulationHandler, WPPopulationConfig, WPPopulationDownloader, and WPPopulationReader.
• Uses new WorldPopRestClient to dynamically query the WorldPop REST API.
• Replaces static metadata files and hardcoded logic with API-based discovery and download.
• Country code lookup and dataset filtering now handled at runtime.

• Improved validation, extensibility, logging, and error handling.

• POI-Based WorldPop Mapping

• PoiViewGenerator.map_wp_pop() method:

  • Maps WorldPop population data around POIs using flexible spatial predicates:
  • "centroid_within", "intersects", "fractional" (1000m only), "within"
  • Supports configurable radius and resolution (100m or 1000m).
  • Aggregates population data and appends it to the view.

• Geometry-Based Zonal WorldPop Mapping

• GeometryBasedZonalViewGenerator.map_wp_pop() method:
  • Maps WorldPop population data to polygons/zones using:
  • "intersects" or "fractional" predicate
  • Returns zonal population sums as a new view column.
  • Handles predicate-dependent data loading (raster vs. GeoDataFrame).

Changed¶

• Refactored BaseHandler.ensure_data_available
• More efficient data check and download logic.
• Downloads only missing units unless force_download=True.

• Cleaner structure and better reuse of get_relevant_data_units().

• Refactored WorldPop Module

• Complete handler redesign using API-based architecture.
• Dataset paths and URLs are now dynamically constructed from API metadata.
• Resolution/year validation is more robust and descriptive.
• Removed static constants, gender/school_age toggles, and local CSV dependency.

Fixed¶

• Several small fixes and improvements to zonal aggregation methods, especially around CRS consistency, missing values, and result alignment.

[v0.6.5] - 2025-07-01¶

Added¶

• MercatorTiles.get_quadkeys_from_points()
  New static method for efficient 1:1 point-to-quadkey mapping using coordinate-based logic, improving performance over spatial joins.

• AdminBoundariesViewGenerator
  New generator class for producing zonal views based on administrative boundaries (e.g., districts, provinces) with flexible source and admin level support.

• Zonal View Generator Enhancements

• _view: Internal attribute for accumulating mapped statistics.
• view: Exposes current state of zonal view.
• add_variable_to_view(): Adds mapped data from map_points, map_polygons, or map_rasters with robust validation and zone alignment.

• to_dataframe() and to_geodataframe() methods added for exporting current view in tabular or spatial formats.

• PoiViewGenerator Enhancements

• Consistent _view DataFrame for storing mapped results.
• _update_view(): Central method to update POI data.
• save_view(): Improved format handling (CSV, Parquet, GeoJSON, etc.) with geometry recovery.
• to_dataframe() and to_geodataframe() methods added for convenient export of enriched POI view.

• Robust duplicate ID detection and CRS validation in map_zonal_stats.

• TifProcessor Enhancements

• sample_by_polygons_batched(): Parallel polygon sampling.
• Enhanced sample_by_polygons() with nodata masking and multiple stats.

• warn_on_error: Flag to suppress sampling warnings.

• GeoTIFF Multi-Band Support

• multi mode added for multi-band raster support.
• Auto-detects band names via metadata.

• Strict validation of band count based on mode (single, rgb, rgba, multi).

• Spatial Distance Graph Algorithm

• build_distance_graph() added for fast KD-tree-based spatial matching.
• Supports both DataFrame and GeoDataFrame inputs.
• Outputs a networkx.Graph with optional DataFrame of matches.

• Handles projections, self-match exclusion, and includes verbose stats/logs.

• Database Integration (Experimental)

• Added DBConnection class in core/io/database.py for unified Trino and PostgreSQL access.
• Supports schema/table introspection, query execution, and reading into pandas or dask.
• Handles connection creation, credential management, and diagnostics.

• Utility methods for schema/view/table/column listings and parameterized queries.

• GHSL Population Mapping

• map_ghsl_pop() method added to GeometryBasedZonalViewGenerator.
• Aggregates GHSL population rasters to user-defined zones.
• Supports intersects and fractional predicates (latter for 1000m resolution only).
• Returns population statistics (e.g., sum) with customizable column prefix.

Changed¶

• MercatorTiles.from_points() now internally uses get_quadkeys_from_points() for better performance.

• map_points() and map_rasters() now return Dict[zone_id, value] to support direct usage with add_variable_to_view().

• Refactored aggregate_polygons_to_zones()

• area_weighted deprecated in favor of predicate.
• Supports flexible predicates like "within", "fractional" for spatial aggregation.

• map_polygons() updated to reflect this change.

• Optional Admin Boundaries Configuration

• ADMIN_BOUNDARIES_DATA_DIR is now optional.
• AdminBoundaries.create() only attempts to load if explicitly configured or path is provided.
• Improved documentation and fallback behavior for missing configs.

Fixed¶

• GHSL Downloader
• ZIP files are now downloaded into a temporary cache directory using requests.get().

• Avoids unnecessary writes and ensures cleanup.

• TifProcessor

• Removed polygon sampling warnings unless explicitly enabled.

Deprecated¶

• TifProcessor.tabular → use to_dataframe() instead.
• TifProcessor.get_zoned_geodataframe() → use to_geodataframe() instead.
• area_weighted → use predicate in aggregation methods instead.

[v0.6.4] - 2025-06-19¶

Added¶

• GigaSchoolProfileFetcher
• New class to fetch and process school profile data from the Giga School Profile API
• Supports paginated fetching, filtering by country and school ID

• Includes methods to generate connectivity summary statistics by region, connection type, and source

• GigaSchoolMeasurementsFetcher

• New class to fetch and process daily real-time connectivity measurements from the Giga API
• Supports filtering by date range and school

• Includes performance summary generation (download/upload speeds, latency, quality flags)

• AdminBoundaries.from_geoboundaries

• New class method to download and process geoBoundaries data by country and admin level

• Automatically handles HDX dataset discovery, downloading, and fallback logic

• HDXConfig.search_datasets

• Static method to search HDX datasets without full handler initialization
• Supports query string, sort order, result count, HDX site selection, and custom user agent

Fixed¶

• Typo in MaxarImageDownloader causing runtime error

Documentation¶

• Improved Configuration Guide (docs/user-guide/configuration.md)
• Added comprehensive table of environment variables with defaults and descriptions
• Synced .env_sample and config.py with docs
• Example .env file and guidance on path overrides using config.set_path
• New section on config.ensure_directories_exist and troubleshooting tips
• Clearer handling of credentials and security notes
• Improved formatting and structure for clarity

[v0.6.3] - 2025-06-16¶

Added¶

• Major refactor of HDX module to align with unified BaseHandler architecture:
• HDXConfig: fully aligned with BaseHandlerConfig structure.
• Added flexible pattern matching for resource filtering.
• Improved data unit resolution by country, geometry, and points.
• Enhanced resource filtering with exact and regex options.
• HDXDownloader fully aligned with BaseHandlerDownloader:
• Simplified sequential download logic.
• Improved error handling, validation, and logging.
• HDXReader fully aligned with BaseHandlerReader:
• Added resolve_source_paths and load_all_resources methods.
• Simplified source handling for single and multiple files.
• Cleaned up redundant and dataset-specific logic.

• Introduced HDXHandler as unified orchestration layer using factory methods.

• Refactor of RelativeWealthIndex (RWI) module:

• Added new RWIHandler class aligned with HDXHandler and BaseHandler.
• Simplified class names: RWIDownloader and RWIReader.
• Enhanced configuration with latest_only flag to select newest resources automatically.
• Simplified resource filtering and country resolution logic.

• Improved code maintainability, type hints, and error handling.

• New raster multi-band support in TifProcessor:

• Added new multi mode for handling multi-band raster datasets.
• Automatic band name detection from raster metadata.
• Added strict mode validation (single, rgb, rgba, multi).
• Enhanced error handling for invalid modes and band counts.

Fixed¶

• Fixed GHSL tiles loading behavior for correct coordinate system handling:
• Moved TILES_URL formatting and tile loading to validate_configuration.
• Ensures proper tile loading after CRS validation.

Documentation¶

• Updated and standardized API references across documentation.
• Standardized handler method names and usage examples.
• Added building enrichment examples for POI processing.
• Updated installation instructions.

Deprecated¶

• Deprecated direct imports from individual handler modules.

[v0.6.2] - 2025-06-11¶

Added¶

• New ROOT_DATA_DIR configuration option to set a base directory for all data tiers
• Can be configured via environment variable ROOT_DATA_DIR or .env file
• Defaults to current directory (.) if not specified
• All tier data paths (bronze, silver, gold, views) are now constructed relative to this root directory
• Example: Setting ROOT_DATA_DIR=/data/gigaspatial will store all data under /data/gigaspatial/bronze, /data/gigaspatial/silver, etc.

Fixed¶

• Fixed URL formatting in GHSL tiles by using Enum value instead of Enum member
• Ensures consistent URL formatting with numeric values (4326) instead of Enum names (WGS84)

• Fixes URL formatting issue across different Python environments

• Refactored GHSL downloader to follow DataStore abstraction

• Directory creation is now handled by DataStore implementation
• Removed redundant directory creation logic from download_data_unit method
• Improves separation of concerns and makes the code more maintainable

[v0.6.1] - 2025-06-09¶

Fixed¶

• Gracefully handle missing or invalid GeoRepo API key in AdminBoundaries.create():
• Wrapped GeoRepoClient initialization in a try-except block
• Added fallback to GADM if GeoRepo client fails
• Improved logging for better debugging and transparency

[v0.6.0] - 2025-06-09¶

Added¶

POI View Generator¶

• map_zonal_stats: New method for enriched spatial mapping with support for:
• Raster point sampling (value at POI location)
• Raster zonal statistics (with buffer zone)
• Polygon aggregation (with optional area-weighted averaging)
• Auto-generated POI IDs in _init_points_gdf for consistent point tracking.
• Support for area-weighted aggregation for polygon-based statistics.

BaseHandler Orchestration Layer¶

• New abstract BaseHandler class providing unified lifecycle orchestration for config, downloader, and reader.
• High-level interface methods:
• ensure_data_available()
• load_data()
• download_and_load()
• get_available_data_info()
• Integrated factory pattern for safe and standardized component creation.
• Built-in context manager support for resource cleanup.
• Fully backwards compatible with existing handler architecture.

Handlers Updated to Use BaseHandler¶

• GoogleOpenBuildingsHandler
• MicrosoftBuildingsHandler
• GHSLDataHandler
• All now inherit from BaseHandler, supporting standardized behavior and cleaner APIs.

Changed¶

POI View Generator¶

• map_built_s and map_smod now internally use the new map_zonal_stats method.
• tif_processors renamed to data to support both raster and polygon inputs.
• Removed parameters:
• id_column (now handled internally)
• area_column (now automatically calculated)

Internals and Usability¶

• Improved error handling with clearer validation messages.
• Enhanced logging for better visibility during enrichment.
• More consistent use of coordinate column naming.
• Refined type hints and parameter documentation across key methods.

Notes¶

• Removed legacy POI generator classes and redundant poi.py file.
• Simplified imports and removed unused handler dependencies.
• All POI generator methods now include updated docstrings, parameter explanations, and usage examples.
• Added docs on the new BaseHandler interface and handler refactors.

[v0.5.0] - 2025-06-02¶

Changed¶

• Refactored data loading architecture:
• Introduced dedicated reader classes for major datasets (Microsoft Global Buildings, Google Open Buildings, GHSL), each inheriting from a new BaseHandlerReader.
• Centralized file existence checks and raster/tabular loading methods in BaseHandlerReader.

• Improved maintainability by encapsulating dataset-specific logic inside each reader class.

• Modularized source resolution:

• Each reader now supports resolving data by country, geometry, or individual points, improving code reuse and flexibility.

• Unified POI enrichment:

• Merged all POI generators (Google Open Buildings, Microsoft Global Buildings, GHSL Built Surface, GHSL SMOD) into a single PoiViewGenerator class.
• Supports flexible inputs: list of (lat, lon) tuples, list of dicts, DataFrame, or GeoDataFrame.
• Maintains consistent internal state via points_gdf, updated after each mapping.

• Enables chained enrichment of POI data using multiple datasets.

• Modernized internal data access:

• All data loading now uses dedicated handler/reader classes, improving consistency and long-term maintainability.

Fixed¶

• Full DataStore integration:
• Fixed OpenCellID and HDX handlers to fully support the DataStore abstraction.
• All file reads, writes, and checks now use the configured DataStore (local or cloud).
• Temporary files are only used during downloads; final data is always stored and accessed via the DataStore interface.

Removed¶

• Removed deprecated POI generator classes and the now-obsolete poi submodule. All enrichment is handled through the unified PoiViewGenerator.

Notes¶

• This release finalizes the architectural refactors started in v0.5.0.
• While marked stable, please report any issues or regressions from the new modular structure.

[v0.5.0b1] - 2025-05-27¶

Added¶

• New Handlers:
• hdx.py: Handler for downloading and managing Humanitarian Data Exchange datasets.
• rwi.py: Handler for the Relative Wealth Index dataset.
• opencellid.py: Handler for OpenCellID tower locations.
• unicef_georepo.py: Integration with UNICEF’s GeoRepo asset repository.
• Zonal Generators:
• Introduced the generators/zonal/ module to support spatial aggregations of various data types (points, polygons, rasters) to zonal geometries such as grid tiles or catchment areas.
• New Geo-Processing Methods:
• Added methods to compute centroids of (Multi)Polygon geometries.
• Added methods to calculate area of (Multi)Polygon geometries in square meters.

Changed¶

• Refactored:
• config.py: Added support for new environment variables (OpenCellID and UNICEF GeoRepo keys).
• geo.py: Enhanced spatial join functions for improved performance and clarity.
• handlers/:
  • Minor robustness improvements in google_open_buildings and microsoft_global_buildings.
  • Added a new class method in boundaries for initializing admin boundaries from UNICEF GeoRepo.
• core/io/:
  • Added list_directories method to both ADLS and local storage backends.
• Documentation & Project Structure:
• Updated .env_sample and .gitignore to align with new environment variables and data handling practices.

Dependencies¶

• Updated requirements.txt and setup.py to reflect new dependencies and ensure compatibility.

Notes¶

• This is a pre-release (v0.5.0b1) and is intended for testing and feedback.
• Some new modules, especially in handlers and generators, are experimental and may be refined in upcoming releases.

[v0.4.1] - 2025-04-17¶

Added¶

• Documentation:
  • Added API Reference documentation for all modules, classes, and functions.
  • Added a Configuration Guide to explain how to set up paths, API keys, and other.
• TifProcessor: added new to_dataframe method.
• config: added set_path method for dynamic path management.

Changed¶

• Documentation:
  • Restructured the docs/ directory to improve organization and navigation.
  • Updated the index.md for the User Guide to provide a clear overview of available documentation.
  • Updated Examples for downloading, processing, and storing geospatial data - more to come.
• README:
  • Updated the README with a clear description of the package’s purpose and key features.
  • Added a section on View Generators to explain spatial context enrichment and mapping to grid or POI locations.
  • Included a Supported Datasets section with an image of dataset provider logos.

Fixed¶

• Handled errors when processing nodes, relations, and ways in OSMLocationFetcher.
• Made admin1 and admin1_id_giga optional in GigaEntity instances for countries with no admin level 1 divisions.

[v0.4.0] - 2025-04-01¶

Added¶

• POI View Generators: Introduced a new module, generators, containing a base class for POI view generation.
• Expanded POI Support: Added new classes for generating POI views from:
  • Google Open Buildings
  • Microsoft Global Buildings
  • GHSL Settlement Model
  • GHSL Built Surface
• New Reader: Added read_gzipped_json_or_csv to handle compressed JSON/CSV files.

Changed¶

• ADLSDataStore Enhancements: Updated methods to match LocalDataStore for improved consistency.
• Geo Processing Updates:
  • Improved convert_to_dataframe for more efficient data conversion.
  • Enhanced annotate_with_admin_regions to improve spatial joins.
• New TifProcessor Methods:
  • sample_by_polygons for polygon-based raster sampling.
  • sample_multiple_tifs_by_coordinates & sample_multiple_tifs_by_polygons to manage multi-raster sampling.
• Fixed Global Config Handling: Resolved issues with handling configurations inside classes.

[v0.3.2] - 2025-03-21¶

Added¶

• Added a method to efficiently assign unique IDs to features.

Changed¶

• Enhanced logging for better debugging and clarity.

Fixed¶

• Minor bug fix in config.py

[0.3.1] - 2025-03-20¶

Added¶

• Enhanced AdminBoundaries handler with improved error handling for cases where administrative level data is unavailable for a country.
• Added pyproject.toml and setup.py, enabling pip install support for the package.
• Introduced a new method annotate_with_admin_regions in geo.py to perform spatial joins between input points and administrative boundaries (levels 1 and 2), handling conflicts where points intersect multiple admin regions.

Removed¶

• Removed the utils module containing logger.py and integrated LOG_FORMAT and get_logger into config.py for a more streamlined logging approach.

[0.3.0] - 2025-03-18¶

Added¶

• Compression support in readers for improved efficiency
• New GHSL data handler to manage GHSL dataset downloads

Fixed¶

• Small fixes/improvements in Microsoft Buildings, Maxar, and Overture handlers

[v0.2.2] - 2025-03-12¶

• Refactored Handlers: Improved structure and performance of maxar_image.py, osm.py and overture.py to enhance geospatial data handling.

• Documentation Improvements:

  • Updated index.md, advanced.md, and use-cases.md for better clarity.
  • Added installation.md under docs/getting-started for setup guidance.
  • Refined API documentation in docs/api/index.md.

• Configuration & Setup Enhancements: • Improved .gitignore to exclude unnecessary files. • Updated mkdocs.yml for better documentation structuring.

• Bug Fixes & Minor Optimizations: Small fixes and improvements across the codebase for stability and maintainability.

[v0.2.1] - 2025-02-28¶

Added¶

• Introduced WorldPopDownloader feature to handlers
• Refactored TifProcessor class for better performance

Fixed¶

• Minor bug fixes and performance improvements

[v0.2.0] - MaxarImageDownloader & Bug Fixes - 2025-02-24¶

• New Handler: MaxarImageDownloader for downloading Maxar images.
• Bug Fixes: Various improvements and bug fixes.
• Enhancements: Minor optimizations in handlers.

[v0.1.1] - 2025-02-24¶

Added¶

• Local Data Store: Introduced a new local data store alongside ADLS to improve data storage and read/write functionality.
• Boundaries Handler: Added boundaries.py, a new handler that allows to read administrative boundaries from GADM.

Changed¶

• Handler Refactoring: Refactored existing handlers to improve modularity and data handling.
• Configuration Management: Added config.py to manage paths, runtime settings, and environment variables.

Removed¶

• Administrative Schema: Removed administrative.py since its functionality is now handled by the boundaries handler.
• Globals Module: Removed globals.py and replaced it with config.py for better configuration management.

Updated Files¶

• config.py
• boundaries.py
• google_open_buildings.py
• mapbox_image.py
• microsoft_global_buildings.py
• ookla_speedtest.py
• mercator_tiles.py
• adls_data_store.py
• data_store.py
• local_data_store.py
• readers.py
• writers.py
• entity.py

[v0.1.0] - 2025-02-07¶

Added¶

• New data handlers: google_open_buildings.py, microsoft_global_buildings.py, overture.py, mapbox_image.py, osm.py
• Processing functions in tif_processor.py, geo.py and transform.py
• Grid generation modules: h3_tiles.py, mercator_tiles.py
• View managers: grid_view.py and national_view.py
• Schemas: administrative.py

Changed¶

• Updated requirements.txt with new dependencies
• Improved logging and data storage mechanisms

Removed¶

• Deprecated views: h3_view.py, mercator_view.py