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Merge pull request planetlabs#48 from planetlabs/foss4gna
pin base image version to before conda 4.4 to fix kernda bug
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‎jupyter-notebooks/inspecting-sat-imagery/Inspecting Satellite Imagery.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Inspecting Satellite Imagery using Rasterio\n",
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"## A first look at analyzing satellite data with Python\n",
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"\n",
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"At this point, you've explored different ways of searching for, filtering, and downloading satellite imagery. Now let's use one of these acquired datasets and dig into it a bit with Python.\n",
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"\n",
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"Here we're going to use a Python library called `rasterio`: you may be familiar with it already, or perhaps with the related C library, `GDAL`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 50,
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"metadata": {},
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"outputs": [],
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"source": [
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"import rasterio\n",
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"satdat = rasterio.open(\"example.tif\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Basic details\n",
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"What can we learn about this satellite image using just Python?"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 51,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"BoundingBox(left=540759.0, bottom=3754401.0, right=568047.0, top=3767985.0)"
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]
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},
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"execution_count": 51,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Get the bounding box of this GeoTIFF\n",
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"satdat.bounds"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 63,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Width: 27288.0, Height: 13584.0\n"
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]
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}
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],
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"source": [
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"# Get dimensions, in map units (here, that's meters)\n",
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"\n",
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"width = satdat.bounds.right - satdat.bounds.left\n",
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"height = satdat.bounds.top - satdat.bounds.bottom\n",
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"\n",
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"print(\"Width: {}, Height: {}\".format(width, height))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 64,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Width: 9096, Height: 4528\n"
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]
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}
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],
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"source": [
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"# Get dimensions, in pixels\n",
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"px_width = satdat.width\n",
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"px_height = satdat.height\n",
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"print(\"Width: {}, Height: {}\".format(px_width, px_height))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 65,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(3.0, 3.0)"
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]
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},
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"execution_count": 65,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# How many meters to a pixel?\n",
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"\n",
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"w = width / px_width\n",
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"h = height / px_height\n",
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"\n",
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"w, h"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 66,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"CRS({'init': 'epsg:32611'})"
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]
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},
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"execution_count": 66,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Get coordinate reference system\n",
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"satdat.crs"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 59,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Top left corner coordinates: (540759.0, 3767985.0)\n",
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"Bottom right corner coordinates: (568047.0, 3754401.0)\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2910: FutureWarning: The value of this property will change in version 1.0. Please see https://github.com/mapbox/rasterio/issues/86 for details.\n",
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" exec(code_obj, self.user_global_ns, self.user_ns)\n"
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]
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}
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],
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"source": [
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"# Get coordinates of top-left & bottom right corners\n",
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"# NOTE: how to do this depends on your Rasterio version:\n",
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"# the below example may generate a FutureWarning, which is safe to ignore here\n",
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"\n",
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"try:\n",
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" topleft = satdat.transform * (0, 0)\n",
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" botright = satdat.transform * (width, height)\n",
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" \n",
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"except TypeError:\n",
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" topleft = satdat.affine * (0, 0)\n",
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" botright = satdat.affine * (width, height)\n",
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" \n",
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"print(\"Top left corner coordinates: {}\".format(topleft))\n",
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"print(\"Bottom right corner coordinates: {}\".format(botright))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Bands\n",
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"So far, we haven't done too much raster-specific work yet. Since we know we're inspecting a multispectral satellite image, let's see what we can learn about its bands."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Get the number of bands by listing their indices\n",
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"satdat.indexes"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Because we know we're look at a PlanetScope 4-band analytic satellite image, we can define the bands by their order:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# PlanetScope 4-band band order: BGRN\n",
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"\n",
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"blue = satdat.read(1)\n",
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"green = satdat.read(2)\n",
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"red = satdat.read(3)\n",
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"nir = satdat.read(4)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# bands are stored as numpy arrays\n",
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"\n",
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"type(blue)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"blue"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Output min & max pixel values in each band\n",
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"\n",
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"print(blue.min(), blue.max())\n",
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"print(green.min(), green.max())\n",
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"print(red.min(), red.max())\n",
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"print(nir.min(), nir.max())"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Pixels"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 61,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"6382"
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]
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},
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"execution_count": 61,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Let's grab the pixel 5km east and 5km south of the upper left corner\n",
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"\n",
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"# get the pixel \n",
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"px_x = satdat.bounds.left + 5000\n",
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"px_y = satdat.bounds.top - 5000\n",
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"\n",
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"row, col = satdat.index(px_x, px_y)\n",
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"\n",
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"# Now let's look at the value of Band1 (\"blue\") at this pixel\n",
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"blue[row, col]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎jupyter-notebooks/mosaicing/basic_compositing_demo.ipynb‎

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