2

I tried to perform a pixel based time series change detection algorithm in GEE for a defined region, so i intended to extract every pixel time series values into something like a table or matrix, and implement the pixel based algorithm by rows or columns.

I find out a similar question and rewrite the code by following the solution given by Nicholas Clinton as follows:

#define the interested path and row to select the images
path = 120
row = 32

#define the time period to filter the images you want
start = ee.Date.fromYMD(1983, 1, 1)
finish = ee.Date.fromYMD(2019, 1, 1)

#rename the OLI images
l8_bandlist = ee.List(['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B10', 'pixel_qa'])
rename_list = ee.List(['blue', 'green', 'red', 'nir', 'swir1', 'swir2', 'tbb', 'qa'])

#build the image collection
l8_sr = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR').filter(\
ee.Filter.eq('WRS_PATH', path)).filter(ee.Filter.eq('WRS_ROW', row)).filterDate(\
start, finish).select(l8_bandlist, rename_list).sort('system:time_start')

# using shapefile to restrict the area of interest
shp = ee.FeatureCollection('users/myzhenghrsc/testarea').geometry()

#reduce the region restricted by uploaded shapfile into points correspond to OLI pixels
dictionary = ee.Image.pixelLonLat().reduceRegion(
reducer=ee.Reducer.toCollection(['longitude', 'latitude']),
geometry=shp,
scale=30)

#function to build the piont featureCollection
def __rebuildpoints(feature):
lon = feature.get('longitude'),
lat = feature.get('latitude'),
return ee.Feature(ee.Geometry.Point([lon, lat])), {
    'featureID':
    ee.Number(lon).multiply(1000).round().format('%5.0f').cat('_').cat(
        ee.Number(lat).multiply(1000).round().format('%5.0f'))
}

#perform the function above
points = ee.FeatureCollection(dictionary.get('features')).map(__rebuildpoints)

def triplets(image):
  def feature(value):
    return value.set({
        'imageID': pointvalue.id(),
        'timeMillis': pointvalue.get('system:time_start')
    })

  pointvalue = image.reduceRegion({
    'collection': points,
    'reducer': ee.Reducer.first().setOutputs(image.bandNames()),
    'scale': 30
})
return pointvalue

turplets = l8_sr.select('red').map(triplets)

def newformat(table, rowId, colId, rowProperty, colProperty):
rows = table.distinct(rowId),
joined = ee.Join.saveAll('matches').apply({
    primary=rows,
    secondary=table,
    condition=ee.Filter.equals({
        leftField=rowId,
        rightField=colId
    })
})

def __row(row):
    def __feature(feature):
        feature = ee.Feature(feature),
        return [feature.get(colId), feature.get(colProperty)].flatten()

    values = ee.List(row.get('matches')).map(__feature)
    return row.select([rowId, rowProperty]).set(ee.Dictionary(values))

return joined.map(__row)


results = newformat(triplets, 'imageID', 'featureID', 'timemillis', 'RED')

But i got a error as follows when i perform this code:

Invalid argument specified for ee.Number(): ee.ComputedObject({ "type": "Invocation", "arguments": { "object": { "type": "ArgumentRef", "value": null }, "property": "longitude" }, "functionName": "Element.get" })

0

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Browse other questions tagged or ask your own question.