[GIS] Get the correct transform from bounding box with Rasterio

affine transformationextentspythonrasteriosentinel-hub

I have image as numpy array with no projection or geographical data and I have information of the bouding box of this numpy array (the image suppose to match perfectly the bbox).
The bbox is sentinelhub.geometry.BBox type.

I have the following informtion about the bbox:

bbox_size
>>>(850, 1279) #it has 1279 rows and 850 columns, not to be confused

bbox_coords_wgs84
>>>[-56.413932589, -12.93287647, -56.335907465, -12.81704823]  #lower left, upper right

The problem is that whenever I'm trying to save my numpy array, I believe there is problem with the transform as I get it very disorted.
I'm using the following for the transform:

transform=rasterio.transform.from_bounds(*bbox, width= bbox_size[1], height= bbox_size[0])
transform
>>>Affine(6.1004788115715275e-05, 0.0, -56.413932589,
       0.0, -0.00013626851764705978, -12.81704823)

and the result look like this : (the red crosses are where there real lower left and upper right suppose to be:

Why is this happens? I believe there is something very basic that i'm missing here

Best Answer

You confused the height & width parameters and are passing them reversed. You use columns=height and rows=width when you should be using columns=width and rows=height. Change your code to:

transform=rasterio.transform.from_bounds(*bbox, width=bbox_size[0], height= bbox_size[1])

Related Solutions

[GIS] Defining Affine transform with rasterio

If you do this:

>>>import rasterio
>>>dir(rasterio)
['Affine', 'Band', 'DatasetReader', 'Env', 'MemoryFile', 'NullHandler', 'Path', 'RasterioIOError', '__all__', '__builtins__', '__cached__', '__doc__', '__file__', '__gdal_version__', '__loader__', '__name__', '__package__', '__path__', '__spec__', '__version__', '_base', '_crs', '_env', '_err', '_features', '_io', '_shim', '_transform', '_warp', 'absolute_import', 'band', 'bool_', 'check_dtype', 'compat', 'complex_', 'contextmanager', 'control', 'coords', 'crs', 'default_gtiff_profile', 'drivers', 'dtypes', 'ensure_env_with_credentials', 'enums', 'env', 'errors', 'float32', 'float64', 'gdal_version', 'get_writer_for_driver', 'get_writer_for_path', 'guard_transform', 'int16', 'int32', 'int8', 'io', 'is_blacklisted', 'log', 'logging', 'namedtuple', 'open', 'pad', 'parse_path', 'path', 'profiles', 'rasterio', 'sample', 'sbyte', 'session', 'string_types', 'transform', 'ubyte', 'uint16', 'uint32', 'uint8', 'vrt', 'windows']

it is corroborated that correct method is 'Affine'. So, by using following command you have desired answer without any error.

>>>rasterio.Affine(-101.7359960059834, 10.0, 0, 20.8312118894487, 0, -10.0)
Affine(-101.7359960059834, 10.0, 0.0,
       20.8312118894487, 0.0, -10.0)

You can get same result as follows:

>>>transform = (-101.7359960059834, 10.0, 0, 20.8312118894487, 0, -10.0)
>>>rasterio.Affine(transform[0],transform[1],transform[2],transform[3],transform[4],transform[5] )
Affine(-101.7359960059834, 10.0, 0.0,
       20.8312118894487, 0.0, -10.0)

With a help to rasterio.Affine;

>>>help(rasterio.Affine)
Help on class Affine in module affine:

class Affine(Affine)
 |  Affine(a, b, c, d, e, f)
 |  
 |  Two dimensional affine transform for 2D linear mapping.
 |  
 |  Parameters
 |  ----------
 |  a, b, c, d, e, f : float
.
.
.

So, when you do:

>>>rasterio.Affine(transform)
Traceback (most recent call last):
  File "/usr/lib/python3.7/code.py", line 90, in runcode
    exec(code, self.locals)
  File "<input>", line 1, in <module>
TypeError: __new__() missing 5 required positional arguments: 'b', 'c', 'd', 'e', and 'f'

you got an error because you require 6 positional arguments as float (not a tuple).

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