.ipynb .pdf

Contents

Convert from Vector to Raster

Written by Men Vuthy, 2022

---

Dataset

• Vector: H30植物群落.shp

• Reference raster: kano_20180429_wgs84.tiff

Import necessary modules

!pip install rasterio
!pip install geopandas

import os
import numpy as np
import rasterio
from rasterio.features import rasterize
from rasterio.transform import from_bounds
import geopandas as gpd
import matplotlib.pyplot as plt

Mount drive

from google.colab import drive
drive.mount('/content/drive')

Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount("/content/drive", force_remount=True).

cd /content/drive/MyDrive/Colab Notebooks/Z. Other topics/Convert shapefile to raster

/content/drive/MyDrive/Colab Notebooks/Z. Other topics/Convert shapefile to raster

Load dataset

# Load raster image for reference
image_ref = rasterio.open('data/kano_20180429_wgs84.tiff')

# Load survey data shapefile or json file
geo_survey = gpd.read_file('data/水国/H30植物群落.shp').to_crs(image_ref.crs)

geo_survey

	Id	code	area_ha	基本分類	基本分類No	群落コード	群落表示コ	群落名	lyr_code	調査管理番	河川コード	調査年度	調査回	調査年月日	表示用	geometry
0	0	02	0.042844	沈水植物群落	1	1003	013	ホザキノフサモ群落	WA8312	R2018_85_11350_3_U29358	9-85-501-001-000-2	2018	1	20181105	None	POLYGON ((138.93902 35.05341, 138.93902 35.053...
1	0	02	0.015477	沈水植物群落	1	1003	013	ホザキノフサモ群落	WA8312	R2018_85_11350_3_U29358	9-85-501-001-000-2	2018	1	20181105	None	POLYGON ((138.93657 35.06657, 138.93655 35.066...
2	0	02	0.013277	沈水植物群落	1	1003	013	ホザキノフサモ群落	WA8312	R2018_85_11350_3_U29358	9-85-501-001-000-2	2018	1	20181105	None	POLYGON ((138.93926 35.05376, 138.93923 35.053...
3	0	02	0.024026	沈水植物群落	1	1003	013	ホザキノフサモ群落	WA8312	R2018_85_11350_3_U29358	9-85-501-001-000-2	2018	1	20181105	None	POLYGON ((138.93913 35.05392, 138.93914 35.053...
4	0	02	0.062657	沈水植物群落	1	1003	013	ホザキノフサモ群落	WA8312	R2018_85_11350_3_U29358	9-85-501-001-000-2	2018	1	20181105	None	POLYGON ((138.93623 35.06915, 138.93621 35.069...
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
3188	0	79	0.009195	開放水面	28	28000	28	開放水面	WA8312	R2018_85_11350_3_U29358	9-85-501-001-000-2	2018	1	20181105	None	POLYGON ((138.95272 34.98724, 138.95272 34.987...
3189	0	79	0.016298	開放水面	28	28000	28	開放水面	WA8312	R2018_85_11350_3_U29358	9-85-501-001-000-2	2018	1	20181105	None	POLYGON ((138.94891 34.98141, 138.94895 34.981...
3190	0	82	0.011413	ヤナギ高木林	12	12008	128	ジャヤナギ−アカメヤナギ群集（低木林）	WA8312	R2018_85_11350_3_U29358	9-85-501-001-000-2	2018	1	20181105	ヤナギ	POLYGON ((138.93614 35.06527, 138.93615 35.065...
3191	0	76	0.078064	人工構造物	26	28000	262	コンクリート構造物	WA8312	R2018_85_11350_3_U29358	9-85-501-001-000-2	2018	1	20181105	None	POLYGON ((138.90882 35.08336, 138.90879 35.083...
3192	0	76	0.082595	人工構造物	26	28000	262	コンクリート構造物	WA8312	R2018_85_11350_3_U29358	9-85-501-001-000-2	2018	1	20181105	None	POLYGON ((138.91149 35.08144, 138.91145 35.081...

3193 rows × 16 columns

Parameter Setting

Select the column to write vector value into pixel

# Define parameters
label_column = '基本分類No'

Convert from Vector to Raster

# Project the survey geo into same CRS as the reference image
geodata = geo_survey.to_crs(crs=image_ref.crs)

# Convert vector to raster
shape = image_ref.shape
transform = image_ref.transform
rasterize_array = rasterize(
    [(shape, label) for shape, label in zip(geodata['geometry'], geodata[label_column])],
    out_shape=shape,
    transform=transform,
    fill=0,
    all_touched=True,
    dtype=rasterio.float32)

# Plot rasterized shape
plt.figure(figsize=(8,10))
plt.imshow(rasterize_array, 'gray')
plt.show();

# Write rasterized array to image (.tif)
with rasterio.open(
    'rasterized-results.tif', 'w',
    driver='GTiff',
    dtype=rasterio.float32,
    nodata=0,
    count=1,
    width=rasterize_array.shape[1],
    height=rasterize_array.shape[0],
    transform=transform,
    crs=image_ref.crs
) as dst:
    dst.write(rasterize_array, indexes=1)

previous

Calculate daily average potential evaporation from 3-year dataset for Source Model

next

Google Earth Engine