image_stats_by_zone() Error

[caomy7]

Environment Information

Please run the following code on your computer and share the output with us so that we can better debug your issue:

import geemap
geemap.Report()

Description

Describe what you were trying to get done.
Tell us what happened, what went wrong, and what you expected to happen.

I want to get the SOS information based on the land cover.

I get a bug as follow when I run the code in the North America area.

{'type': 'Projection', 'crs': 'SR-ORG:6974', 'transform': [463.3127165279165, 0, -20015109.354, 0, -463.3127165279167, 10007554.677003]}
{'type': 'Projection', 'crs': 'SR-ORG:6974', 'transform': [463.3127165279165, 0, -20015109.354, 0, -463.3127165279167, 10007554.677003]}

HttpError Traceback (most recent call last)
/usr/local/lib/python3.10/dist-packages/ee/data.py in _execute_cloud_call(call, num_retries)
394 try:
--> 395 return call.execute(num_retries=num_retries)
396 except googleapiclient.errors.HttpError as e:

6 frames
HttpError: <HttpError 400 when requesting https://earthengine.googleapis.com/v1/projects/earthengine-legacy/value:compute?prettyPrint=false&alt=json returned "Unable to transform edge (6144.000000, 0.000000 to 6144.000000, 0.000977) from SR-ORG:6974 PLANAR [4633.127165279165, 0.0, -2.0015109354E7, 0.0, -4633.127165279167, 1.0007554677003E7] to EPSG:4326.". Details: "Unable to transform edge (6144.000000, 0.000000 to 6144.000000, 0.000977) from SR-ORG:6974 PLANAR [4633.127165279165, 0.0, -2.0015109354E7, 0.0, -4633.127165279167, 1.0007554677003E7] to EPSG:4326.">

During handling of the above exception, another exception occurred:

EEException Traceback (most recent call last)
/usr/local/lib/python3.10/dist-packages/ee/data.py in _execute_cloud_call(call, num_retries)
395 return call.execute(num_retries=num_retries)
396 except googleapiclient.errors.HttpError as e:
--> 397 raise _translate_cloud_exception(e) # pylint: disable=raise-missing-from
398
399

EEException:

What I Did

#########  1. get the SOS info from MODIS
import ee
import geemap
import pandas as pdc
import datetime

# 初始化Earth Engine
ee.Initialize()
Map = geemap.Map()

Map.add_basemap('HYBRID')
# Map.add_basemap()
daymet = ee.FeatureCollection("users/Molly_HK/daymet_area")
roi = daymet


year1 = 2019 ###c
start = str(year1)+'-01-01'
end = str(year1)+'-12-31'

collection = ee.ImageCollection('MODIS/061/MCD12Q2').filterBounds(roi).filter(ee.Filter.date(start, end));

projection0 = collection.first().projection()
print(projection0.getInfo())


# collection = ee.ImageCollection('MODIS/061/MOD09Q1').filterBounds(roi).filterDate(start, end)
lc = ee.ImageCollection('MODIS/061/MCD12Q1').filterBounds(roi).filter(ee.Filter.date(start, end)).first()
lc_unique = lc.select('LC_Type1').lte(12) #cropland, 植被
# lc_unique = lc.select('LC_Type1').lte(14) #cropland, 植被

def clip_mask(image):
  lc = image.updateMask(lc_unique)
  return lc

dataset = collection.map(clip_mask)


projectionlc = lc_unique.projection()
print(projectionlc.getInfo())

projectiondata = dataset.first().projection()
print(projectiondata.getInfo())

#
Greenup_1 = dataset.select('Greenup_1').first().clip(roi);
Dormancy_1 = dataset.select('Dormancy_1').first().clip(roi);


MOD12BGN = datetime.date(1970, 1, 1)
print(MOD12BGN)
MOD12END = datetime.date(year1 - 1, 12, 31)
print(MOD12END)
MOD12DAY = (MOD12END - MOD12BGN).days
print(MOD12DAY)

SOS = Greenup_1.subtract(MOD12DAY)

projectionSOS = SOS.projection()
print(projectionSOS.getInfo())


palette = ['#000000', '#060A24', '#10174E', '#1A2A78', '#243EA2', '#2E52CC', '#3A6CFF', '#6D8EFF', '#9BAEFF', '#C5CDFF',
           '#E8E9FF', '#FFF4D6', '#FFE5A3', '#FFD271', '#FFC33F', '#FFB10D', '#FF9C00', '#FF8800', '#FF7300', '#FF5E00',
           '#FF4800', '#FF3300', '#FF1D00', '#FF0700', '#FF0000']


# Add to map
viz = {
  'palette': palette,
  'min': 1,
  'max': 365,
}

# # Map.addLayer(roi, {}, 'ROI')

# Map.addLayer(Greenup_1, viz, 'SOS', True)
Map.addLayer(SOS, viz, 'SOS', True)
Map.add_colorbar(viz)


# Map.addLayer(Dormancy_1,viz, 'Dormancy_1', False)

Map.addLayer(roi, {}, 'roi', False)
Map.centerObject(roi,7)
Map


#########  2. Caculating the result#################


# 获取图像属性
projection = SOS.projection()
print(projection.getInfo())

lc = ee.ImageCollection('MODIS/061/MCD12Q1').first().select('LC_Type1')
projection1 = lc.projection()
print(projection1.getInfo())

# landcover = ee.Image("USGS/NLCD_RELEASES/2019_REL/NLCD/2019").select('landcover')

stats = geemap.image_stats_by_zone(SOS,lc,reducer = "MEAN")
stats

[giswqs]

This is an issue caused by the projection of MODIS data. See this.