Models

Crown

Bases: Base

Represents the delineated polygon boundaries associated with specific tree anchors.

Attributes:

Name	Type	Description
objectid	int	Primary key, auto-incrementing integer identifier.
crown_id	str	Unique, non-nullable string identifier for the crown polygon.
tree_id	str	Foreign key linking to the parent Tree's tree_id. Non-nullable, cascades on delete.
crown_category	str	Categorical designation of the crown generation approach ('Manual' or 'Automated'). Non-nullable.
generation_method	str	Algorithm or methodology used for automated delineation (if applicable).
source_lidar_id	int	Foreign key linking to the originating LidarAcquisition. Sets to NULL on delete.
source_image_id	int	Foreign key linking to the originating ImageAcquisition. Sets to NULL on delete.
geom	NativeGeometry	Custom spatial type for the crown polygon geometry, spatially indexed.
created_at	datetime	Timestamp of record creation, defaults to current UTC time.

Constraints

chk_crown_category: Ensures crown_category is strictly either 'Manual' or 'Automated'. chk_automated_method: Ensures generation_method is populated if crown_category is 'Automated'. chk_source_exists: Ensures that manual crowns do not require a source, but automated or generated crowns must link to at least one LiDAR or image source.

Relationships

tree (Tree): The master tree anchor point associated with this crown boundary. lidar_acquisition (LidarAcquisition): The LiDAR dataset used to delineate or inform this crown polygon. image_acquisition (ImageAcquisition): The imagery dataset used to delineate or inform this crown polygon. spectral_attributes (list[SpectralAttribute]): Associated spectral metrics. Cascade deletes orphans. structural_attributes (list[StructuralAttribute]): Associated geometric metrics. Cascade deletes orphans.

Source code in src/phytospatial/db/models.py

class Crown(Base):
    """
    Represents the delineated polygon boundaries associated with specific tree anchors.

    Attributes:
        objectid (int): Primary key, auto-incrementing integer identifier.
        crown_id (str): Unique, non-nullable string identifier for the crown polygon.
        tree_id (str): Foreign key linking to the parent Tree's tree_id. Non-nullable, cascades on delete.
        crown_category (str): Categorical designation of the crown generation approach ('Manual' or 'Automated'). Non-nullable.
        generation_method (str): Algorithm or methodology used for automated delineation (if applicable).
        source_lidar_id (int): Foreign key linking to the originating LidarAcquisition. Sets to NULL on delete.
        source_image_id (int): Foreign key linking to the originating ImageAcquisition. Sets to NULL on delete.
        geom (NativeGeometry): Custom spatial type for the crown polygon geometry, spatially indexed.
        created_at (datetime.datetime): Timestamp of record creation, defaults to current UTC time.

    Constraints:
        chk_crown_category: Ensures `crown_category` is strictly either 'Manual' or 'Automated'.
        chk_automated_method: Ensures `generation_method` is populated if `crown_category` is 'Automated'.
        chk_source_exists: Ensures that manual crowns do not require a source, but automated or generated crowns must link to at least one LiDAR or image source.

    Relationships:
        tree (Tree): The master tree anchor point associated with this crown boundary.
        lidar_acquisition (LidarAcquisition): The LiDAR dataset used to delineate or inform this crown polygon.
        image_acquisition (ImageAcquisition): The imagery dataset used to delineate or inform this crown polygon.
        spectral_attributes (list[SpectralAttribute]): Associated spectral metrics. Cascade deletes orphans.
        structural_attributes (list[StructuralAttribute]): Associated geometric metrics. Cascade deletes orphans.
    """
    __tablename__ = 'crowns'

    objectid = Column(Integer, primary_key=True, autoincrement=True)
    crown_id = Column(String(255), unique=True, nullable=False)
    tree_id = Column(String(255), ForeignKey('trees.tree_id', ondelete='CASCADE'), nullable=False)
    crown_category = Column(String(50), nullable=False)
    generation_method = Column(String(255))
    source_lidar_id = Column(Integer, ForeignKey('lidar_acquisitions.id', ondelete='SET NULL'))
    source_image_id = Column(Integer, ForeignKey('image_acquisitions.id', ondelete='SET NULL'))
    geom = Column(NativeGeometry('POLYGON', 32619))
    created_at = Column(DateTime(timezone=True), default=datetime.datetime.utcnow)

    __table_args__ = (
        CheckConstraint(
            "crown_category IN ('Manual', 'Automated')",
            name='chk_crown_category'
        ),
        CheckConstraint(
            "(crown_category = 'Manual') OR (crown_category = 'Automated' AND generation_method IS NOT NULL)",
            name='chk_automated_method'
        ),
        CheckConstraint(
            "(crown_category = 'Manual') OR (source_lidar_id IS NOT NULL OR source_image_id IS NOT NULL)",
            name='chk_source_exists'
        ),
    )

    tree = relationship("Tree", back_populates="crowns")
    lidar_acquisition = relationship("LidarAcquisition", back_populates="crowns")
    image_acquisition = relationship("ImageAcquisition", back_populates="crowns")
    spectral_attributes = relationship("SpectralAttribute", back_populates="crown", cascade="all, delete-orphan")
    structural_attributes = relationship("StructuralAttribute", back_populates="crown", cascade="all, delete-orphan")

ImageAcquisition

Bases: Base

Registers foundational metadata for multispectral and hyperspectral raster acquisitions.

Attributes:

Name	Type	Description
id	int	Primary key, auto-incrementing integer identifier.
acquisition_datetime	datetime	Non-nullable timestamp of when the imagery was acquired.
sensor_type	str	Specifications or model of the imaging sensor used.
gsd_cm	float	Ground Sample Distance represented in centimeters per pixel.

Relationships

bands (list[ImageBand]): Collection of specific spectral bands recorded during this acquisition. Cascade deletes orphans. spectral_attributes (list[SpectralAttribute]): Collection of spectral metrics extracted from this image acquisition. crowns (list[Crown]): Collection of crown polygons generated or validated using this image acquisition.

Source code in src/phytospatial/db/models.py

class ImageAcquisition(Base):
    """
    Registers foundational metadata for multispectral and hyperspectral raster acquisitions.

    Attributes:
        id (int): Primary key, auto-incrementing integer identifier.
        acquisition_datetime (datetime.datetime): Non-nullable timestamp of when the imagery was acquired.
        sensor_type (str): Specifications or model of the imaging sensor used.
        gsd_cm (float): Ground Sample Distance represented in centimeters per pixel.

    Relationships:
        bands (list[ImageBand]): Collection of specific spectral bands recorded during this acquisition. Cascade deletes orphans.
        spectral_attributes (list[SpectralAttribute]): Collection of spectral metrics extracted from this image acquisition.
        crowns (list[Crown]): Collection of crown polygons generated or validated using this image acquisition.
    """
    __tablename__ = 'image_acquisitions'

    id = Column(Integer, primary_key=True, autoincrement=True)
    acquisition_datetime = Column(DateTime(timezone=True), nullable=False)
    sensor_type = Column(String(255))
    gsd_cm = Column(Float)

    bands = relationship("ImageBand", back_populates="image_acquisition", cascade="all, delete-orphan")
    spectral_attributes = relationship("SpectralAttribute", back_populates="image_acquisition")
    crowns = relationship("Crown", back_populates="image_acquisition")

ImageBand

Bases: Base

Defines individual spectral bands associated with specific image acquisitions.

Attributes:

Name	Type	Description
id	int	Primary key, auto-incrementing integer identifier.
image_acquisition_id	int	Foreign key linking to the parent ImageAcquisition. Non-nullable, cascades on delete.
band_index	int	The sequential index or channel number of the band within the raster dataset. Non-nullable.
wavelength_nm	float	The central wavelength of the band measured in nanometers. Non-nullable.
band_name	str	The common name or designation of the band.

Relationships

image_acquisition (ImageAcquisition): The parent multispectral or hyperspectral acquisition event.

Source code in src/phytospatial/db/models.py

class ImageBand(Base):
    """
    Defines individual spectral bands associated with specific image acquisitions.

    Attributes:
        id (int): Primary key, auto-incrementing integer identifier.
        image_acquisition_id (int): Foreign key linking to the parent ImageAcquisition. Non-nullable, cascades on delete.
        band_index (int): The sequential index or channel number of the band within the raster dataset. Non-nullable.
        wavelength_nm (float): The central wavelength of the band measured in nanometers. Non-nullable.
        band_name (str): The common name or designation of the band.

    Relationships:
        image_acquisition (ImageAcquisition): The parent multispectral or hyperspectral acquisition event.
    """
    __tablename__ = 'image_bands'

    id = Column(Integer, primary_key=True, autoincrement=True)
    image_acquisition_id = Column(Integer, ForeignKey('image_acquisitions.id', ondelete='CASCADE'), nullable=False)
    band_index = Column(Integer, nullable=False)
    wavelength_nm = Column(Float, nullable=False)
    band_name = Column(String(255))

    image_acquisition = relationship("ImageAcquisition", back_populates="bands")

JSONVariant

Bases: TypeDecorator

Dynamically abstracts JSON column typing to support both PostgreSQL JSONB and SQLite VARCHAR serialization.

Source code in src/phytospatial/db/models.py

class JSONVariant(TypeDecorator):
    """
    Dynamically abstracts JSON column typing to support both PostgreSQL JSONB and SQLite VARCHAR serialization.
    """
    impl = VARCHAR
    cache_ok = True

    def load_dialect_impl(
            self, 
            dialect: Any
            ) -> Any:
        """
        Provisions the appropriate SQL type descriptor based on the active database engine dialect.

        Args:
            dialect (Any): The active SQLAlchemy execution dialect.

        Returns:
            Any: The dialect-specific column type implementation.
        """
        if dialect.name == 'postgresql':
            return dialect.type_descriptor(JSONB())
        return dialect.type_descriptor(VARCHAR())

    def process_bind_param(
            self, 
            value: Dict[str, Any], 
            dialect: Any
            ) -> Any:
        """
        Serializes dictionary payloads into dialect-compatible formats during database insertion.

        Args:
            value (Dict[str, Any]): The target dictionary payload.
            dialect (Any): The active SQLAlchemy execution dialect.

        Returns:
            Any: The serialized payload ready for database insertion.
        """
        if value is None:
            return value
        if dialect.name == 'postgresql':
            return value
        import json
        return json.dumps(value)

    def process_result_value(
            self, 
            value: Any, 
            dialect: Any
            ) -> Any:
        """
        Deserializes dialect-specific strings or binaries back into Python dictionaries during retrieval.

        Args:
            value (Any): The raw data retrieved from the database.
            dialect (Any): The active SQLAlchemy execution dialect.

        Returns:
            Dict[str, Any]: The parsed dictionary payload.
        """
        if value is None:
            return None
        if dialect.name == 'postgresql':
            return value
        import json
        return json.loads(value)

load_dialect_impl(dialect)

Provisions the appropriate SQL type descriptor based on the active database engine dialect.

Parameters:

Name	Type	Description	Default
dialect	Any	The active SQLAlchemy execution dialect.	required

Returns:

Name	Type	Description
Any	Any	The dialect-specific column type implementation.

Source code in src/phytospatial/db/models.py

def load_dialect_impl(
        self, 
        dialect: Any
        ) -> Any:
    """
    Provisions the appropriate SQL type descriptor based on the active database engine dialect.

    Args:
        dialect (Any): The active SQLAlchemy execution dialect.

    Returns:
        Any: The dialect-specific column type implementation.
    """
    if dialect.name == 'postgresql':
        return dialect.type_descriptor(JSONB())
    return dialect.type_descriptor(VARCHAR())

process_bind_param(value, dialect)

Serializes dictionary payloads into dialect-compatible formats during database insertion.

Parameters:

Name	Type	Description	Default
value	Dict[str, Any]	The target dictionary payload.	required
dialect	Any	The active SQLAlchemy execution dialect.	required

Returns:

Name	Type	Description
Any	Any	The serialized payload ready for database insertion.

Source code in src/phytospatial/db/models.py

def process_bind_param(
        self, 
        value: Dict[str, Any], 
        dialect: Any
        ) -> Any:
    """
    Serializes dictionary payloads into dialect-compatible formats during database insertion.

    Args:
        value (Dict[str, Any]): The target dictionary payload.
        dialect (Any): The active SQLAlchemy execution dialect.

    Returns:
        Any: The serialized payload ready for database insertion.
    """
    if value is None:
        return value
    if dialect.name == 'postgresql':
        return value
    import json
    return json.dumps(value)

process_result_value(value, dialect)

Deserializes dialect-specific strings or binaries back into Python dictionaries during retrieval.

Parameters:

Name	Type	Description	Default
value	Any	The raw data retrieved from the database.	required
dialect	Any	The active SQLAlchemy execution dialect.	required

Returns:

Type	Description
Any	Dict[str, Any]: The parsed dictionary payload.

Source code in src/phytospatial/db/models.py

def process_result_value(
        self, 
        value: Any, 
        dialect: Any
        ) -> Any:
    """
    Deserializes dialect-specific strings or binaries back into Python dictionaries during retrieval.

    Args:
        value (Any): The raw data retrieved from the database.
        dialect (Any): The active SQLAlchemy execution dialect.

    Returns:
        Dict[str, Any]: The parsed dictionary payload.
    """
    if value is None:
        return None
    if dialect.name == 'postgresql':
        return value
    import json
    return json.loads(value)

LidarAcquisition

Bases: Base

Registers foundational metadata for raw LiDAR point cloud acquisitions.

Attributes:

Name	Type	Description
id	int	Primary key, auto-incrementing integer identifier.
acquisition_datetime	datetime	Non-nullable timestamp of when the LiDAR data was acquired.
sensor_type	str	Specifications or model of the LiDAR sensor used.
point_density_m2	float	Average points per square meter captured during the flight.
number_of_returns	int	Maximum number of returns recorded per pulse.

Relationships

structural_attributes (list[StructuralAttribute]): Collection of structural metrics derived from this LiDAR acquisition. crowns (list[Crown]): Collection of crown polygons generated or validated using this LiDAR acquisition.

Source code in src/phytospatial/db/models.py

class LidarAcquisition(Base):
    """
    Registers foundational metadata for raw LiDAR point cloud acquisitions.

    Attributes:
        id (int): Primary key, auto-incrementing integer identifier.
        acquisition_datetime (datetime.datetime): Non-nullable timestamp of when the LiDAR data was acquired.
        sensor_type (str): Specifications or model of the LiDAR sensor used.
        point_density_m2 (float): Average points per square meter captured during the flight.
        number_of_returns (int): Maximum number of returns recorded per pulse.

    Relationships:
        structural_attributes (list[StructuralAttribute]): Collection of structural metrics derived from this LiDAR acquisition.
        crowns (list[Crown]): Collection of crown polygons generated or validated using this LiDAR acquisition.
    """
    __tablename__ = 'lidar_acquisitions'

    id = Column(Integer, primary_key=True, autoincrement=True)
    acquisition_datetime = Column(DateTime(timezone=True), nullable=False)
    sensor_type = Column(String(255))
    point_density_m2 = Column(Float)
    number_of_returns = Column(Integer)

    structural_attributes = relationship("StructuralAttribute", back_populates="lidar_acquisition")
    crowns = relationship("Crown", back_populates="lidar_acquisition")

NativeGeometry

Bases: UserDefinedType

A custom SQLAlchemy type for defining spatial columns without external dependencies.

This class bypasses ORM-level geometry serialization, falling back to standard geometry declarations for databases like PostGIS and SpatiaLite. It relies on the database engine to natively parse Extended Well-Known Binary (EWKB) hex strings.

Source code in src/phytospatial/db/models.py

class NativeGeometry(UserDefinedType):
    """
    A custom SQLAlchemy type for defining spatial columns without external dependencies.

    This class bypasses ORM-level geometry serialization, falling back to standard 
    geometry declarations for databases like PostGIS and SpatiaLite. It relies on 
    the database engine to natively parse Extended Well-Known Binary (EWKB) hex strings.
    """

    def __init__(
            self, 
            geometry_type: str = 'GEOMETRY', 
            srid: int = 32619
            ) -> None:
        """
        Initializes the NativeGeometry type.

        Args:
            geometry_type (str): The specific geometry type ('POINT', 'POLYGON', etc.).
            srid (int): The spatial reference identifier.
        """
        self.geometry_type = geometry_type.upper()
        self.srid = srid

    def get_col_spec(
            self, 
            **kw: Any
            ) -> str:
        """
        Generates the column specification for DDL compilation.

        Args:
            **kw (Any): Additional keyword arguments passed by the SQLAlchemy compiler.

        Returns:
            str: The SQL column type definition.
        """
        return f"geometry({self.geometry_type}, {self.srid})"

    def bind_processor(
            self, 
            dialect: Any
            ) -> Any:
        """
        Processes the bound parameter before execution.

        Args:
            dialect (Any): The active database dialect.

        Returns:
            Any: A processor function that returns the value unmodified, relying on 
            native database EWKB hex casting.
        """
        def process(value: Optional[str]) -> Optional[str]:
            return value
        return process

    def result_processor(
            self, 
            dialect: Any, 
            coltype: Any
            ) -> Any:
        """
        Processes the result value retrieved from the database.

        Args:
            dialect (Any): The active database dialect.
            coltype (Any): The column type.

        Returns:
            Any: A processor function that returns the raw WKB/EWKB hex string.
        """
        def process(value: Optional[Any]) -> Optional[Any]:
            return value
        return process

__init__(geometry_type='GEOMETRY', srid=32619)

Initializes the NativeGeometry type.

Parameters:

Name	Type	Description	Default
geometry_type	str	The specific geometry type ('POINT', 'POLYGON', etc.).	'GEOMETRY'
srid	int	The spatial reference identifier.	32619

Source code in src/phytospatial/db/models.py

def __init__(
        self, 
        geometry_type: str = 'GEOMETRY', 
        srid: int = 32619
        ) -> None:
    """
    Initializes the NativeGeometry type.

    Args:
        geometry_type (str): The specific geometry type ('POINT', 'POLYGON', etc.).
        srid (int): The spatial reference identifier.
    """
    self.geometry_type = geometry_type.upper()
    self.srid = srid

bind_processor(dialect)

Processes the bound parameter before execution.

Parameters:

Name	Type	Description	Default
dialect	Any	The active database dialect.	required

Returns:

Name	Type	Description
Any	Any	A processor function that returns the value unmodified, relying on
	Any	native database EWKB hex casting.

Source code in src/phytospatial/db/models.py

def bind_processor(
        self, 
        dialect: Any
        ) -> Any:
    """
    Processes the bound parameter before execution.

    Args:
        dialect (Any): The active database dialect.

    Returns:
        Any: A processor function that returns the value unmodified, relying on 
        native database EWKB hex casting.
    """
    def process(value: Optional[str]) -> Optional[str]:
        return value
    return process

get_col_spec(**kw)

Generates the column specification for DDL compilation.

Parameters:

Name	Type	Description	Default
**kw	Any	Additional keyword arguments passed by the SQLAlchemy compiler.	{}

Returns:

Name	Type	Description
str	str	The SQL column type definition.

Source code in src/phytospatial/db/models.py

def get_col_spec(
        self, 
        **kw: Any
        ) -> str:
    """
    Generates the column specification for DDL compilation.

    Args:
        **kw (Any): Additional keyword arguments passed by the SQLAlchemy compiler.

    Returns:
        str: The SQL column type definition.
    """
    return f"geometry({self.geometry_type}, {self.srid})"

result_processor(dialect, coltype)

Processes the result value retrieved from the database.

Parameters:

Name	Type	Description	Default
dialect	Any	The active database dialect.	required
coltype	Any	The column type.	required

Returns:

Name	Type	Description
Any	Any	A processor function that returns the raw WKB/EWKB hex string.

Source code in src/phytospatial/db/models.py

def result_processor(
        self, 
        dialect: Any, 
        coltype: Any
        ) -> Any:
    """
    Processes the result value retrieved from the database.

    Args:
        dialect (Any): The active database dialect.
        coltype (Any): The column type.

    Returns:
        Any: A processor function that returns the raw WKB/EWKB hex string.
    """
    def process(value: Optional[Any]) -> Optional[Any]:
        return value
    return process

SpectralAttribute

Bases: Base

Stores analytical metrics extracted from raster overlays mapped to specific crowns.

Attributes:

Name	Type	Description
objectid	int	Primary key, auto-incrementing integer identifier.
crown_id	str	Foreign key linking to the mapped Crown. Non-nullable, cascades on delete.
source_image_id	int	Foreign key linking to the source ImageAcquisition. Sets to NULL on delete.
metrics	JSONVariant	Flexible JSON payload containing extracted index values and statistics. Non-nullable.
extracted_at	datetime	Timestamp marking when the metrics were computed, defaults to current UTC time.

Indexes

ix_spectral_metrics_gin: GIN index deployed on the metrics column for rapid JSON querying in PostgreSQL environments.

Relationships

crown (Crown): The spatial crown polygon these metrics correspond to. image_acquisition (ImageAcquisition): The raster dataset from which these spectral values were extracted.

Source code in src/phytospatial/db/models.py

class SpectralAttribute(Base):
    """
    Stores analytical metrics extracted from raster overlays mapped to specific crowns.

    Attributes:
        objectid (int): Primary key, auto-incrementing integer identifier.
        crown_id (str): Foreign key linking to the mapped Crown. Non-nullable, cascades on delete.
        source_image_id (int): Foreign key linking to the source ImageAcquisition. Sets to NULL on delete.
        metrics (JSONVariant): Flexible JSON payload containing extracted index values and statistics. Non-nullable.
        extracted_at (datetime.datetime): Timestamp marking when the metrics were computed, defaults to current UTC time.

    Indexes:
        ix_spectral_metrics_gin: GIN index deployed on the `metrics` column for rapid JSON querying in PostgreSQL environments.

    Relationships:
        crown (Crown): The spatial crown polygon these metrics correspond to.
        image_acquisition (ImageAcquisition): The raster dataset from which these spectral values were extracted.
    """
    __tablename__ = 'spectral_attributes'

    objectid = Column(Integer, primary_key=True, autoincrement=True)
    crown_id = Column(String(255), ForeignKey('crowns.crown_id', ondelete='CASCADE'), nullable=False)
    source_image_id = Column(Integer, ForeignKey('image_acquisitions.id', ondelete='SET NULL'))
    metrics = Column(JSONVariant, nullable=False)
    extracted_at = Column(DateTime(timezone=True), default=datetime.datetime.utcnow)

    __table_args__ = (
        Index('ix_spectral_metrics_gin', 'metrics', postgresql_using='gin'),
    )

    crown = relationship("Crown", back_populates="spectral_attributes")
    image_acquisition = relationship("ImageAcquisition", back_populates="spectral_attributes")

StructuralAttribute

Bases: Base

Stores geometric and structural metrics extracted from point clouds mapped to specific crowns.

Attributes:

Name	Type	Description
objectid	int	Primary key, auto-incrementing integer identifier.
crown_id	str	Foreign key linking to the mapped Crown. Non-nullable, cascades on delete.
source_lidar_id	int	Foreign key linking to the source LidarAcquisition. Sets to NULL on delete.
metrics	JSONVariant	Flexible JSON payload containing computed structural statistics. Non-nullable.
extracted_at	datetime	Timestamp marking when the metrics were computed, defaults to current UTC time.

Indexes

ix_structural_metrics_gin: GIN index deployed on the metrics column for rapid JSON querying in PostgreSQL environments.

Relationships

crown (Crown): The spatial crown polygon these structural traits correspond to. lidar_acquisition (LidarAcquisition): The point cloud dataset from which these physical dimensions were calculated.

Source code in src/phytospatial/db/models.py

class StructuralAttribute(Base):
    """
    Stores geometric and structural metrics extracted from point clouds mapped to specific crowns.

    Attributes:
        objectid (int): Primary key, auto-incrementing integer identifier.
        crown_id (str): Foreign key linking to the mapped Crown. Non-nullable, cascades on delete.
        source_lidar_id (int): Foreign key linking to the source LidarAcquisition. Sets to NULL on delete.
        metrics (JSONVariant): Flexible JSON payload containing computed structural statistics. Non-nullable.
        extracted_at (datetime.datetime): Timestamp marking when the metrics were computed, defaults to current UTC time.

    Indexes:
        ix_structural_metrics_gin: GIN index deployed on the `metrics` column for rapid JSON querying in PostgreSQL environments.

    Relationships:
        crown (Crown): The spatial crown polygon these structural traits correspond to.
        lidar_acquisition (LidarAcquisition): The point cloud dataset from which these physical dimensions were calculated.
    """
    __tablename__ = 'structural_attributes'

    objectid = Column(Integer, primary_key=True, autoincrement=True)
    crown_id = Column(String(255), ForeignKey('crowns.crown_id', ondelete='CASCADE'), nullable=False)
    source_lidar_id = Column(Integer, ForeignKey('lidar_acquisitions.id', ondelete='SET NULL'))
    metrics = Column(JSONVariant, nullable=False)
    extracted_at = Column(DateTime(timezone=True), default=datetime.datetime.utcnow)

    __table_args__ = (
        Index('ix_structural_metrics_gin', 'metrics', postgresql_using='gin'),
    )

    crown = relationship("Crown", back_populates="structural_attributes")
    lidar_acquisition = relationship("LidarAcquisition", back_populates="structural_attributes")

Tree

Bases: Base

Represents the primary master tree anchor points in the spatial database.

Attributes:

Name	Type	Description
objectid	int	Primary key, auto-incrementing integer identifier.
tree_id	str	Unique, non-nullable string identifier for the tree.
species	str	Botanical species classification of the tree.
status	str	Current physiological or management status of the tree.
geom	NativeGeometry	Custom spatial type for the tree's geometry, spatially indexed.
created_at	datetime	Timestamp of record creation, defaults to current UTC time.

Relationships

crowns (list[Crown]): Collection of delineated crown polygons associated with this tree. Cascade deletes orphans.

Source code in src/phytospatial/db/models.py

class Tree(Base):
    """
    Represents the primary master tree anchor points in the spatial database.

    Attributes:
        objectid (int): Primary key, auto-incrementing integer identifier.
        tree_id (str): Unique, non-nullable string identifier for the tree.
        species (str): Botanical species classification of the tree.
        status (str): Current physiological or management status of the tree.
        geom (NativeGeometry): Custom spatial type for the tree's geometry, spatially indexed.
        created_at (datetime.datetime): Timestamp of record creation, defaults to current UTC time.

    Relationships:
        crowns (list[Crown]): Collection of delineated crown polygons associated with this tree. Cascade deletes orphans.
    """
    __tablename__ = 'trees'

    objectid = Column(Integer, primary_key=True, autoincrement=True)
    tree_id = Column(String(255), unique=True, nullable=False)
    species = Column(String(255))
    status = Column(String(20))
    geom = Column(NativeGeometry('POINT', 32619))
    created_at = Column(DateTime(timezone=True), default=datetime.datetime.utcnow)

    crowns = relationship("Crown", back_populates="tree", cascade="all, delete-orphan")