Phenocam

This module contains functionality to download and load data from phenocam observations (https://phenocam.nau.edu/webcam/) using phenocamr as client.

Requires phenocamr R package. Install with

install.packages("phenocamr")

Example

from springtime.datasets import PhenocamrSite

dataset = PhenocamrSite(
    site="harvard$",
    years=(2019, 2020),
)
dataset.download()
df = dataset.load()

Example

from springtime.datasets import PhenocamrBoundingBox

dataset = PhenocamrBoundingBox(
    area={
        "name": "harvard",
        "bbox": [-73, 42, -72, 43],
    },
    years=(2019, 2020),
)
dataset.download()
df = dataset.load()

PhenocamVariables = Literal['midday_r', 'midday_g', 'midday_b', 'midday_gcc', 'midday_rcc', 'r_mean', 'r_std', 'g_mean', 'g_std', 'b_mean', 'b_std', 'gcc_mean', 'gcc_std', 'gcc_50', 'gcc_75', 'gcc_90', 'rcc_mean', 'rcc_std', 'rcc_50', 'rcc_75', 'rcc_90', 'max_solar_elev', 'smooth_gcc_mean', 'smooth_gcc_50', 'smooth_gcc_75', 'smooth_gcc_90', 'smooth_rcc_mean', 'smooth_rcc_50', 'smooth_rcc_75', 'smooth_rcc_90', 'smooth_ci_gcc_mean', 'smooth_ci_gcc_50', 'smooth_ci_gcc_75', 'smooth_ci_gcc_90', 'smooth_ci_rcc_mean', 'smooth_ci_rcc_50', 'smooth_ci_rcc_75', 'smooth_ci_rcc_90'] module-attribute

Variables available in phenocamr.

Phenocam

Bases: Dataset

Download and load data from phenocam

Attributes:

Name	Type	Description
years		timerange. For example years=[2000, 2002] downloads data for three years.
resample		Resample the dataset to a different time resolution. If None, no resampling.
veg_type	Optional[str]	Vegetation type (DB, EN). Default is "all".
frequency	Literal['1', '3', 'roistats']	Frequency of the time series product.
variables	Sequence[PhenocamVariables]	Variables you want to download. When empty will download all the variables.

download() abstractmethod

Download the data.

Only downloads if data is not in CONFIG.cache_dir or CONFIG.force_override is TRUE.

load() abstractmethod

Load the dataset from disk into memory.

This may include pre-processing operations as specified by the context, e.g. filter certain variables, remove data points with too many NaNs, reshape data.

PhenocamrSite

Bases: Phenocam

PhenoCam time series for site.

Attributes:

Name	Type	Description
veg_type		Vegetation type (DB, EN). Default is "all".
frequency		Frequency of the time series product.
variables		Variables you want to download. When empty will download all the variables.
site	str	Name of site. Append $ to get exact match.
rois	Optional[List[int]]	The id of the ROI to download. Default is all ROIs at site.
years	Optional[List[int]]	timerange. For example years=[2000, 2002] downloads data for three years.
resample	Optional[List[int]]	Resample the dataset to a different time resolution. If None, no resampling.

download()

Download the data.

Only downloads if data is not in CONFIG.cache_dir or CONFIG.force_override is TRUE.

load()

Load the dataset from disk into memory.

This may include pre-processing operations as specified by the context, e.g. filter certain variables, remove data points with too many NaNs, reshape data.

PhenocamrBoundingBox

Bases: Phenocam

PhenoCam time series for sites in a bounding box.

Attributes:

Name	Type	Description
years		timerange. For example years=[2000, 2002] downloads data for three years.
resample		Resample the dataset to a different time resolution. If None, no resampling.
veg_type		Vegetation type (DB, EN). Default is "all".
frequency		Frequency of the time series product.
variables		Variables you want to download. When empty will download all the variables.
area	NamedArea	A dictionary of the form {"name": "yourname", "bbox": [xmin, ymin, xmax, ymax]}.

download()

Download the data.

Only downloads if data is not in CONFIG.cache_dir or CONFIG.force_override is TRUE.

load()

Load the dataset from disk into memory.

This may include pre-processing operations as specified by the context, e.g. filter certain variables, remove data points with too many NaNs, reshape data.

list_sites()

List of phenocam sites.

Returns:

Type	Description
geopandas.GeoDataFrame	Data frame containing phenocam sites

list_rois()

List of phenocam regions of interest (ROI).

Returns:

Type	Description
geopandas.GeoDataFrame	Data frame containing phenocam Regions of Interest.