Changing spatial extent after affine transformation

Question

I have a GeoTIFF file of cropped agricultural plots that I am trying to rotate so that they are perpendicular to the image edges. The source image looks like this:

However, when I rotate the image using the Affine functions, the dimensions of the source image are retained, thereby cutting off part of the image as shown:

I have been unable to find a solution that adjusts the dimensions of the output image so that parts are not cut off. Is there a method for resolving this?

My code used is as follows:

import rasterio
from rasterio.plot import show
import rasterio.warp
from affine import Affine
from pprint import pprint
from rasterio.warp import calculate_default_transform, reproject, Resampling

# Takes GeoTIFF file and outputs center pixels
def get_center_pixel(img):
    height, width = img.height, img.width
    x_mid_pixel = width // 2
    y_mid_pixel = height // 2
    return x_mid_pixel, y_mid_pixel

raster = "clip.tif"
angle = 65
scale = 1

with rasterio.open(raster) as src:
    assert src.crs == 'EPSG:32617', 'Raster must have CRS=EPSG:4326'
    pivot = get_center_pixel(src)
    show(src)

    dst_transform = src.transform * Affine.rotation(angle, pivot) * Affine.scale(1)
    dst_meta = src.meta
    dst_meta['transform'] = dst_transform

    with rasterio.open("rotate.tif", 'w', **dst_meta) as dst:
        for i in range(1, src.count + 1):
            reproject(
                source=rasterio.band(src,i),
                destination=rasterio.band(dst, i),
                src_transform=src.transform,
                src_crs=src.crs,
                dst_transform=dst_transform,
                dst_crs=src.crs,
                resampling=Resampling.nearest
            )

Answer 1

The issue was that the dst image file was maintaining the same resolution. However, if the resolution of the output file is changed, an Affine.translation must be added to re-center the source image onto the new dimensions. Additionally, I added code to calculate the optimal dimensions of the output file based on the dimensions. The new script results in a rotated image that maintains its projection:

import rasterio
from rotate import get_center_pixel
from affine import Affine
from rasterio.warp import reproject, Resampling
import numpy as np

# Set the file path for the input and output GeoTIFF files
raster = r"raster path"
angle = -88

with rasterio.open(raster) as src:
    pivot = get_center_pixel(src)

    rows, cols = src.shape

    # Calculate the dimensions of the output raster based on the rotated dimensions of the input raster
    cos_theta = abs(np.cos(np.radians(angle)))
    sin_theta = abs(np.sin(np.radians(angle)))
    new_rows = int(cols * sin_theta + rows * cos_theta)
    new_cols = int(rows * sin_theta + cols * cos_theta)


    dst_transform = src.transform * Affine.rotation(angle, pivot=pivot) * Affine.scale(1) * Affine.translation(pivot[0] - new_cols//2,pivot[1] - new_rows // 2)

    kwargs = src.meta.copy()
    # kwargs['transform'] = dst_transform
    kwargs.update({
        'width': new_cols,
        'height': new_rows,
        'transform': dst_transform
    })

    with rasterio.open("output.tif", 'w', **kwargs) as dst:
        for i in range(1, src.count + 1):
            reproject(
                source=rasterio.band(src, i),
                destination=rasterio.band(dst, i),
                src_transform=src.transform,
                src_crs=src.crs,
                dst_transform=dst_transform,
                dst_crs=src.crs,
                resampling=Resampling.bilinear)