Skip to content

Commit cc3788e

Browse files
jpswinskijpswinski
committed
Merge branch 'development' into main
2 parents 3c93f89 + 586bf2c commit cc3788e

File tree

2 files changed

+226
-0
lines changed

2 files changed

+226
-0
lines changed

‎utils/hls.py

Lines changed: 179 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,179 @@
1+
#
2+
# Test for landsat stac server
3+
import geopandas as gpd
4+
import requests as r
5+
import boto3
6+
import rasterio as rio
7+
import rioxarray
8+
import os
9+
from rasterio.session import AWSSession
10+
11+
def BuildSquare(lon, lat, delta):
12+
c1 = [lon + delta, lat + delta]
13+
c2 = [lon + delta, lat - delta]
14+
c3 = [lon - delta, lat - delta]
15+
c4 = [lon - delta, lat + delta]
16+
geometry = {"type": "Polygon", "coordinates": [[ c1, c2, c3, c4, c1 ]]}
17+
return geometry
18+
19+
20+
s3_cred_endpoint = {
21+
'lpdaac':'https://data.lpdaac.earthdatacloud.nasa.gov/s3credentials'
22+
}
23+
24+
def get_temp_creds(provider):
25+
return r.get(s3_cred_endpoint[provider]).json()
26+
27+
28+
29+
###############################################################################
30+
# MAIN
31+
###############################################################################
32+
33+
if __name__ == '__main__':
34+
35+
stac = 'https://cmr.earthdata.nasa.gov/stac/' # CMR-STAC API Endpoint
36+
stac_response = r.get(stac).json() # Call the STAC API endpoint
37+
38+
# for s in stac_response: print(s)
39+
40+
print(f"You are now using the {stac_response['id']} API (STAC Version: {stac_response['stac_version']}). \n{stac_response['description']}")
41+
print(f"There are {len(stac_response['links'])} STAC catalogs available in CMR.")
42+
43+
stac_lp = [s for s in stac_response['links'] if 'LP' in s['title']] # Search for only LP-specific catalogs
44+
45+
# LPCLOUD is the STAC catalog we will be using and exploring today
46+
lp_cloud = r.get([s for s in stac_lp if s['title'] == 'LPCLOUD'][0]['href']).json()
47+
# for l in lp_cloud: print(f"{l}: {lp_cloud[l]}")
48+
49+
lp_links = lp_cloud['links']
50+
for l in lp_links:
51+
try:
52+
print(f"{l['href']} is the {l['title']}")
53+
except:
54+
print(f"{l['href']}")
55+
56+
57+
lp_collections = [l['href'] for l in lp_links if l['rel'] == 'collections'][0] # Set collections endpoint to variable
58+
collections_response = r.get(f"{lp_collections}").json() # Call collections endpoint
59+
print(f"This collection contains {collections_response['description']} ({len(collections_response['collections'])} available)")
60+
61+
collections = collections_response['collections']
62+
# print(collections[1])
63+
64+
# Search available version 2 collections for HLS and print them out
65+
hls_collections = [c for c in collections if 'HLS' in c['id'] and 'v2' in c['id']]
66+
for h in hls_collections:
67+
print(f"{h['title']} has an ID (shortname) of: {h['id']}")
68+
69+
l30 = [h for h in hls_collections if 'HLSL30' in h['id'] and 'v2.0' in h['id']][0] # Grab HLSL30 collection
70+
for l in l30['extent']: # Check out the extent of this collection
71+
print(f"{l}: {l30['extent'][l]}")
72+
73+
l30_id = 'HLSL30.v2.0'
74+
print(f"HLS L30 Start Date is: {l30['extent']['temporal']['interval'][0][0]}")
75+
76+
l30_items = [l['href'] for l in l30['links'] if l['rel'] == 'items'][0] # Set items endpoint to variable
77+
print(l30_items)
78+
l30_items_response = r.get(f"{l30_items}").json() # Call items endpoint
79+
# print(l30_items_response)
80+
# l30_item = l30_items_response['features'][0] # select first item (10 items returned by default)
81+
# print(l30_item)
82+
83+
# for i, l in enumerate(l30_items_response['features']):
84+
# print(f"Item at index {i} is {l['id']}")
85+
# print(f"Item at index {i} is {l['properties']['eo:cloud_cover']}% cloudy.")
86+
87+
lp_search = [l['href'] for l in lp_links if l['rel'] == 'search'][0] # Define the search endpoint
88+
# lp_search is https://cmr.earthdata.nasa.gov/stac/LPCLOUD/search
89+
90+
# Set up a dictionary that will be used to POST requests to the search endpoint
91+
params = {}
92+
93+
lim = 100
94+
params['limit'] = lim # Add in a limit parameter to retrieve 100 items at a time.
95+
print(params)
96+
search_response = r.post(lp_search, json=params).json() # send POST request to retrieve first 100 items in the STAC collection
97+
print(f"{len(search_response['features'])} items found!")
98+
99+
# Bring in the farm field region of interest
100+
field = gpd.read_file('/home/elidwa/hls-tutorial/Field_Boundary.geojson')
101+
print(field)
102+
fieldShape = field['geometry'][0] # Define the geometry as a shapely polygon
103+
bbox = f'{fieldShape.bounds[0]},{fieldShape.bounds[1]},{fieldShape.bounds[2]},{fieldShape.bounds[3]}' # Defined from ROI bounds
104+
params['bbox'] = bbox # Add ROI to params
105+
date_time = "2021-07-01T00:00:00Z/2021-08-31T23:59:59Z" # Define start time period / end time period
106+
params['datetime'] = date_time
107+
params['collections'] = l30_id
108+
109+
hls_items = r.post(lp_search, json=params).json() # Send POST request with datetime included
110+
print(f"{len(hls_items['features'])} items found!")
111+
hls_items = hls_items['features']
112+
113+
h = hls_items[0]
114+
# print(h)
115+
116+
evi_band_links = []
117+
118+
# Define which HLS product is being accessed
119+
# if h['assets']['browse']['href'].split('/')[4] == 'HLSS30.015':
120+
# evi_bands = ['B8A', 'B04', 'B02', 'Fmask'] # NIR RED BLUE Quality for S30
121+
# else:
122+
# evi_bands = ['B05', 'B04', 'B02', 'Fmask'] # NIR RED BLUE Quality for L30
123+
124+
evi_bands = ['B05', 'B04', 'B02', 'Fmask'] # NIR RED BLUE Quality for L30
125+
126+
# Subset the assets in the item down to only the desired bands
127+
for a in h['assets']:
128+
if any(b == a for b in evi_bands):
129+
evi_band_links.append(h['assets'][a]['href'])
130+
for e in evi_band_links: print(e)
131+
132+
# The result of this seach is:
133+
# https://data.lpdaac.earthdatacloud.nasa.gov/lp-prod-protected/HLSL30.020/HLS.L30.T10TEK.2021183T185121.v2.0/HLS.L30.T10TEK.2021183T185121.v2.0.B02.tif
134+
# https://data.lpdaac.earthdatacloud.nasa.gov/lp-prod-protected/HLSL30.020/HLS.L30.T10TEK.2021183T185121.v2.0/HLS.L30.T10TEK.2021183T185121.v2.0.Fmask.tif
135+
# https://data.lpdaac.earthdatacloud.nasa.gov/lp-prod-protected/HLSL30.020/HLS.L30.T10TEK.2021183T185121.v2.0/HLS.L30.T10TEK.2021183T185121.v2.0.B04.tif
136+
# https://data.lpdaac.earthdatacloud.nasa.gov/lp-prod-protected/HLSL30.020/HLS.L30.T10TEK.2021183T185121.v2.0/HLS.L30.T10TEK.2021183T185121.v2.0.B05.tif
137+
#
138+
# create an s3 list
139+
s3List = []
140+
141+
for e in evi_band_links:
142+
# print(e)
143+
s3path = e.replace("https://data.lpdaac.earthdatacloud.nasa.gov/", "s3://")
144+
# print(s3path)
145+
s3List.append(s3path)
146+
147+
for e in s3List:
148+
print(e)
149+
150+
151+
if os.path.isfile(os.path.expanduser('~/.netrc')):
152+
# For Githhub CI, we can use ~/.netrc
153+
temp_creds_req = get_temp_creds('lpdaac')
154+
else:
155+
# ADD temporary credentials here
156+
temp_creds_req = {}
157+
158+
session = boto3.Session(aws_access_key_id=temp_creds_req['accessKeyId'],
159+
aws_secret_access_key=temp_creds_req['secretAccessKey'],
160+
aws_session_token=temp_creds_req['sessionToken'],
161+
region_name='us-west-2')
162+
163+
164+
# NOTE: Using rioxarray assumes you are accessing a GeoTIFF
165+
rio_env = rio.Env(AWSSession(session),
166+
GDAL_DISABLE_READDIR_ON_OPEN='TRUE',
167+
GDAL_HTTP_COOKIEFILE=os.path.expanduser('~/cookies.txt'),
168+
GDAL_HTTP_COOKIEJAR=os.path.expanduser('~/cookies.txt'))
169+
rio_env.__enter__()
170+
171+
172+
for e in s3List:
173+
print(e)
174+
if '.tif' in e:
175+
da = rioxarray.open_rasterio(e)
176+
print(da)
177+
178+
179+
print("Done!")

‎utils/landsat.py

Lines changed: 47 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,47 @@
1+
#
2+
# Test for landsat stac server
3+
import geopandas as gpd
4+
import numpy as np
5+
import pandas as pd
6+
import pystac
7+
from pystac_client import Client
8+
9+
10+
def BuildSquare(lon, lat, delta):
11+
c1 = [lon + delta, lat + delta]
12+
c2 = [lon + delta, lat - delta]
13+
c3 = [lon - delta, lat - delta]
14+
c4 = [lon - delta, lat + delta]
15+
geometry = {"type": "Polygon", "coordinates": [[ c1, c2, c3, c4, c1 ]]}
16+
return geometry
17+
18+
19+
###############################################################################
20+
# MAIN
21+
###############################################################################
22+
23+
if __name__ == '__main__':
24+
25+
stacServer = "https://landsatlook.usgs.gov/stac-server"
26+
LandsatSTAC = Client.open(stacServer, headers=[])
27+
28+
for collection in LandsatSTAC.get_collections():
29+
print(collection)
30+
31+
geometry = BuildSquare(-59.346271, -34.233076, 0.04)
32+
timeRange = '2019-06-01/2021-06-01'
33+
34+
LandsatSearch = LandsatSTAC.search (
35+
intersects = geometry,
36+
datetime = timeRange,
37+
query = ['eo:cloud_cover95'],
38+
collections = ["landsat-c2l2-sr"] )
39+
40+
Landsat_items = [i.to_dict() for i in LandsatSearch.get_items()]
41+
print(f"{len(Landsat_items)} Landsat scenes fetched")
42+
43+
for item in Landsat_items:
44+
red_href = item['assets']['red']['href']
45+
red_s3 = item['assets']['red']['alternate']['s3']['href']
46+
# print(red_href)
47+
print(red_s3)

0 commit comments

Comments
 (0)