def reproj_roi(self, out_path, lonw, lone, lats, latn):
'''
根据给定的经纬度方位裁剪AMSR2 L3 数据
:param out_path:
:param lonw:
:param lone:
:param lats:
:param latn:
:return:
'''
corner_lon = [lonw, lone, lone, lonw]
corner_lat = [lats, lats, latn, latn]
corner_xy = self.proj_to_nsidc_sea_ice_stere_n(corner_lon, corner_lat)
min_x = corner_xy[0].min()
max_x = corner_xy[0].max()
min_y = corner_xy[1].min()
max_y = corner_xy[1].max()
start_x = min_x - self.lu_x
end_x = max_x - self.lu_x
start_x_pixel = int(start_x / self.gsd)
end_x_pixel = int(np.ceil(end_x / self.gsd))
if start_x_pixel < 0:
start_x_pixel = 0
if end_x_pixel >= self.data_shape[1]:
end_x_pixel = self.data_shape[1] - 1
start_y = self.lu_y - max_y
end_y = self.lu_y - min_y
start_y_pixel = int(start_y / self.gsd)
end_y_pixel = int(np.ceil(end_y / self.gsd))
if start_y_pixel < 0:
start_y_pixel = 0
if end_y_pixel >= self.data_shape[0]:
end_y_pixel = self.data_shape[0] - 1
# 获得区域内的亮温
sub_nh_89h = self.nh_89h[start_y_pixel:end_y_pixel,
start_x_pixel:end_x_pixel].copy()
sub_nh_89v = self.nh_89v[start_y_pixel:end_y_pixel,
start_x_pixel:end_x_pixel].copy()
origin_x = start_x_pixel * self.gsd + self.lu_x
origin_y = self.lu_y - start_y_pixel * self.gsd
file_format = 'GTiff'
driver = gdal.GetDriverByName(file_format)
dst_ds = driver.Create(out_path,
xsize=sub_nh_89h.shape[1],
ysize=sub_nh_89h.shape[0],
bands=2,
eType=gdal.GDT_Int32)
srs = NSR(3411)
dst_ds.SetProjection(srs.ExportToWkt())
dst_ds.SetGeoTransform([origin_x, self.gsd, 0, origin_y, 0, -self.gsd])
band1 = dst_ds.GetRasterBand(1)
band1.WriteArray(sub_nh_89h)
band2 = dst_ds.GetRasterBand(2)
band2.WriteArray(sub_nh_89v)
dst_ds = None
def test_init_from_EPSG(self):
nsr = NSR(4326)
self.assertEqual(type(nsr), NSR)
self.assertEqual(nsr.Validate(), 0)
self.assertTrue('4326' in nsr.ExportToWkt())
def reproj_roi(self, out_path, gsd, lonw, lone, lats, latn, res='H'):
'''
:param out_path:
:param gsd:
:param lonw:
:param lone:
:param lats:
:param latn:
:return:
'''
corner_lon = [lonw, lone, lone, lonw]
corner_lat = [lats, lats, latn, latn]
corner_xy = self.proj_to_wgs84_nsidc_sea_ice_stere_n(
corner_lon, corner_lat)
min_x = corner_xy[0].min()
max_x = corner_xy[0].max()
min_y = corner_xy[1].min()
max_y = corner_xy[1].max()
img_width = int(np.ceil((max_x - min_x) / gsd))
img_height = int(np.ceil((max_y - min_y) / gsd))
img_pixel_crd_x = np.linspace(min_x, max_x, img_width)
img_pixel_crd_y = np.linspace(max_y, min_y, img_height)
grid_crd_x, grid_crd_y = np.meshgrid(img_pixel_crd_x, img_pixel_crd_y)
grid_lonlat = self.proj_to_wgs84_nsidc_sea_ice_stere_n(
grid_crd_x.flatten(), grid_crd_y.flatten(), True)
grid_lon = grid_lonlat[0]
grid_lat = grid_lonlat[1]
grid_lon_idx = (grid_lon - self.min_lon) / self.mask_res
grid_lat_idx = (grid_lat - self.min_lat) / self.mask_res
grid_lon_idx = grid_lon_idx.astype(np.int)
grid_lat_idx = grid_lat_idx.astype(np.int)
gpi = self.mask[grid_lat_idx, grid_lon_idx]
gpi = gpi.reshape(grid_crd_x.shape)
if res == 'H':
hr_xy = self.proj_to_wgs84_nsidc_sea_ice_stere_n(
self.hr_lon.flatten(), self.hr_lat.flatten())
hr_x = hr_xy[0].reshape(self.hr_shape)
hr_y = hr_xy[1].reshape(self.hr_shape)
hr_pts = np.asarray(list(zip(hr_x.flatten(), hr_y.flatten())))
hr_value = self.bt_89h.flatten()
dst_pts = np.asarray(
list(zip(grid_crd_x.flatten(), grid_crd_y.flatten())))
dst_value = interpolate.griddata(hr_pts,
hr_value,
dst_pts,
method='linear',
rescale=True)
dst_value = dst_value.reshape(grid_crd_x.shape)
else:
lr_xy = self.proj_to_wgs84_nsidc_sea_ice_stere_n(
self.lr_lon.flatten(), self.lr_lat.flatten())
lr_x = lr_xy[0].reshape(self.lr_shape)
lr_y = lr_xy[1].reshape(self.lr_shape)
lr_pts = np.asarray(list(zip(lr_x.flatten(), lr_y.flatten())))
lr_value = self.bt_36h.flatten()
dst_pts = np.asarray(
list(zip(grid_crd_x.flatten(), grid_crd_y.flatten())))
dst_value = interpolate.griddata(lr_pts,
lr_value,
dst_pts,
method='cubic',
rescale=True)
dst_value = dst_value.reshape(grid_crd_x.shape)
dst_value[~gpi] = np.nan
file_format = 'GTiff'
driver = gdal.GetDriverByName(file_format)
dst_ds = driver.Create(out_path,
xsize=img_width,
ysize=img_height,
bands=1,
eType=gdal.GDT_Byte)
srs = NSR(3413)
dst_ds.SetProjection(srs.ExportToWkt())
dst_ds.SetGeoTransform([min_x, gsd, 0, max_y, 0, -gsd])
img_uint8 = get_uint8_image(dst_value, None, None, 1, 99)
# img_uint8 = unsharp_masking_sharp(img_uint8)
# img_uint8 = laplcian_sharp(img_uint8)
dst_ds.WriteRaster(0, 0, img_width, img_height, img_uint8.tostring())
dst_ds = None