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Make web requests to a Resonant GeoData instance.

Project description


rgd_client - Resonant GeoDataClient

The rgd_client Python package allows users to make web requests to a Resonant GeoData instance within a Python script.


pip install rgd-client


Search and display results

import json
import matplotlib.pyplot as plt
import numpy as np

from rgd_client import Rgdc

def plot_geojson(gjs, *args, **kwargs):
    points = np.array(gjs['coordinates'])
    if points.ndim == 3:
        points = points[0]
    if points.ndim == 1:
        points = points.reshape((1, points.size, ))
    return plt.plot(points[:,0], points[:,1], *args, **kwargs)

client = Rgdc(username='username', password='password')
bbox = {

q =, predicate='intersects')

for s in q:

plot_geojson(bbox, 'k--', label='Search Region')

for s in q:
    plot_geojson(s['footprint'], label=s['subentry_name'])

plt.title(f'Count: {len(q)}')

Inspect raster

Preview thumbnails of the raster

import imageio
from io import BytesIO

raster = client.get_raster(q[0])
plot_geojson(bbox, 'k--')
plot_geojson(raster['outline'], 'r')
load_image = lambda imbytes: imageio.imread(BytesIO(imbytes))

count = len(raster['parent_raster']['image_set']['images'])
for i in range(count):
    thumb_bytes = client.download_raster_thumbnail(q[0], band=i)
    thumb = load_image(thumb_bytes)
    plt.subplot(1, count, i+1)


Download Raster

Download the entire image set of the raster

import rasterio
from rasterio.plot import show

paths = client.download_raster(q[0])
rasters = [ for im in paths.images]
for i, src in enumerate(rasters):
    plt.subplot(1, len(rasters), i+1)
    ax = plt.gca()
    show(src, ax=ax)

Upload Processed Imagery/Raster

file_url = '...'  # Some already processed file that has been upload to S3

file = client.create_file_from_url(file_url)
image = client.create_image_from_file(file)
image_set = client.create_image_set([image, ])
raster = client.create_raster_from_image_set(image_set)

STAC Item Support

The Python client has a search endpoint specifically for Raster data that returns each record in the search results as a STAC Item.

q = client.search_raster_stac(query=json.dumps(bbox), predicate='intersects')

print(q[0])  # view result as STAC Item

# Download using the search result
paths = client.download_raster(q[0])

We can also upload new data in the STAC Item format. Here we simply pass back the same STAC Item JSON which will not actually do anything because RGD recognizes that these files are already present with a Raster.


Please note that the assets in the STAC Item must already be uploaded to a cloud storage provider with either s3:// or https:// URLs. Further, the images must have the data tag on each asset. e.g.:

    ... # other STAC Item fields
    'assets': {
        'image-15030': {
            'href': '',
            'title': 'GRANULE/L1C_T17SMS_A029738_20210302T161751/IMG_DATA/T17SMS_20210302T161201_B01.jp2',
            'eo:bands': [{'name': 'B1'}],
            'roles': ['data'],
        'image-15041': {
            'href': '',
            'title': 'GRANULE/L1C_T17SMS_A029738_20210302T161751/IMG_DATA/T17SMS_20210302T161201_B02.jp2',
            'eo:bands': [{'name': 'B1'}],
            'roles': ['data'],
        ...  # ancillary files can lack a role but we like to see `metadata` used.
        'ancillary-30687': {
            'href': '',
            'title': 'GRANULE/L1C_T17SMS_A029738_20210302T161751/QI_DATA/MSK_TECQUA_B03.gml',
            'roles': ['metadata'],

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