Hfrhyu

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"
)