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Copy pathDownload_Remote_Feature.py
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180 lines (162 loc) · 6.44 KB
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import ee
ee.Authenticate()
import requests
def download_BH(lat_min, lat_max, lon_min, lon_max, output_file):
ee.Initialize()
# 创建感兴趣区域 (ROI)
roi = ee.Geometry.Rectangle([lon_min, lat_min, lon_max, lat_max])
# 加载 建筑高度building height 图像集合
built = (
ee.ImageCollection("JRC/GHSL/P2023A/GHS_BUILT_H")
.filterBounds(roi)
.median()
)
url = built.clip(roi).getDownloadURL({
'scale': 100, # 分辨率 (米)
'region': roi.coordinates().getInfo(), # ROI 区域
'format': 'GeoTIFF' # 文件格式
})
# 下载数据到本地
# output_file = 'average_building_height_2018.tif'
response = requests.get(url, stream=True)
if response.status_code == 200:
with open(output_file, 'wb') as file:
for chunk in response.iter_content(chunk_size=1024):
file.write(chunk)
print(f"数据已下载到本地：{output_file}")
else:
print(f"下载失败，状态码：{response.status_code}")
def download_BV(lat_min, lat_max, lon_min, lon_max, output_file):
ee.Initialize()
# 创建感兴趣区域 (ROI)
roi = ee.Geometry.Rectangle([lon_min, lat_min, lon_max, lat_max])
# 加载 Sentinel-2 图像集合
built = (
ee.ImageCollection("JRC/GHSL/P2023A/GHS_BUILT_V")
.filterDate('2020-01-01', '2020-12-31') # 时间范围
.filterBounds(roi)
.median()
)
# 检查波段名称
print("波段名称：", built.bandNames().getInfo())
# 指定波段下载
band_name = "built_volume_total" # 替换为实际波段名称
url = built.select(band_name).clip(roi).getDownloadURL({
'scale': 100, # 分辨率 (米)
'region': roi.coordinates().getInfo(), # ROI 区域
'format': 'GeoTIFF' # 文件格式
})
response = requests.get(url, stream=True)
if response.status_code == 200:
with open(output_file, 'wb') as file:
for chunk in response.iter_content(chunk_size=1024):
file.write(chunk)
print(f"波段 {band_name} 数据已下载到本地：{output_file}")
else:
print(f"下载失败，状态码：{response.status_code}")
def download_BS(lat_min, lat_max, lon_min, lon_max, output_file):
ee.Initialize()
# 创建感兴趣区域 (ROI)
roi = ee.Geometry.Rectangle([lon_min, lat_min, lon_max, lat_max])
# 加载 Sentinel-2 图像集合
built = (
ee.ImageCollection("JRC/GHSL/P2023A/GHS_BUILT_S_10m")
.filterBounds(roi)
.median()
)
# 检查波段名称
print("波段名称：", built.bandNames().getInfo())
# 指定波段下载
band_name = "built_surface" # 替换为实际波段名称
url = built.select(band_name).clip(roi).getDownloadURL({
'scale': 100, # 分辨率 (米)
'region': roi.coordinates().getInfo(), # ROI 区域
'format': 'GeoTIFF' # 文件格式
})
# 下载数据到本地
response = requests.get(url, stream=True)
if response.status_code == 200:
with open(output_file, 'wb') as file:
for chunk in response.iter_content(chunk_size=1024):
file.write(chunk)
print(f"波段 {band_name} 数据已下载到本地：{output_file}")
else:
print(f"下载失败，状态码：{response.status_code}")
def download_S2_og(lat_min, lat_max, lon_min, lon_max, output_file):
ee.Initialize()
roi = ee.Geometry.Rectangle([lon_min, lat_min, lon_max, lat_max])
# 加载 Sentinel-2 图像集合，筛选云量小于 5%，并计算中位数
sentinel2 = (
ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')
.filterDate('2022-01-01', '2022-12-01') # 时间范围
.filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', 5)) # 云量过滤
.filterBounds(roi) # 感兴趣区域
.median()
)
print("波段名称：", sentinel2.bandNames().getInfo())
# 提取原始波段
bands_to_include = ['B11', 'B9', 'B8', 'B7', 'B6', 'B5', 'B4', 'B3', 'B1'] # 常用波段
# 将原始波段与计算的特征合并
features = sentinel2.select(bands_to_include)
print("合并后的波段：", features.bandNames().getInfo())
url = features.clip(roi).getDownloadURL({
'scale': 100, # 分辨率 (米)
'region': roi.coordinates().getInfo(), # ROI 区域
'format': 'GeoTIFF' # 文件格式
})
# 下载数据到本地
response = requests.get(url, stream=True)
if response.status_code == 200:
with open(output_file, 'wb') as file:
for chunk in response.iter_content(chunk_size=1024):
file.write(chunk)
print(f"数据已下载到本地：{output_file}")
else:
print(f"下载失败，状态码：{response.status_code}")
def download_pop(lat_min, lat_max, lon_min, lon_max, output_file):
ee.Initialize()
# 创建感兴趣区域 (ROI)
roi = ee.Geometry.Rectangle([lon_min, lat_min, lon_max, lat_max])
# 加载 建筑高度 图像集合
built = (
ee.ImageCollection("JRC/GHSL/P2023A/GHS_POP")
.filterDate('2020-01-01', '2020-12-31') # 时间范围
.filterBounds(roi)
.median()
)
url = built.clip(roi).getDownloadURL({
'scale': 100, # 分辨率 (米)
'region': roi.coordinates().getInfo(), # ROI 区域
'format': 'GeoTIFF' # 文件格式
})
# 下载数据到本地
response = requests.get(url, stream=True)
if response.status_code == 200:
with open(output_file, 'wb') as file:
for chunk in response.iter_content(chunk_size=1024):
file.write(chunk)
print(f"数据已下载到本地：{output_file}")
else:
print(f"下载失败，状态码：{response.status_code}")
lon_min, lon_max = -2.990, -1.660
lat_min, lat_max = 53.035, 54.000
output_file = 'your_Manchester_2020_pop.tif'
download_pop(lat_min, lat_max, lon_min, lon_max, output_file)
output_file = 'your_Manchester_2022_BV.tif'
download_BV(lat_min, lat_max, lon_min, lon_max, output_file)
output_file = 'your_Manchester_S2_2022_10bands.tif'
download_S2_og(lat_min, lat_max, lon_min, lon_max, output_file)
output_file = 'your_Manchester_BH_2022.tif'
download_BH(lat_min, lat_max, lon_min, lon_max, output_file)
'''
# ROI indice for London
lat_min = 51.137
lat_max = 52.335
lon_min = -0.8241
lon_max = 0.9728
#ROI indice for Barcelona
lat_min = 41.250
lat_max = 41.780
lon_min = 1.790
lon_max = 2.540
'''