Updated scripts for aws-landsat

aws-landsat/process_sat.py

@@ -1,9 +1,10 @@
-#!/usr/bin/python3
+#!/Users/amandatan/miniconda3/envs/myenv/bin/python
 import os
 import rasterio
+import numpy as np
 
 print('Landsat on AWS:')
-filepath = 'http://landsat-pds.s3.amazonaws.com/c1/L8/042/034/LC08_L1TP_042034_20170616_20170629_01_T1/LC08_L1TP_042034_20170616_20170629_01_T1_B4.TIF'
+filepath = 'https://landsat-pds.s3.amazonaws.com/c1/L8/042/034/LC08_L1TP_042034_20170616_20170629_01_T1/LC08_L1TP_042034_20170616_20170629_01_T1_B4.TIF'
 with rasterio.open(filepath) as src:
     print(src.profile)
 
@@ -18,7 +19,7 @@
 print(thumbnail)
 
 date = '2017-06-16'
-url = 'http://landsat-pds.s3.amazonaws.com/c1/L8/042/034/LC08_L1TP_042034_20170616_20170629_01_T1/'
+url = 'https://landsat-pds.s3.amazonaws.com/c1/L8/042/034/LC08_L1TP_042034_20170616_20170629_01_T1/'
 redband = 'LC08_L1TP_042034_20170616_20170629_01_T1_B{}.TIF'.format(4)
 nirband = 'LC08_L1TP_042034_20170616_20170629_01_T1_B{}.TIF'.format(5)
 
@@ -30,6 +31,11 @@
     red = src.read(1, out_shape=(1, int(src.height // oview), int(src.width // oview)))
     print(red)
 
+with rasterio.open(url+nirband) as src:
+    oviews = src.overviews(1) # list of overviews from biggest to smallest
+    oview = oviews[1]  # Use second-highest resolution overview
+    nir = src.read(1, out_shape=(1, int(src.height // oview), int(src.width // oview)))
+
 def calc_ndvi(nir,red):
     '''Calculate NDVI from integer arrays'''
     nir = nir.astype('f4')