Timeseries

The Timeseries endpoints are used to generate time series data for the datasets available in Climate Engine.

There are three groups of Timeseries endpoints for points, polygons or an Earth Engine FeaturesCollection:

/timeseries/native - The native endpoints are used to generate ‘raw’ time series data.

/timeseries/interannual - The interannual endpoints are used to generate time series of yearly values of the dataset variable summarized over a season.

/timeseries/regression - The regression endpoints are used to perform regression analysis of the dataset variable summarized over a season.

NOTES:

- The ‘forecasts’ endpoints are only available for forecast datasets CFS_GRIDMET, FRET, GEPS_2WK, “GEPS_4WK.

/timeseries/native/coordinates

/timeseries/native/feature_collection

/timeseries/native/forecasts/coordinates

/timeseries/native/forecasts/feature_collection

/timeseries/standard_index/coordinates

/timeseries/standard_index/feature_collection

/timeseries/interannual/coordinates

/timeseries/interannual/feature_collection

/timeseries/regression/coordinates

/timeseries/regression/feature_collection

/timeseries/native/coordinates

Generates timeseries of values of the dataset variable and timeperiod between start_date and end_date for points or polygons.

Returns: json

Resource url example:

/timeseries/native/coordinates?dataset=GRIDMET&variable=pr&start_date=2014-01-01&end_date=2014-02-01&coordinates=[[-119.96,39.57]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
coordinates	yes	List of point or polygon coordinates, see https://support.climateengine.org/article/152-formatting-coordinates-for-api-requests		[[-119.96,39.57]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
compute_trends	no	Also compute trends		sens_slope, polyfit
mask_image_id	no	Image mask ID
mask_band	no	Mask band
mask_value	no	Image mask value
start_date	yes			2019-01-01
end_date	yes			2019-12-31
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/native/feature_collection

Generates timeseries of values of the dataset variable and timeperiod between start_date and end_date for the features of an Earth Engine FeatureCollection.

The values are averaged over the pixels lying within each feature of the feature collection.

Permissions on the asset must be such that it is readable by anyone.

Returns: json

Resource url example:

/timeseries/native/feature_collection?dataset=LANDSAT7_TOA&variable=NDVI&start_date=2014-01-01&end_date=2014-02-01&feature_collection_asset_id=WCMC/WDPA/current/points&sub_choices= ["Golden Gate"]&filter_by=NAME

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
feature_collection_asset_id	yes	EE FeatureCollection asset id, must have “Anyone can read” permissions		WCMC/WDPA/current/points
sub_choices	no	List of features to use in analysis, must be strings		[“Golden Gate”]
filter_by	no	Property name to filter sub-choices		NAME
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
compute_trends	no	Also compute trends		sens_slope, polyfit
mask_image_id	no	Image mask ID
mask_band	no	Mask band
mask_value	no	Image mask value
start_date	yes			2019-01-01
end_date	yes			2019-12-31
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/native/forecasts/coordinates

Generates timeseries of forecast values of the dataset variable and timeperiod between start_date and end_date for points or polygons.

Returns: json

Resource url example:

/timeseries/native/forecasts/coordinates?dataset=CFS_GRIDMET&variable=pr&start_day=day01&end_day=day28&coordinates=[[-119.96,39.57]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
coordinates	yes	List of point or polygon coordinates, see https://support.climateengine.org/article/152-formatting-coordinates-for-api-requests		[[-119.96,39.57]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max
dataset	yes		CFS_GRIDMET	CFS_GRIDMET, FRET, GEPS_2WK,GEPS_4WK
variable	yes	pet, pr, tmmn, tmmx		pr
model	yes	ens01 to en<xx> for individual models (see documentation), ens_min, ens_max, ens_mean, ens_median	ens_mean	ens_max
mask_image_id	no	Image mask ID
mask_band	no	Mask band
mask_value	no	Image mask value
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/native/forecasts/feature_collection

Generates timeseries of forecast values of the dataset variable and timeperiod between start_date and end_date for the features of an Earth Engine FeatureCollection.

The values are averaged over the pixels lying within each feature of the feature collection.

Permissions on the asset must be such that it is readable by anyone.

Returns: json

Resource url example:

/timeseries/native/forecasts/feature_collection?dataset=CFS_GRIDMET&variable=pet&start_day=day01&end_day=day28&feature_collection_asset_id=WCMC/WDPA/current/points&sub_choices= ["Golden Gate"]&filter_by=NAME

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
feature_collection_asset_id	yes	EE FeatureCollection asset id, must have “Anyone can read” permissions		WCMC/WDPA/current/points
sub_choices	no	List of features to use in analysis, must be strings		[“Golden Gate”]
filter_by	no	Property name to filter sub-choices		NAME
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
dataset	yes		CFS_GRIDMET	CFS_GRIDMET, FRET, GEPS_2WK,GEPS_4WK
variable	yes	pet, pr, tmmn, tmmx		pet
model	yes	ens01 to en<xx> for individual models (see documentation), ens_min, ens_max, ens_mean, ens_median	ens_mean	ens_max
mask_image_id	no	Image mask ID
mask_band	no	Mask band
mask_value	no	Image mask value
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/standard_index/coordinates

Generates timeseries of standard index based on inputs for points or polygons.

Standard Precipitation Index (SPI) for example is the standard index of precipitation. To calculate SPI, you would use precipitation as the variable.

Similarly, the Standardized Precipitation Evapotranspiration Index (SPEI) potential water deficit (precipitation minus potential evapotranspiration) would be used as the variable.

In the case of a buffer, the values are reduced over the pixels lying within the point before calculating the standard index.

Note: Cannot use pre-calculated drought indices, i.e. GridMET Drought as dataset/variable.

Available variables: spi, spei, eddi, speih, edddih

Returns: json

Resource url example:

/timeseries/standard_index/coordinates?dataset=PRISM_MONTHLY&variable=ppt&area_reducer=mean&start_date=1991-01-01&end_date=2020-12-31&start_year=1991&end_year=2020&accumulation=3&distribution=loglogistic&coordinates=%5B%5B-121.61%2C38.78%5D%5D

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
coordinates	yes	List of point or polygon coordinates, see https://support.climateengine.org/article/152-formatting-coordinates-for-api-requests		[[-121.61,38.78]]
buffer	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max
dataset	yes	Dataset of interest	PRISM_MONTHLY	PRISM_MONTHLY, GRIDMET
variable	yes	Variable of interest	spi	spi, spei, eddi, speih, eddih
mask_image_id	no	Image mask ID
mask_band	no	Mask band
mask_value	no	Image mask value
start_date	yes	Start date for timeseries	1991-01-01	2019-01-01
end_date	yes	End date for timeseries	2020-12-31	2019-12-31
start_year	yes	Start year for climatology	1991	1990
end_year	yes	End year for climatology	2020	2020
accumulation	yes	Accumulation period for index. Same unit as dataset.	3	3, 30, 12, 365
distribution	yes	The distribution used to calculate the standard index	loglogistic	loglogistic, gamma, nonparametric
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/standard_index/feature_collection

Generates timeseries of standard index based on inputs for an Earth Engine FeatureCollection.

Standard Precipitation Index (SPI) for example is the standard index of precipitation. To calculate SPI, you would use precipitation as the variable.

Similarly, the Standardized Precipitation Evapotranspiration Index (SPEI) potential water deficit (precipitation minus potential evapotranspiration) would be used as the variable.

The values are reduced over the pixels lying within the feature before calculating the standard index.

Note: Cannot use pre-calculated drought indices, i.e. GridMET Drought as dataset/variable.

Available variables: spi, spei, eddi, speih, edddih

Returns: json

Resource url example:

/timeseries/standard_index/feature_collection?dataset=PRISM_MONTHLY&variable=ppt&area_reducer=mean&start_date=1991-01-01&end_date=2020-12-31&start_year=1991&end_year=2020&accumulation=3&distribution=loglogistic&feature_collection_asset_id=USGS%2FWBD%2F2017%2FHUC08

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
feature_collection_asset_id	yes	EE FeatureCollection asset id, must have “Anyone can read” permissions	USGS/WBD/2017/HUC08
sub_choices	no	List of features you are interested in		Piscataqua-Salmon Falls
filter_by	no	Name of the property you want to filter by		name
buffer	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Reducer over the polygon	mean	mean, median, min, max
dataset	yes	Dataset of interest	PRISM_MONTHLY	PRISM_MONTHLY, GRIDMET
variable	yes	Variable of interest	spi	spi, spei, eddi, speih, edddih
mask_image_id	no	Image mask ID
mask_band	no	Mask band
mask_value	no	Image mask value
start_date	yes	Start date for timeseries	1991-01-01	2019-01-01
end_date	yes	End date for timeseries	2020-12-31	2019-12-31
start_year	yes	Start year for climatology	1991	1990
end_year	yes	End year for climatology	2020	2020
accumulation	yes	Accumulation period for index. Same unit as dataset.	3	3, 30, 12, 365
distribution	yes	The distribution used to calculate the standard index	loglogistic	loglogistic, gamma, nonparametric
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/interannual/coordinates

Generates timeseries of yearly values of the dataset variable summarized over a season for points or polygons.

Returns: json

Resource url example:

/timeseries/interannual/coordinates?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&start_year=2016&end_year=2018&coordinates=[[-119.96,39.57], [-119, 39]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
coordinates	yes	List of point or polygon coordinates, see https://support.climateengine.org/article/152-formatting-coordinates-for-api-requests		[[-119.96,39.57]]
buffer	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean	mean, median, min, max
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
compute_trends	no	Also compute trends		sens_slope, polyfit
temporal_statistic	yes			mean
mask_image_id	no	Image mask ID
mask_band	no	Mask band
mask_value	no	Image mask value
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
start_year	yes			2016
end_year	yes			2018
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/interannual/feature_collection

Generates timeseries of yearly values of the dataset variable summarized over a season for the features of an Earth Engine FeatureCollection.

The values are averaged over the pixels lying within each feature of the feature collection.

Permissions on the asset must be such that it is readable by anyone.

Returns: json

Resource url example:

/timeseries/interannual/feature_collection?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&start_year=2014&end_year=2018&feature_collection_asset_id=WCMC/WDPA/current/points&sub_choices=["Golden Gate"]&filter_by=NAME

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
feature_collection_asset_id	yes	EE FeatureCollection asset id, must have “Anyone can read” permissions		WCMC/WDPA/current/points
sub_choices	no	List of features to use in analysis, must be strings		[“Golden Gate”]
filter_by	no	Property name to filter sub-choices		NAME
area_reducer	yes	Statistic over region	mean	mean, median, min, max, stdev, count, count_un, skew, kurtosis, percentile_5, percentile_10, percentile_25, percentile_75, percentile_90, percentile_95
dataset	yes			LANDSAT7_TOA
variable	yes	single or multiple variable		NDVI or NDVI,EVI
compute_trends	no	Also compute trends		sens_slope, polyfit
temporal_statistic	yes			mean, median, max, min, total
mask_image_id	no	Image mask ID
mask_band	no	Mask band
mask_value	no	Image mask value
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
start_year	yes			2016
end_year	yes			2018
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/regression/coordinates

Performs regression analysis of the dataset variable summarized over a season for points or polygons.

Returns: json

Resource url example:

/timeseries/regression/coordinates?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&var2_dataset=LANDSAT7_TOA&var2_variable=NDSI&var2_temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&var2_start_day=01&var2_end_day=30&var2_start_month=01&var2_end_month=12&start_year=2016&end_year=2018&coordinates=[[-119.96,39.57]]

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
coordinates	yes	List of point or polygon coordinates, see https://support.climateengine.org/article/152-formatting-coordinates-for-api-requests		[[-119.96,39.57]]
buffers	no	List of integer buffers (meters) to be applied to each geometry		[400]
area_reducer	yes	Statistic over region	mean
dataset	yes			LANDSAT7_TOA
variable	yes			NDVI
mask_image_id	no	Image mask ID
mask_band	no	Mask band
mask_value	no	Image mask value
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
temporal_statistic	yes			mean, median, max, min, total
var2_dataset	yes			LANDSAT7_TOA
var2_variable	yes			NDSI
var2_mask_image_id	no	Image mask ID for the second dataset/variable
var2_mask_band	no	Mask band for the second dataset/variable
var2_mask_value	no	Image mask value for the second dataset/variable
var2_start_day	yes			01
var2_end_day	yes			30
var2_start_month	yes			01
var2_end_month	yes			12
start_year	yes			2016
end_year	yes			2018
var2_temporal_statistic	yes			mean
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json

/timeseries/regression/feature_collection

Performs regression analysis of the dataset variable summarized over a season for the features of an Earth Engine FeatureCollection.

The values are averaged over the pixels lying within each feature of the feature collection.

Permissions on the asset must be such that it is readable by anyone.

Returns: json

Resource url example:

/timeseries/regression/feature_collection?dataset=LANDSAT7_TOA&variable=NDVI&temporal_statistic=Mean&var2_dataset=LANDSAT7_TOA&var2_variable=NDSI&var2_temporal_statistic=Mean&start_day=01&end_day=30&start_month=01&end_month=12&var2_start_day=01&var2_end_day=30&var2_start_month=01&var2_end_month=12&start_year=2016&end_year=2018&feature_collection_asset_id=USGS/WBD/2017/HUC08&sub_choices=["Animas"]&filter_by=name

NAME	REQUIRED	DESCRIPTION	DEFAULT	EXAMPLE
feature_collection_asset_id	yes	EE FeatureCollection asset id, must have “Anyone can read” permissions		USGS/WBD/2017/HUC08
sub_choices	no	List of features to use in analysis, must be strings		[“Animas”]
filter_by	no	Property name to filter sub-choices		name
area_reducer	yes	Statistic over region	mean	mean, median, min, max
dataset	yes			LANDSAT7_TOA
variable	yes			NDVI
temporal_statistic	yes			mean
var2_dataset	yes			LANDSAT7_TOA
variable	yes			NDSI
temporal_statistic	yes			mean
start_day	yes			01
end_day	yes			30
start_month	yes			01
end_month	yes			12
var2_start_day	yes			01
var2_end_day	yes			30
var2_start_month	yes			01
var2_end_month	yes			12
start_year	yes			2016
end_year	yes			2018
export_path	no	Export CSV results to a Google cloud storage bucket (must have correct permissions)		climate-engine-public/my_csv_file.csv
export_format	no	File format of export	json	csv, json