146 chart image collection

ImageCollection Charts

Uncomment the following line to install geemap if needed.

In [ ]:

# %pip install -U geemap

# %pip install -U geemap

Import libraries¶

In [ ]:

import ee
import geemap
from geemap import chart

import ee import geemap from geemap import chart

In [ ]:

geemap.ee_initialize()

geemap.ee_initialize()

image_series¶

In [ ]:

# Define the forest feature collection.
forest = ee.FeatureCollection("projects/google/charts_feature_example").filter(
    ee.Filter.eq("label", "Forest")
)

# Load MODIS vegetation indices data and subset a decade of images.
veg_indices = (
    ee.ImageCollection("MODIS/061/MOD13A1")
    .filter(ee.Filter.date("2010-01-01", "2020-01-01"))
    .select(["NDVI", "EVI"])
)

# Define the forest feature collection. forest = ee.FeatureCollection("projects/google/charts_feature_example").filter( ee.Filter.eq("label", "Forest") ) # Load MODIS vegetation indices data and subset a decade of images. veg_indices = ( ee.ImageCollection("MODIS/061/MOD13A1") .filter(ee.Filter.date("2010-01-01", "2020-01-01")) .select(["NDVI", "EVI"]) )

In [ ]:

title = "Average Vegetation Index Value by Date for Forest"
x_label = "Year"
y_label = "Vegetation index (x1e4)"
colors = ["#e37d05", "#1d6b99"]

title = "Average Vegetation Index Value by Date for Forest" x_label = "Year" y_label = "Vegetation index (x1e4)" colors = ["#e37d05", "#1d6b99"]

In [ ]:

fig = chart.image_series(
    veg_indices,
    region=forest,
    reducer=ee.Reducer.mean(),
    scale=500,
    x_property="system:time_start",
    chart_type="LineChart",
    x_cols="date",
    y_cols=["NDVI", "EVI"],
    colors=colors,
    title=title,
    x_label=x_label,
    y_label=y_label,
    legend_location="right",
)
fig

fig = chart.image_series( veg_indices, region=forest, reducer=ee.Reducer.mean(), scale=500, x_property="system:time_start", chart_type="LineChart", x_cols="date", y_cols=["NDVI", "EVI"], colors=colors, title=title, x_label=x_label, y_label=y_label, legend_location="right", ) fig

image_series_by_region¶

In [ ]:

# Import the example feature collection.
ecoregions = ee.FeatureCollection("projects/google/charts_feature_example")

# Load MODIS vegetation indices data and subset a decade of images.
veg_indices = (
    ee.ImageCollection("MODIS/061/MOD13A1")
    .filter(ee.Filter.date("2010-01-01", "2020-01-01"))
    .select(["NDVI"])
)

# Import the example feature collection. ecoregions = ee.FeatureCollection("projects/google/charts_feature_example") # Load MODIS vegetation indices data and subset a decade of images. veg_indices = ( ee.ImageCollection("MODIS/061/MOD13A1") .filter(ee.Filter.date("2010-01-01", "2020-01-01")) .select(["NDVI"]) )

In [ ]:

title = "Average NDVI Value by Date"
x_label = "Date"
y_label = "NDVI (x1e4)"
x_cols = "index"
y_cols = ["Desert", "Forest", "Grassland"]
colors = ["#f0af07", "#0f8755", "#76b349"]

title = "Average NDVI Value by Date" x_label = "Date" y_label = "NDVI (x1e4)" x_cols = "index" y_cols = ["Desert", "Forest", "Grassland"] colors = ["#f0af07", "#0f8755", "#76b349"]

In [ ]:

fig = chart.image_series_by_region(
    veg_indices,
    regions=ecoregions,
    reducer=ee.Reducer.mean(),
    band="NDVI",
    scale=500,
    x_property="system:time_start",
    series_property="label",
    chart_type="LineChart",
    x_cols=x_cols,
    y_cols=y_cols,
    title=title,
    x_label=x_label,
    y_label=y_label,
    colors=colors,
    stroke_width=3,
    legend_location="bottom-left",
)
fig

fig = chart.image_series_by_region( veg_indices, regions=ecoregions, reducer=ee.Reducer.mean(), band="NDVI", scale=500, x_property="system:time_start", series_property="label", chart_type="LineChart", x_cols=x_cols, y_cols=y_cols, title=title, x_label=x_label, y_label=y_label, colors=colors, stroke_width=3, legend_location="bottom-left", ) fig

image_doy_series¶

In [ ]:

# Import the example feature collection and subset the grassland feature.
grassland = ee.FeatureCollection("projects/google/charts_feature_example").filter(
    ee.Filter.eq("label", "Grassland")
)

# Load MODIS vegetation indices data and subset a decade of images.
veg_indices = (
    ee.ImageCollection("MODIS/061/MOD13A1")
    .filter(ee.Filter.date("2010-01-01", "2020-01-01"))
    .select(["NDVI", "EVI"])
)

# Import the example feature collection and subset the grassland feature. grassland = ee.FeatureCollection("projects/google/charts_feature_example").filter( ee.Filter.eq("label", "Grassland") ) # Load MODIS vegetation indices data and subset a decade of images. veg_indices = ( ee.ImageCollection("MODIS/061/MOD13A1") .filter(ee.Filter.date("2010-01-01", "2020-01-01")) .select(["NDVI", "EVI"]) )

In [ ]:

title = "Average Vegetation Index Value by Day of Year for Grassland"
x_label = "Day of Year"
y_label = "Vegetation Index (x1e4)"
colors = ["#f0af07", "#0f8755"]

title = "Average Vegetation Index Value by Day of Year for Grassland" x_label = "Day of Year" y_label = "Vegetation Index (x1e4)" colors = ["#f0af07", "#0f8755"]

In [ ]:

fig = chart.image_doy_series(
    image_collection=veg_indices,
    region=grassland,
    scale=500,
    chart_type="LineChart",
    title=title,
    x_label=x_label,
    y_label=y_label,
    colors=colors,
    stroke_width=5,
)
fig

fig = chart.image_doy_series( image_collection=veg_indices, region=grassland, scale=500, chart_type="LineChart", title=title, x_label=x_label, y_label=y_label, colors=colors, stroke_width=5, ) fig

image_doy_series_by_year¶

In [ ]:

# Import the example feature collection and subset the grassland feature.
grassland = ee.FeatureCollection("projects/google/charts_feature_example").filter(
    ee.Filter.eq("label", "Grassland")
)

# Load MODIS vegetation indices data and subset years 2012 and 2019.
veg_indices = (
    ee.ImageCollection("MODIS/061/MOD13A1")
    .filter(
        ee.Filter.Or(
            ee.Filter.date("2012-01-01", "2013-01-01"),
            ee.Filter.date("2019-01-01", "2020-01-01"),
        )
    )
    .select(["NDVI", "EVI"])
)

# Import the example feature collection and subset the grassland feature. grassland = ee.FeatureCollection("projects/google/charts_feature_example").filter( ee.Filter.eq("label", "Grassland") ) # Load MODIS vegetation indices data and subset years 2012 and 2019. veg_indices = ( ee.ImageCollection("MODIS/061/MOD13A1") .filter( ee.Filter.Or( ee.Filter.date("2012-01-01", "2013-01-01"), ee.Filter.date("2019-01-01", "2020-01-01"), ) ) .select(["NDVI", "EVI"]) )

In [ ]:

title = "Average Vegetation Index Value by Day of Year for Grassland"
x_label = "Day of Year"
y_label = "Vegetation Index (x1e4)"
colors = ["#e37d05", "#1d6b99"]

title = "Average Vegetation Index Value by Day of Year for Grassland" x_label = "Day of Year" y_label = "Vegetation Index (x1e4)" colors = ["#e37d05", "#1d6b99"]

In [ ]:

fig = chart.doy_series_by_year(
    veg_indices,
    band_name="NDVI",
    region=grassland,
    scale=500,
    chart_type="LineChart",
    colors=colors,
    title=title,
    x_label=x_label,
    y_label=y_label,
    stroke_width=5,
)
fig

fig = chart.doy_series_by_year( veg_indices, band_name="NDVI", region=grassland, scale=500, chart_type="LineChart", colors=colors, title=title, x_label=x_label, y_label=y_label, stroke_width=5, ) fig

image_doy_series_by_region¶

In [ ]:

# Import the example feature collection and subset the grassland feature.
ecoregions = ee.FeatureCollection("projects/google/charts_feature_example")

# Load MODIS vegetation indices data and subset a decade of images.
veg_indices = (
    ee.ImageCollection("MODIS/061/MOD13A1")
    .filter(ee.Filter.date("2010-01-01", "2020-01-01"))
    .select(["NDVI"])
)

# Import the example feature collection and subset the grassland feature. ecoregions = ee.FeatureCollection("projects/google/charts_feature_example") # Load MODIS vegetation indices data and subset a decade of images. veg_indices = ( ee.ImageCollection("MODIS/061/MOD13A1") .filter(ee.Filter.date("2010-01-01", "2020-01-01")) .select(["NDVI"]) )

In [ ]:

title = "Average Vegetation Index Value by Day of Year for Grassland"
x_label = "Day of Year"
y_label = "Vegetation Index (x1e4)"
colors = ["#f0af07", "#0f8755", "#76b349"]

title = "Average Vegetation Index Value by Day of Year for Grassland" x_label = "Day of Year" y_label = "Vegetation Index (x1e4)" colors = ["#f0af07", "#0f8755", "#76b349"]

In [ ]:

fig = chart.image_doy_series_by_region(
    veg_indices,
    "NDVI",
    ecoregions,
    region_reducer="mean",
    scale=500,
    year_reducer=ee.Reducer.mean(),
    start_day=1,
    end_day=366,
    series_property="label",
    stroke_width=5,
    chart_type="LineChart",
    title=title,
    x_label=x_label,
    y_label=y_label,
    colors=colors,
    legend_location="right",
)
fig

fig = chart.image_doy_series_by_region( veg_indices, "NDVI", ecoregions, region_reducer="mean", scale=500, year_reducer=ee.Reducer.mean(), start_day=1, end_day=366, series_property="label", stroke_width=5, chart_type="LineChart", title=title, x_label=x_label, y_label=y_label, colors=colors, legend_location="right", ) fig