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I am trying to create a function to calculate the average Vegetation Condition Index

((mean NDVI of individual year)-(min NDVI from full period)) / ((max NDVI from full period) - (min NDVI from full period))

...for the months of March, April and May in each individual year between 2001 and 2020 for a part of Ukraine, and then plot this on a graph. My reference period for the index is 2001-2020. I have applied a mask to just run the script on agricultural land in one specific region of the country.

I think there is an issue with my actual function as it is not currently running properly and is throwing the following error:

enter image description here

//calculate average monthly NDVI for Ukraine
//get MODIS NDVI
var collection = ee.ImageCollection('MODIS/006/MOD13A1').select('NDVI');

//import country boundaries
var countries = ee.FeatureCollection('USDOS/LSIB_SIMPLE/2017');

//Subset Ukraine feature from countries.
var ukr = ee.Feature(
  countries
   .filter(ee.Filter.eq('country_na', 'Ukraine'))
    .first()
);
print("ukr",ukr);

// Choose a reference period for your baseline
var reference = ee.ImageCollection(collection.filterDate('2001-01-01', '2020-12-31'))
  .sort('system:time_start');
print("reference",reference);

//filter out images from specific date
//march, april, may (spring)
var spring = reference.filter(ee.Filter.dayOfYear(59,150));

//calulate min of full series (mam 2001-2020) for each pixel
var spring_min = spring.min();

//calculate max of full series (mam 2001-2020) for each pixel
var spring_max = spring.max();

//mam_2003_mean IS the average ndvi for specific season (2003 mam)
//clip to zap agrimask
var spring_agrimask_min = spring_min.multiply(zap_crop_mask);
var spring_agrimask_max = spring_max.multiply(zap_crop_mask);

//Use a function to iterate through months and calculate average Vegetation condition Index
var years = ee.List.sequence(2001, 2020);
print("years",years);

var byYear = ee.ImageCollection.fromImages(
      years.map(function (y) {
          var year_mean = y.select(("NDVI")).mean();
          var year_mean_mask = year_mean.multiply(zap_crop_mask);
          var vci_top = year_mean_mask.subtract(spring_agrimask_min);
          var vci_bot = spring_agrimask_max.subtract(spring_arimask_min);
          var vci = vci_top.subtract(vci_bot);
        return vci.filter(ee.Filter.calendarRange(y, y, 'year'))
                    .set('year', y);
}));
print("byYear",byYear);

//Define chart parameters
var chartParam = {
 title: 'Annual average NDVI',
  hAxis: {title: 'Time'},
  vAxis: {title: 'Average NDVI'},
};

//Plot the chart
var chart = ui.Chart.image.seriesByRegion({
  imageCollection: byYear,
//  regions: ukr,
  reducer: ee.Reducer.mean(),
  scale: 500,
  xProperty: 'year',
  seriesProperty: 'PROJECT'
});
//Print chart to console
print(chart.setOptions(chartParam));

1 Answer 1

0

Structuring the function like this worked well

var summer_vci = ee.ImageCollection.fromImages(
      years.map(function (y) {
        return summer.filter(ee.Filter.calendarRange(y, y, 'year'))
                    .select(("NDVI")).mean()
                    .multiply(zap_crop_mask)
                    .subtract(summer_agrimask_min)
                    .divide(vci_bot_sum)
                    .set('year', y);
}));
print("byYear",summer_vci);

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