计算多边形内不同波段的百分比

Question

我目前正在使用来自 GEE (USGS/GFSAD1000_V0) 的数据集，目的是将其转置到我在所有这些之前已经确定的一组多边形上。我现在正在尝试计算某个多边形内不同值（0-9）的像素百分比并将其打印出来。

import ee
import numpy as np

ee.Initialize()

polygon_version = '(SOURCE)'
land_polygons = ee.FeatureCollection(f'users/(SOURCE)/{polygon_version}_poly_land')

def Landcover_Crops_nr(polygons):
    dataset = ee.Image("USGS/GFSAD1000_V0").clip(polygons)
    type_crop = dataset.select("landcover")
    arr = np.array(type_crop)

    rawres = type_crop.getInfo()["features"]
    res = {
        x["properties"]["id"]: {
            "id": x["properties"]["id"],
            "area": float(x["properties"]["area"]),
            "center_lat": x["properties"]["center_lat"],
            "crop_area": x["properties"]["sum"],
        }
        for x in rawres
    }

    return res
values, frequencies= np.unique(arr, return_counts=True)
sum = np.sum(frequencies)
percentages = [x/sum*100 for x in frequencies]
dfgen = Landcover_Crops_nr(land_polygons)
dfgen.to_csv(f'{polygon_version}_Crops.csv', index=False)
print (dfgen)

我以前尝试过，但正如您所见，它只会关注 9 值，而像这样手动执行对于全球数据集来说不是一个选项

Answer 1

尝试使用 numpy 库。 例如

import numpy as np

# generate an array of size 10x10 with values (0-9)
arr = np.random.randint(10, size=(10, 10))

# get unique values with frequencies
values, frequencies= np.unique(arr, return_counts=True) 

# calculate sum of frequencies
sum = np.sum(frequencies)

# calculate percentages
percentages = [x/sum*100 for x in frequencies]

# Example

# print(values)
# [0, 1, ...,9 ]

# print(percentages)
# [25.0, 15.0, ..., 2.5]

要在您的方法中采用这种方法，请尝试使用

arr = np.array(type_crop)

改为

arr = np.random.randint(10, size=(10, 10))

假设您的 type_crop 是二维数组。