Calculation of Standard Vegetation Index from EVI for Image Collection in Google Earth Engine

Question

I'm relatively new to scripting in the Google Earth Engine and have an issue with calculating the Standard Vegetation Index (SVI) for a MODIS image collection. I want to write a function, which uses ee.Reducer.mean() and ee.Reducer.stdDev() of an image to calculate the SVI and map it over the image collection. However, GEE gives me the following Error-Code:

Error in map(ID=XXX_XX_XX): Image.constant: Invalid Image.constant type.

Where "ID=XXXX_XX_XX" seems to be a random date. Has anybody an idea how to solve that problem?

//Add ROI
var ROI = ee.Geometry.Polygon(
  [[-2.2535247523754443,5.881894109545312], 
  [-0.31993100237544425,5.881894109545312], 
  [-0.31993100237544425,9.669268383910472], 
  [-2.2535247523754443,5.881894109545312]]);

//Add MODIS ImageCollection
var MODIS = ee.ImageCollection("MODIS/006/MOD13Q1")
  .select(['EVI'])
  .filterDate('2000-01-01', '2020-01-01')
  .filterBounds(ROI)
  .map(function(image){return image.clip(ROI)});

//Function to Map SVI over image collection
var CalculateSVI = MODIS.map(function(SVI){
  var SelectImage = SVI.select(['EVI'], ['SVI']);

//Calculate Mean of Image  
  var Mean = ee.Number(SelectImage.reduceRegion({
  reducer: ee.Reducer.mean(),
  geometry: ROI,
  bestEffort: true,
  }));

//Calculate Stdv of Image  
  var Stdv = ee.Number(SelectImage.reduceRegion({
  reducer: ee.Reducer.stdDev(),
  geometry: ROI,
  bestEffort: true,
  }));

//Calculate SVI
  var CalcSVI =  SelectImage.expression(
  ((SelectImage.subtract(Mean)).divide(Stdv))
  );

  return CalcSVI.addBands(SVI);
});
print(CalculateSVI);

Answer 1

reduceRegion() returns a ee.Dictionary(). Since you selected one band, you will always have one output value. You can then get that value from the dictionary using .values().get(0). Also, you don't need to use the expression() function.

//Calculate Mean of Image  
  var Mean = ee.Number(SelectImage.reduceRegion({
  reducer: ee.Reducer.mean(),
  geometry: ROI,
  bestEffort: true,
  }).values().get(0));

//Calculate Stdv of Image  
  var Stdv = ee.Number(SelectImage.reduceRegion({
  reducer: ee.Reducer.stdDev(),
  geometry: ROI,
  bestEffort: true,
  }).values().get(0));

//Calculate SVI
  var CalcSVI = (SelectImage.subtract(Mean)).divide(Stdv)

see some other suggestion in the code. Note that this is just the solution of the code error you got. I have no idea if the actual SVI values are correctly calculated.

Answer 2

Apart from the problems @kuik points out, I'm wondering if you're calculating SVI correctly. I've never done it myself, but look at this article:

The SVI is a z-score deviation from the mean in units of the standard deviation, calculated from the NDVI or EVI values for each pixel location of a composite period for each year during a given reference period. The equation below shows the general calculation of the SVI

It seems like you should calculate your mean and standard deviation by pixel over time, not over your region. Here's my take on this, which might not be correct, but reflects my understanding of the above article:

var region = ee.Geometry.Polygon([
  [-2.2535247523754443, 5.881894109545312],
  [-0.31993100237544425, 5.881894109545312],
  [-0.31993100237544425, 9.669268383910472],
  [-2.2535247523754443, 5.881894109545312]
])

var startDate = ee.Date('2000-01-01')
var endDate = ee.Date('2020-01-01')

var collection = ee.ImageCollection("MODIS/006/MOD13Q1")
  .filterDate(startDate, endDate)
  .filterBounds(region)
  .map(maskClouds)
  .select(['EVI'])

var deltaDays = 7
var statsCollection = ee.ImageCollection(
  ee.List.sequence(0, 365, deltaDays).map(calculateStats)
)

var sviCollection = collection.map(toSVI)  
print(sviCollection)

Map.centerObject(region, 9)
var first = sviCollection
  .first()
  .clip(region)

var sviVis = {
    min: -2,
    max: 2,
    palette: ["ffffff", "ce7e45", "df923d", "f1b555", "fcd163", "99b718", "74a901", "66a000", "529400", "3e8601", "207401", "056201", "004c00", "023b01", "012e01", "011d01", "011301"]
  }  
Map.addLayer(first, sviVis, 'first')


function calculateStats(startDOY) {
  var endDOY = ee.Number(startDOY).add(deltaDays)
  return collection
    .filter(ee.Filter.calendarRange(startDOY, endDOY, 'day_of_year'))
    .reduce(ee.Reducer.stdDev().combine(ee.Reducer.mean(), null, true))
    .set('startDOY', startDOY)
    .set('endDOY', endDOY)  
}

function toSVI(image) {
  var doy = image.date().getRelative('day', 'year')
  var stats = statsCollection
    .filter(ee.Filter.lte('startDOY', doy))
    .filter(ee.Filter.gt('endDOY', doy))
    .first()
  return image
    .expression(
      '(evi - mean) / stdDev', {
        evi: image, 
        mean: stats.select('EVI_mean'), 
        stdDev: stats.select('EVI_stdDev')
    })
    .rename('svi')
    .copyProperties(image, image.propertyNames())
}

function maskClouds(image) {
  var qa = image.select('DetailedQA')

  // https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13Q1
  var quality = bitwiseExtract(qa, 0, 1)
  var usefulness = bitwiseExtract(qa, 2, 5)
  var aerosolQuantity = bitwiseExtract(qa, 6, 7)
  var adjacentCloudDetected = bitwiseExtract(qa, 8)
  var atmosphereBrdfCorrection = bitwiseExtract(qa, 9)
  var mixedClouds = bitwiseExtract(qa, 10)
  var landWaterMask = bitwiseExtract(qa, 11, 13)
  var possibleSnowIce = bitwiseExtract(qa, 14)
  var possibleShadow = bitwiseExtract(qa, 15)
  var mask = quality.lte(1) // VI produced, but check other QA
    .and(usefulness.lte(2)) // Lower quality
    .and(aerosolQuantity.lte(2)) // Intermediate
    .and(adjacentCloudDetected.eq(0)) // No
    .and(mixedClouds.eq(0)) // No
    .and(possibleSnowIce.eq(0)) // No
    .and(possibleShadow.eq(0)) // No
  return image.updateMask(mask)
}

function bitwiseExtract(value, fromBit, toBit) {
  if (toBit === undefined)
    toBit = fromBit
  var maskSize = ee.Number(1).add(toBit).subtract(fromBit)
  var mask = ee.Number(1).leftShift(maskSize).subtract(1)
  return value.rightShift(fromBit).bitwiseAnd(mask)
}

https://code.earthengine.google.com/1e552b88ad6f27f12acf58adcc01b8ba