Google Earth Engine Tutorial: Beginners Guide 16 Create Time Series Charts

Google Earth Engine Tutorial: Beginners Guide 16 – Create Time Series Charts using Google Earth Engine

Creating time series charts in Google Earth Engine (GEE) allows you to visualize changes in geospatial data over time. This tutorial will guide you through the process of generating a time series chart using Landsat imagery as an example. Follow these steps to analyze and plot data for a specific region and time period.

1. Load and Filter the Image Collection

Start by loading a dataset, such as Landsat 8 Collection 2 Tier 1 surface reflectance data. Filter it by your area of interest and time range:

var dataset = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2")
  .filterDate('2015-01-01', '2023-12-31')
  .filter(ee.Filter.eq('WRS_PATH', 25))
  .filter(ee.Filter.eq('WRS_ROW', 10));

2. Define the Region of Interest

Create a geometry object for the region you want to analyze. Replace the coordinates with your desired area:

var region = ee.Geometry.Rectangle([-122.5, 37.5, -122.0, 38.0]);

3. Calculate the Average Value per Image

Use a function to calculate the average value of a specific band, such as NDVI, for each image:

function calculateAverage(image) {
  var ndvi = image.select('SRB4').divide(image.select('SRB5')).rename('NDVI');
  var avg = ndvi.reduceRegion(ee.Reducer.mean(), region).get('NDVI');
  return image.set('NDVI_avg', avg);
}

4. Generate a List of Date and Value Pairs

Map the function over the image collection to extract the average values and dates:

var timeSeries = dataset.map(calculateAverage).map(function(image) {
  return ee.List([image.date().format('YYYY-MM-DD'), image.get('NDVI_avg')]);
});

Flatten the list to create a structured array of date-value pairs:

var values = timeSeries.reduce(ee.Reducer.toList(), 1).get(0);

5. Create the Time Series Chart

Use the charting tools in GEE to generate a time series plot. Customize the chart’s title, axis labels, and other parameters:

var chart = ee.Chart.array.values(values, 0, 1)
  .setOptions({
    title: 'NDVI Time Series',
    hAxis: {title: 'Date'},
    vAxis: {title: 'Average NDVI Value'},
    chartArea: {width: '80%', height: '70%'}
  });
print(chart);

The chart will appear in the console. To download it as an image, use chart.getDownloadURL() in the GEE Code Editor.

6. Customize and Visualize

You can customize the chart by changing the band, region, or date range. Consider using different datasets or metrics for other applications, such as land surface temperature or precipitation trends.

7. Export the Chart

To export the chart as a file, use the Export.image.toDrive function. Replace chart with your chart object and adjust parameters:

Export.image.toDrive({
  image: chart,
  description: 'NDVI_Time_Series',
  fileNamePrefix: 'ndvi_chart',
  scale: 30,
  region: region
});