array to tiff raster image with gdal

Question

Update

i try to follow this tutorial

but i dont know how can export to new tiff images slope/aspect with GDAL ?

the full code :

from __future__ import division
from osgeo import gdal
from matplotlib.colors import ListedColormap
from matplotlib import colors
import sys
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import math

filename = 'dem.tif'

def getResolution(rasterfn):
    raster = gdal.Open(rasterfn)
    geotransform = raster.GetGeoTransform()
    res = {"east-west": abs(geotransform[1]), 
           "north-south": abs(geotransform[5])}
    return res

def raster2array(rasterfn):
    raster = gdal.Open(rasterfn)
    band = raster.GetRasterBand(1)
    return band.ReadAsArray()

def getNoDataValue(rasterfn):
    raster = gdal.Open(rasterfn)
    band = raster.GetRasterBand(1)
    return band.GetNoDataValue()

data_array = raster2array(filename)
nodataval = getNoDataValue(filename)
resolution = getResolution(filename)
print(resolution)
print(nodataval)

print(type(data_array))
print(data_array.shape)

num_rows = data_array.shape[0]
num_cols = data_array.shape[1]

slope_array = np.ones_like(data_array) * nodataval
aspect_array = np.ones_like(data_array) * nodataval

for i in range(1, num_rows - 1):
    for j in range(1, num_cols - 1):
        a = data_array[i - 1][j - 1]
        b = data_array[i - 1][j]
        c = data_array[i - 1][j + 1]
        d = data_array[i][j - 1]
        e = data_array[i][j]
        f = data_array[i][j + 1]
        g = data_array[i + 1][j - 1]
        h = data_array[i + 1][j]
        q = data_array[i + 1][j + 1]

        vals = [a, b, c, d, e, f, g, h, q]

        if nodataval in vals:
            all_present = False
        else:
            all_present = True

        if all_present == True:
            dz_dx = (c + (2 * f) + q - a - (2 * d) - g) / (8 * resolution['east-west'])
            dz_dy = (g + (2 * h) + q - a - (2 * b) - c) / (8 * resolution['north-south'])
            dz_dx_sq = math.pow(dz_dx, 2)
            dz_dy_sq = math.pow(dz_dy, 2)

            rise_run = math.sqrt(dz_dx_sq + dz_dy_sq)
            slope_array[i][j] = math.atan(rise_run) * 57.29578

            aspect = math.atan2(dz_dy, (-1 * dz_dx)) * 57.29578
            if aspect < 0:
                aspect_array[i][j] = 90 - aspect
            elif aspect > 90:
                aspect_array[i][j] = 360 - aspect + 90
            else:
                aspect_array[i][j] = 90 - aspect

hist, bins = np.histogram(slope_array, bins=100, range=(0, np.amax(slope_array)))
width = 0.7 * (bins[1] - bins[0])
center = (bins[:-1] + bins[1:]) / 2
plt.bar(center, hist, align='center', width=width)
plt.xlabel('Slope (degrees)')
plt.ylabel('Frequency')
plt.show()

color_map = ListedColormap(['white', 'darkgreen', 'green', 'limegreen', 'lime', 
                            'greenyellow', 'yellow', 'gold', 
                            'orange', 'orangered', 'red'])

# range begins at negative value so that missing values are white
color_bounds = list(range(-3, math.ceil(np.amax(slope_array)), 1))
color_norm = colors.BoundaryNorm(color_bounds, color_map.N)

#Create the plot and colorbar
img = plt.imshow(slope_array, cmap = color_map, norm = color_norm)
cbar = plt.colorbar(img, cmap = color_map, norm = color_norm,
                   boundaries = color_bounds, ticks = color_bounds)

#Show the visualization
plt.axis('off')
plt.title("Slope (degrees)")
plt.show()
plt.close()

first trial to export i follow this tutorial ,but the slope in not correct have lower degrees from the original(using gis program)

import gdal, ogr, os, osr
import numpy as np


def array2raster(newRasterfn,rasterOrigin,pixelWidth,pixelHeight,array):

    cols = array.shape[1]
    rows = array.shape[0]
    originX = rasterOrigin[0]
    originY = rasterOrigin[1]

    driver = gdal.GetDriverByName('GTiff')
    outRaster = driver.Create(newRasterfn, cols, rows, 1, gdal.GDT_Byte)
    outRaster.SetGeoTransform((originX, pixelWidth, 0, originY, 0, pixelHeight))
    outband = outRaster.GetRasterBand(1)
    outband.WriteArray(array)
    outRasterSRS = osr.SpatialReference()
    outRasterSRS.ImportFromEPSG(4326)
    outRaster.SetProjection(outRasterSRS.ExportToWkt())
    outband.FlushCache()


def main(newRasterfn,rasterOrigin,pixelWidth,pixelHeight,array):
    reversed_arr = slope_array # reverse array so the tif looks like the array
    array2raster(newRasterfn,rasterOrigin,pixelWidth,pixelHeight,reversed_arr) # convert array to raster


if __name__ == "__main__":
    rasterOrigin = (-123.25745,45.43013)
    pixelWidth = 10
    pixelHeight = 10
    newRasterfn = 'test.tif'
    array = slope_array

main(newRasterfn,rasterOrigin,pixelWidth,pixelHeight,array)

second trial i follow this quest but i dont take some export

def array_to_raster(slope_array):
    """Array > Raster
    Save a raster from a C order array.
    :param array: ndarray
     """
    dst_filename = 'xxx.tiff'
    x_pixels = num_rows # number of pixels in x
    y_pixels = num_cols # number of pixels in y
    driver = gdal.GetDriverByName('GTiff')
    dataset = driver.Create(
           dst_filename,
           x_pixels,
           y_pixels,
           1,
           gdal.GDT_Float32, )
    dataset.GetRasterBand(1).WriteArray(array)
    dataset.FlushCache()  # Write to disk.
    return dataset, dataset.GetRasterBand(1) 

any idea

Answer 1

The error states exactly what the problem is. You are trying to multiply an int type by a NoneType (None). The most likely case is that nodataval is None, which would occur because the NoDataValue for filename's first raster band is not defined. Your print(nodataval) command should demonstrate that. Remember, printing None doesn't appear as the string 'None'. It appears as a blank or no character.

Your edits show that nodataval is None.