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jpolchlo/AVIRIS landfill scene matching.ipynb

Created August 5, 2021 20:57
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AVIRIS landfill scene matching.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Endmember Selection for Trash Detection"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Package `lxml` missing. Pretty print will be disabled\n"
]
}
],
"source": [
"import ftplib\n",
"from functools import partial\n",
"from io import StringIO\n",
"import json\n",
"from multiprocessing import Pool\n",
"import os\n",
"from os.path import basename, dirname\n",
"import re\n",
"import sys\n",
"import tempfile\n",
"from threading import Lock\n",
"from urllib.parse import urlparse\n",
"\n",
"import fastkml\n",
"import geopandas as gp\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from osgeo import gdal, ogr\n",
"import pandas as pd\n",
"import pyproj\n",
"import pystac as stac\n",
"import pysptools as sp\n",
"import rasterio as rio\n",
"import rasterio.features as rfeat\n",
"import rasterio.warp as rwarp\n",
"import requests\n",
"import shapely\n",
"from tqdm.notebook import tqdm\n",
"import xml.dom as dom\n",
"\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## AVIRIS scene selection"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"def kml_poly_to_geom(kml_poly):\n",
" try:\n",
" # Not all KML polygons are correct (missing LinearRing tag); grab coords directly\n",
" kmldom = dom.minidom.parseString('<?xml version=\"1.0\" encoding=\"UTF-8\"?><kml xmlns=\"http://www.opengis.net/kml/2.2\"><Document><Placemark>'+kml_poly+'</Placemark></Document></kml>')\n",
" coords = kmldom.getElementsByTagName('outerBoundaryIs')[0].getElementsByTagName('coordinates')[0]\n",
" kml = fastkml.KML()\n",
" kml.from_string('<?xml version=\"1.0\" encoding=\"UTF-8\"?><kml xmlns=\"http://www.opengis.net/kml/2.2\"><Document><Placemark><Polygon><outerBoundaryIs><LinearRing>'+coords.toxml()+'</LinearRing></outerBoundaryIs></Polygon></Placemark></Document></kml>')\n",
" except:\n",
" return None\n",
" return next(next(kml.features()).features()).geometry"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f6c9fa76ef0>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"aviris = pd.read_csv('catalog/aviris-flight-lines.csv')\n",
"aviris = gp.GeoDataFrame(aviris, geometry=[kml_poly_to_geom(poly) for poly in aviris['kml_poly']]).set_crs(epsg=4326)\n",
"aviris.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The following code block identifies the scenes with associated L2 imagery."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"ftpurl = urlparse(aviris.iloc[0].link_ftp)\n",
"ftp = ftplib.FTP(ftpurl.hostname)\n",
"ftp.login(ftpurl.username, ftpurl.password)\n",
"\n",
"l2 = []\n",
"for yy in range(6,20):\n",
" ftp.cwd('y{}_data'.format(str(yy).zfill(2)))\n",
" l2 = l2 + list(filter(lambda s: '_refl' in s, ftp.nlst()))\n",
" ftp.cwd('..')\n",
"\n",
"ftp.close()\n",
"\n",
"l2 = [re.sub('_refl\\.tar\\.gz', '', n) for n in l2]\n",
"l2df = pd.DataFrame({'Name': l2, 'has_l2': [True] * len(l2)}).set_index('Name')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>Name</th>\n",
" <th>Site Name</th>\n",
" <th>NASA Log</th>\n",
" <th>Investigator</th>\n",
" <th>Comments</th>\n",
" <th>Flight Scene</th>\n",
" <th>Date</th>\n",
" <th>RDN Ver</th>\n",
" <th>Scene</th>\n",
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" <th>...</th>\n",
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" <th>Lat1</th>\n",
" <th>Lat2</th>\n",
" <th>Lat3</th>\n",
" <th>Lat4</th>\n",
" <th>kml_poly</th>\n",
" <th>HTML Link CH4</th>\n",
" <th>HTML Link Reflectance</th>\n",
" <th>geometry</th>\n",
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" <tbody>\n",
" <tr>\n",
" <td>2057</td>\n",
" <td>f130329t01p00r06</td>\n",
" <td>Ad Hoc</td>\n",
" <td>132003</td>\n",
" <td>Robert Green</td>\n",
" <td>Heading to southern end of So Cal Box Line 2</td>\n",
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" <tr>\n",
" <td>2061</td>\n",
" <td>f130410t01p00r09</td>\n",
" <td>Bay Area Box Line 3</td>\n",
" <td>132003</td>\n",
" <td>Robert Green</td>\n",
" <td>Clear</td>\n",
" <td>f130410t01p00r09_sc01</td>\n",
" <td>4/10/13</td>\n",
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" <td>Robert Green</td>\n",
" <td>Clear</td>\n",
" <td>f130410t01p00r10_sc01</td>\n",
" <td>4/10/13</td>\n",
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" <td>36.631061</td>\n",
" <td>36.687696</td>\n",
" <td>38.910129</td>\n",
" <td>38.851815</td>\n",
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" <td>POLYGON ((-121.83758 36.63106, -121.70684 36.6...</td>\n",
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" <td>f130410t01p00r11_sc01</td>\n",
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" <td>f130410t01p00r12</td>\n",
" <td>Bay Area Box Line 6</td>\n",
" <td>132003</td>\n",
" <td>Robert Green</td>\n",
" <td>Clear</td>\n",
" <td>f130410t01p00r12_sc01</td>\n",
" <td>4/10/13</td>\n",
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" <td>f191001t01p00r12</td>\n",
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" <td>Robert Green</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>POLYGON ((-119.27456 36.65147, -119.09002 36.6...</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <td>4046</td>\n",
" <td>f191001t01p00r13</td>\n",
" <td>Yosemite-NEON Box 6 (YN40)</td>\n",
" <td>192019</td>\n",
" <td>Robert Green</td>\n",
" <td>S -) N</td>\n",
" <td>f191001t01p00r13_sc01</td>\n",
" <td>10/1/19</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
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" <td>36.427286</td>\n",
" <td>36.431268</td>\n",
" <td>38.102648</td>\n",
" <td>38.098419</td>\n",
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" <td>f191001t01p00r14</td>\n",
" <td>Yosemite-NEON Box 8 (YN42)</td>\n",
" <td>192019</td>\n",
" <td>Robert Green</td>\n",
" <td>N -) S</td>\n",
" <td>f191001t01p00r14_sc01</td>\n",
" <td>10/1/19</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
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" <td>36.277591</td>\n",
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" <tr>\n",
" <td>4048</td>\n",
" <td>f191001t01p00r15</td>\n",
" <td>Yosemite-NEON Box 10 (YN44)</td>\n",
" <td>192019</td>\n",
" <td>Robert Green</td>\n",
" <td>S -) N</td>\n",
" <td>f191001t01p00r15_sc01</td>\n",
" <td>10/1/19</td>\n",
" <td>e</td>\n",
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" <td>...</td>\n",
" <td>-119.949323</td>\n",
" <td>36.334614</td>\n",
" <td>36.339230</td>\n",
" <td>38.110919</td>\n",
" <td>38.105999</td>\n",
" <td>&lt;Polygon&gt;&lt;outerBoundaryIs&gt;&lt;coordinates&gt; -119.8...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>POLYGON ((-119.88109 36.33461, -119.68295 36.3...</td>\n",
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" <tr>\n",
" <td>4049</td>\n",
" <td>f191001t01p00r16</td>\n",
" <td>Soda Straw</td>\n",
" <td>192019</td>\n",
" <td>Robert Green</td>\n",
" <td>NaN</td>\n",
" <td>f191001t01p00r16_sc01</td>\n",
" <td>10/1/19</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>...</td>\n",
" <td>-119.115503</td>\n",
" <td>34.381136</td>\n",
" <td>34.358701</td>\n",
" <td>38.204896</td>\n",
" <td>38.228161</td>\n",
" <td>&lt;Polygon&gt;&lt;outerBoundaryIs&gt;&lt;coordinates&gt; -119.9...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>POLYGON ((-119.99574 34.38114, -119.84759 34.3...</td>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1554 rows × 53 columns</p>\n",
"</div>"
],
"text/plain": [
" Name Site Name NASA Log Investigator \\\n",
"2057 f130329t01p00r06 Ad Hoc 132003 Robert Green \n",
"2061 f130410t01p00r09 Bay Area Box Line 3 132003 Robert Green \n",
"2062 f130410t01p00r10 Bay Area Box Line 5 132003 Robert Green \n",
"2063 f130410t01p00r11 Bay Area Box Line 4 132003 Robert Green \n",
"2064 f130410t01p00r12 Bay Area Box Line 6 132003 Robert Green \n",
"... ... ... ... ... \n",
"4045 f191001t01p00r12 Yosemite-NEON Box 4 (YN38) 192019 Robert Green \n",
"4046 f191001t01p00r13 Yosemite-NEON Box 6 (YN40) 192019 Robert Green \n",
"4047 f191001t01p00r14 Yosemite-NEON Box 8 (YN42) 192019 Robert Green \n",
"4048 f191001t01p00r15 Yosemite-NEON Box 10 (YN44) 192019 Robert Green \n",
"4049 f191001t01p00r16 Soda Straw 192019 Robert Green \n",
"\n",
" Comments Flight Scene \\\n",
"2057 Heading to southern end of So Cal Box Line 2 f130329t01p00r06_sc01 \n",
"2061 Clear f130410t01p00r09_sc01 \n",
"2062 Clear f130410t01p00r10_sc01 \n",
"2063 Clear f130410t01p00r11_sc01 \n",
"2064 Clear f130410t01p00r12_sc01 \n",
"... ... ... \n",
"4045 N -) S f191001t01p00r12_sc01 \n",
"4046 S -) N f191001t01p00r13_sc01 \n",
"4047 N -) S f191001t01p00r14_sc01 \n",
"4048 S -) N f191001t01p00r15_sc01 \n",
"4049 NaN f191001t01p00r16_sc01 \n",
"\n",
" Date RDN Ver Scene GEO Ver ... Lon4 Lat1 Lat2 \\\n",
"2057 3/29/13 e sc01 ort ... -116.833779 33.498289 33.669720 \n",
"2061 4/10/13 e sc01 ort ... -122.113629 36.498050 36.547666 \n",
"2062 4/10/13 e sc01 ort ... -123.372638 36.631061 36.687696 \n",
"2063 4/10/13 e sc01 ort ... -123.885101 36.406493 36.527593 \n",
"2064 4/10/13 e sc01 ort ... -123.235697 36.722976 36.778559 \n",
"... ... ... ... ... ... ... ... ... \n",
"4045 10/1/19 e sc01 ort ... -119.321138 36.651468 36.654850 \n",
"4046 10/1/19 e sc01 ort ... -119.530521 36.427286 36.431268 \n",
"4047 10/1/19 e sc01 ort ... -119.745376 36.273111 36.277591 \n",
"4048 10/1/19 e sc01 ort ... -119.949323 36.334614 36.339230 \n",
"4049 10/1/19 e sc01 ort ... -119.115503 34.381136 34.358701 \n",
"\n",
" Lat3 Lat4 kml_poly \\\n",
"2057 34.187606 34.015078 <Polygon><outerBoundaryIs><LinearRing><coordin... \n",
"2061 36.721925 36.672202 <Polygon><outerBoundaryIs><LinearRing><coordin... \n",
"2062 38.910129 38.851815 <Polygon><outerBoundaryIs><LinearRing><coordin... \n",
"2063 39.352162 39.226438 <Polygon><outerBoundaryIs><LinearRing><coordin... \n",
"2064 38.898828 38.841675 <Polygon><outerBoundaryIs><LinearRing><coordin... \n",
"... ... ... ... \n",
"4045 38.178856 38.175283 <Polygon><outerBoundaryIs><coordinates> -119.2... \n",
"4046 38.102648 38.098419 <Polygon><outerBoundaryIs><coordinates> -119.4... \n",
"4047 38.178553 38.173756 <Polygon><outerBoundaryIs><coordinates> -119.6... \n",
"4048 38.110919 38.105999 <Polygon><outerBoundaryIs><coordinates> -119.8... \n",
"4049 38.204896 38.228161 <Polygon><outerBoundaryIs><coordinates> -119.9... \n",
"\n",
" HTML Link CH4 HTML Link Reflectance \\\n",
"2057 NaN <a href='ftp://avoil:[email protected]... \n",
"2061 NaN <a href='ftp://avoil:[email protected]... \n",
"2062 NaN <a href='ftp://avoil:[email protected]... \n",
"2063 NaN <a href='ftp://avoil:[email protected]... \n",
"2064 NaN <a href='ftp://avoil:[email protected]... \n",
"... ... ... \n",
"4045 NaN NaN \n",
"4046 NaN NaN \n",
"4047 NaN NaN \n",
"4048 NaN NaN \n",
"4049 NaN NaN \n",
"\n",
" geometry has_l2 \n",
"2057 POLYGON ((-114.88722 33.49829, -114.81992 33.6... True \n",
"2061 POLYGON ((-122.00625 36.49805, -121.88226 36.5... True \n",
"2062 POLYGON ((-121.83758 36.63106, -121.70684 36.6... True \n",
"2063 POLYGON ((-121.99729 36.40649, -121.70702 36.5... True \n",
"2064 POLYGON ((-121.77412 36.72298, -121.64546 36.7... True \n",
"... ... ... \n",
"4045 POLYGON ((-119.27456 36.65147, -119.09002 36.6... True \n",
"4046 POLYGON ((-119.47518 36.42729, -119.27512 36.4... True \n",
"4047 POLYGON ((-119.67728 36.27311, -119.46922 36.2... True \n",
"4048 POLYGON ((-119.88109 36.33461, -119.68295 36.3... True \n",
"4049 POLYGON ((-119.99574 34.38114, -119.84759 34.3... True \n",
"\n",
"[1554 rows x 53 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"aviris_l2 = aviris.join(l2df, on='Name', how='inner')\n",
"aviris_l2"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def get_outline(link_kml_outline):\n",
" gj = os.path.join('/tmp', next(tempfile._get_candidate_names()) + '.geojson')\n",
" srcDS = gdal.OpenEx(link_kml_outline.iloc[0])\n",
" ds = gdal.VectorTranslate(gj, srcDS, format='GeoJSON')\n",
" del ds # Hacky business to make sure the target file is written (known GDAL weirdness)\n",
" try:\n",
" with open(gj) as f:\n",
" features = json.load(f)['features']\n",
" return shapely.geometry.GeometryCollection([shapely.geometry.shape(f['geometry']) for f in features])\n",
" except:\n",
" print('Failed to process ' + link_kml_outline.iloc[0])\n",
" return None\n",
" finally:\n",
" if os.path.exists(gj):\n",
" os.remove(gj)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "3ecae2dc27e84c6185a04942fd89764d",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"HBox(children=(HTML(value=''), FloatProgress(value=0.0, max=1554.0), HTML(value='')))"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y14_KML/f141107t01p00r13_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y14_KML/f141107t01p00r14_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y16_KML/f160324t01p00r10_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y17_KML/f170507t01p00r07_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y17_KML/f170507t01p00r07_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y17_KML/f170507t01p00r08_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y17_KML/f170507t01p00r09_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y17_KML/f170507t01p00r10_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y17_KML/f170507t01p00r11_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y17_KML/f170507t01p00r12_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y17_KML/f171221t01p00r20_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r07_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r08_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r09_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r10_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r11_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r12_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r13_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r14_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r15_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r16_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r17_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y18_KML/f180816t01p00r18_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y19_KML/f190813t01p00r05_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y19_KML/f190813t01p00r06_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y19_KML/f190813t01p00r07_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y19_KML/f190813t01p00r08_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y19_KML/f190813t01p00r09_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y19_KML/f190813t01p00r10_sc01_outline_KML.kml\n",
"Failed to process http://aviris.jpl.nasa.gov/aviris_locator/y19_KML/f190813t01p00r11_sc01_outline_KML.kml\n",
"\n"
]
}
],
"source": [
"with Pool() as p:\n",
" full_geom = list(tqdm(p.imap(get_outline, np.array_split(aviris_l2.link_kml_outline, len(aviris_l2))), total=len(aviris_l2)))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"fixed = [shapely.geometry.MultiPolygon([x]) if isinstance(x, shapely.geometry.Polygon) else x for x in [(g[0] if g[0].is_valid else g[0].buffer(0)) if g else None for g in full_geom]]\n",
"aviris_l2['full_geom'] = fixed"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
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" <th>NASA Log</th>\n",
" <th>Investigator</th>\n",
" <th>Comments</th>\n",
" <th>Flight Scene</th>\n",
" <th>Date</th>\n",
" <th>RDN Ver</th>\n",
" <th>Scene</th>\n",
" <th>GEO Ver</th>\n",
" <th>...</th>\n",
" <th>Lat1</th>\n",
" <th>Lat2</th>\n",
" <th>Lat3</th>\n",
" <th>Lat4</th>\n",
" <th>kml_poly</th>\n",
" <th>HTML Link CH4</th>\n",
" <th>HTML Link Reflectance</th>\n",
" <th>geometry</th>\n",
" <th>has_l2</th>\n",
" <th>full_geom</th>\n",
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" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td>2057</td>\n",
" <td>f130329t01p00r06</td>\n",
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" <td>Heading to southern end of So Cal Box Line 2</td>\n",
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" <td>Bay Area Box Line 3</td>\n",
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" <td>f130410t01p00r09_sc01</td>\n",
" <td>4/10/13</td>\n",
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" <td>Bay Area Box Line 5</td>\n",
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" <td>Bay Area Box Line 4</td>\n",
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" <td>192019</td>\n",
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" </tbody>\n",
"</table>\n",
"<p>1554 rows × 54 columns</p>\n",
"</div>"
],
"text/plain": [
" Name Site Name NASA Log Investigator \\\n",
"2057 f130329t01p00r06 Ad Hoc 132003 Robert Green \n",
"2061 f130410t01p00r09 Bay Area Box Line 3 132003 Robert Green \n",
"2062 f130410t01p00r10 Bay Area Box Line 5 132003 Robert Green \n",
"2063 f130410t01p00r11 Bay Area Box Line 4 132003 Robert Green \n",
"2064 f130410t01p00r12 Bay Area Box Line 6 132003 Robert Green \n",
"... ... ... ... ... \n",
"4045 f191001t01p00r12 Yosemite-NEON Box 4 (YN38) 192019 Robert Green \n",
"4046 f191001t01p00r13 Yosemite-NEON Box 6 (YN40) 192019 Robert Green \n",
"4047 f191001t01p00r14 Yosemite-NEON Box 8 (YN42) 192019 Robert Green \n",
"4048 f191001t01p00r15 Yosemite-NEON Box 10 (YN44) 192019 Robert Green \n",
"4049 f191001t01p00r16 Soda Straw 192019 Robert Green \n",
"\n",
" Comments Flight Scene \\\n",
"2057 Heading to southern end of So Cal Box Line 2 f130329t01p00r06_sc01 \n",
"2061 Clear f130410t01p00r09_sc01 \n",
"2062 Clear f130410t01p00r10_sc01 \n",
"2063 Clear f130410t01p00r11_sc01 \n",
"2064 Clear f130410t01p00r12_sc01 \n",
"... ... ... \n",
"4045 N -) S f191001t01p00r12_sc01 \n",
"4046 S -) N f191001t01p00r13_sc01 \n",
"4047 N -) S f191001t01p00r14_sc01 \n",
"4048 S -) N f191001t01p00r15_sc01 \n",
"4049 NaN f191001t01p00r16_sc01 \n",
"\n",
" Date RDN Ver Scene GEO Ver ... Lat1 Lat2 Lat3 \\\n",
"2057 3/29/13 e sc01 ort ... 33.498289 33.669720 34.187606 \n",
"2061 4/10/13 e sc01 ort ... 36.498050 36.547666 36.721925 \n",
"2062 4/10/13 e sc01 ort ... 36.631061 36.687696 38.910129 \n",
"2063 4/10/13 e sc01 ort ... 36.406493 36.527593 39.352162 \n",
"2064 4/10/13 e sc01 ort ... 36.722976 36.778559 38.898828 \n",
"... ... ... ... ... ... ... ... ... \n",
"4045 10/1/19 e sc01 ort ... 36.651468 36.654850 38.178856 \n",
"4046 10/1/19 e sc01 ort ... 36.427286 36.431268 38.102648 \n",
"4047 10/1/19 e sc01 ort ... 36.273111 36.277591 38.178553 \n",
"4048 10/1/19 e sc01 ort ... 36.334614 36.339230 38.110919 \n",
"4049 10/1/19 e sc01 ort ... 34.381136 34.358701 38.204896 \n",
"\n",
" Lat4 kml_poly \\\n",
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"... ... ... \n",
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"4049 38.228161 <Polygon><outerBoundaryIs><coordinates> -119.9... \n",
"\n",
" HTML Link CH4 HTML Link Reflectance \\\n",
"2057 NaN <a href='ftp://avoil:[email protected]... \n",
"2061 NaN <a href='ftp://avoil:[email protected]... \n",
"2062 NaN <a href='ftp://avoil:[email protected]... \n",
"2063 NaN <a href='ftp://avoil:[email protected]... \n",
"2064 NaN <a href='ftp://avoil:[email protected]... \n",
"... ... ... \n",
"4045 NaN NaN \n",
"4046 NaN NaN \n",
"4047 NaN NaN \n",
"4048 NaN NaN \n",
"4049 NaN NaN \n",
"\n",
" geometry has_l2 \\\n",
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"2061 POLYGON ((-122.00625 36.49805, -121.88226 36.5... True \n",
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"... ... ... \n",
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"4049 POLYGON ((-119.99574 34.38114, -119.84759 34.3... True \n",
"\n",
" full_geom \n",
"2057 MULTIPOLYGON Z (((-116.81681 34.06101 0.00000,... \n",
"2061 MULTIPOLYGON Z (((-121.99629 36.71918 0.00000,... \n",
"2062 MULTIPOLYGON Z (((-123.24439 38.90783 0.00000,... \n",
"2063 MULTIPOLYGON Z (((-123.63492 39.33193 0.00000,... \n",
"2064 MULTIPOLYGON Z (((-123.17659 38.86743 0.00000,... \n",
"... ... \n",
"4045 MULTIPOLYGON Z (((-119.31012 38.17550 0.00000,... \n",
"4046 MULTIPOLYGON Z (((-119.33525 38.10246 0.00000,... \n",
"4047 MULTIPOLYGON Z (((-119.65916 38.17574 0.00000,... \n",
"4048 MULTIPOLYGON Z (((-119.75356 38.11075 0.00000,... \n",
"4049 MULTIPOLYGON Z (((-119.07885 38.22270 0.00000,... \n",
"\n",
"[1554 rows x 54 columns]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"aviris_l2.set_geometry('full_geom', inplace=True)\n",
"aviris_l2.set_crs(epsg=4326)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
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],
"text/plain": [
"<shapely.geometry.multipolygon.MultiPolygon at 0x7fc759d74d30>"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"aviris_l2.geometry.loc[3232]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Landfill Identification"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"exclude_lfs = [] # [80, 81, 82, 142, 143, 194]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>id_left</th>\n",
" <th>id_right</th>\n",
" <th>name</th>\n",
" <th>geometry</th>\n",
" <th>area</th>\n",
" <th>lfgeom</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td>0</td>\n",
" <td>way/25027718</td>\n",
" <td>aviris_f171221t01p00r09_sc01</td>\n",
" <td>None</td>\n",
" <td>POLYGON ((-121.69279 38.59065, -121.67691 38.5...</td>\n",
" <td>1.622864e+06</td>\n",
" <td>POLYGON ((-121.69279 38.59065, -121.67691 38.5...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>1</td>\n",
" <td>way/25880989</td>\n",
" <td>aviris_f171221t01p00r09_sc01</td>\n",
" <td>None</td>\n",
" <td>POLYGON ((-121.70367 38.55320, -121.70377 38.5...</td>\n",
" <td>5.158543e+04</td>\n",
" <td>POLYGON ((-121.70367 38.55320, -121.70377 38.5...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>2</td>\n",
" <td>way/32704348</td>\n",
" <td>aviris_f171221t01p00r09_sc01</td>\n",
" <td>None</td>\n",
" <td>POLYGON ((-121.17448 38.50409, -121.18004 38.5...</td>\n",
" <td>1.477941e+06</td>\n",
" <td>POLYGON ((-121.17448 38.50409, -121.18004 38.5...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>3</td>\n",
" <td>way/27284827</td>\n",
" <td>aviris_f180601t01p00r06_sc01</td>\n",
" <td>None</td>\n",
" <td>POLYGON ((-122.15237 37.64211, -122.15234 37.6...</td>\n",
" <td>1.549185e+05</td>\n",
" <td>POLYGON ((-122.15237 37.64211, -122.15234 37.6...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>4</td>\n",
" <td>way/27284829</td>\n",
" <td>aviris_f180601t01p00r06_sc01</td>\n",
" <td>None</td>\n",
" <td>POLYGON ((-122.15419 37.64588, -122.15409 37.6...</td>\n",
" <td>2.424573e+05</td>\n",
" <td>POLYGON ((-122.15419 37.64588, -122.15409 37.6...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>260</td>\n",
" <td>way/842826369</td>\n",
" <td>aviris_f170420t01p00r05_sc01</td>\n",
" <td>None</td>\n",
" <td>POLYGON ((-82.84530 35.11884, -82.84436 35.118...</td>\n",
" <td>2.747379e+05</td>\n",
" <td>POLYGON ((-82.84530 35.11884, -82.84436 35.118...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>261</td>\n",
" <td>way/842835292</td>\n",
" <td>aviris_f170420t01p00r05_sc01</td>\n",
" <td>Buncombe County Landfill</td>\n",
" <td>POLYGON ((-82.63889 35.72747, -82.63966 35.727...</td>\n",
" <td>6.774254e+05</td>\n",
" <td>POLYGON ((-82.63889 35.72747, -82.63966 35.727...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>262</td>\n",
" <td>way/861187079</td>\n",
" <td>aviris_f080709t01p00r13_sc01</td>\n",
" <td>Former Landfill</td>\n",
" <td>POLYGON ((-86.18765 42.82224, -86.18775 42.819...</td>\n",
" <td>1.734744e+05</td>\n",
" <td>POLYGON ((-86.18765 42.82224, -86.18775 42.819...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>263</td>\n",
" <td>way/867846377</td>\n",
" <td>aviris_f061002t01p00r10_sc01</td>\n",
" <td>Red Cliff Waste &amp; Recycling Transfer Station</td>\n",
" <td>POLYGON ((-90.79126 46.89637, -90.79126 46.895...</td>\n",
" <td>1.788899e+04</td>\n",
" <td>POLYGON ((-90.79126 46.89637, -90.79126 46.895...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>264</td>\n",
" <td>way/867886092</td>\n",
" <td>aviris_f090705t01p00r10_sc01</td>\n",
" <td>None</td>\n",
" <td>POLYGON ((-76.68536 42.03961, -76.68584 42.036...</td>\n",
" <td>5.726869e+05</td>\n",
" <td>POLYGON ((-76.68536 42.03961, -76.68584 42.036...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>265 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" id_left id_right \\\n",
"0 way/25027718 aviris_f171221t01p00r09_sc01 \n",
"1 way/25880989 aviris_f171221t01p00r09_sc01 \n",
"2 way/32704348 aviris_f171221t01p00r09_sc01 \n",
"3 way/27284827 aviris_f180601t01p00r06_sc01 \n",
"4 way/27284829 aviris_f180601t01p00r06_sc01 \n",
".. ... ... \n",
"260 way/842826369 aviris_f170420t01p00r05_sc01 \n",
"261 way/842835292 aviris_f170420t01p00r05_sc01 \n",
"262 way/861187079 aviris_f080709t01p00r13_sc01 \n",
"263 way/867846377 aviris_f061002t01p00r10_sc01 \n",
"264 way/867886092 aviris_f090705t01p00r10_sc01 \n",
"\n",
" name \\\n",
"0 None \n",
"1 None \n",
"2 None \n",
"3 None \n",
"4 None \n",
".. ... \n",
"260 None \n",
"261 Buncombe County Landfill \n",
"262 Former Landfill \n",
"263 Red Cliff Waste & Recycling Transfer Station \n",
"264 None \n",
"\n",
" geometry area \\\n",
"0 POLYGON ((-121.69279 38.59065, -121.67691 38.5... 1.622864e+06 \n",
"1 POLYGON ((-121.70367 38.55320, -121.70377 38.5... 5.158543e+04 \n",
"2 POLYGON ((-121.17448 38.50409, -121.18004 38.5... 1.477941e+06 \n",
"3 POLYGON ((-122.15237 37.64211, -122.15234 37.6... 1.549185e+05 \n",
"4 POLYGON ((-122.15419 37.64588, -122.15409 37.6... 2.424573e+05 \n",
".. ... ... \n",
"260 POLYGON ((-82.84530 35.11884, -82.84436 35.118... 2.747379e+05 \n",
"261 POLYGON ((-82.63889 35.72747, -82.63966 35.727... 6.774254e+05 \n",
"262 POLYGON ((-86.18765 42.82224, -86.18775 42.819... 1.734744e+05 \n",
"263 POLYGON ((-90.79126 46.89637, -90.79126 46.895... 1.788899e+04 \n",
"264 POLYGON ((-76.68536 42.03961, -76.68584 42.036... 5.726869e+05 \n",
"\n",
" lfgeom \n",
"0 POLYGON ((-121.69279 38.59065, -121.67691 38.5... \n",
"1 POLYGON ((-121.70367 38.55320, -121.70377 38.5... \n",
"2 POLYGON ((-121.17448 38.50409, -121.18004 38.5... \n",
"3 POLYGON ((-122.15237 37.64211, -122.15234 37.6... \n",
"4 POLYGON ((-122.15419 37.64588, -122.15409 37.6... \n",
".. ... \n",
"260 POLYGON ((-82.84530 35.11884, -82.84436 35.118... \n",
"261 POLYGON ((-82.63889 35.72747, -82.63966 35.727... \n",
"262 POLYGON ((-86.18765 42.82224, -86.18775 42.819... \n",
"263 POLYGON ((-90.79126 46.89637, -90.79126 46.895... \n",
"264 POLYGON ((-76.68536 42.03961, -76.68584 42.036... \n",
"\n",
"[265 rows x 6 columns]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"landfills = gp.read_file(\"data/aviris_landfills.gpkg\").set_crs(epsg=4326)\n",
"landfills = landfills.loc[[i for i in range(len(landfills)) if i not in exclude_lfs]]\n",
"landfills['area'] = landfills.geometry.to_crs(epsg=5070).area\n",
"landfills['lfgeom'] = landfills.geometry\n",
"landfills"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Select Landfills by Climate Zone"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"us_eco_raw = gp.read_file('data/CONUS_CLIMATE_DIVISIONS/us_eco_l3.shp')"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"us_l2 = us_eco_raw.dissolve(by='NA_L2CODE')"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fc75a004208>"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"us_l2.plot(edgecolor='black', column='NA_L2NAME')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Select only the largest landfills in a given climate zone"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [],
"source": [
"bigguns = gp.sjoin(landfills, us_l2.to_crs(landfills.crs), lsuffix='lf', rsuffix='zone').sort_values('area').groupby(['index_zone']).head(20)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"index_zone\n",
"10.1 6\n",
"10.2 5\n",
"11.1 20\n",
"15.4 1\n",
"5.2 4\n",
"5.3 5\n",
"6.2 10\n",
"7.1 8\n",
"8.1 20\n",
"8.2 4\n",
"8.3 18\n",
"8.4 20\n",
"8.5 9\n",
"9.2 1\n",
"9.4 14\n",
"Name: id_left, dtype: int64"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bigguns.groupby(['index_zone']).count()['id_left']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### AVIRIS/Landfill Matching and Selection\n",
"\n",
"We'll pair AVIRIS scenes with landfill polygons when the landfill is entirely contained by the AVIRIS swath. We'll then choose the largest landfill."
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Name</th>\n",
" <th>Site Name</th>\n",
" <th>Flight Scene</th>\n",
" <th>RDN Ver</th>\n",
" <th>Scene</th>\n",
" <th>GEO Ver</th>\n",
" <th>link_ftp</th>\n",
" <th>geometry</th>\n",
" <th>lfgeom</th>\n",
" <th>full_geom</th>\n",
" <th>name</th>\n",
" <th>area</th>\n",
" <th>landfill_id</th>\n",
" <th>zone</th>\n",
" <th>zone_name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td>2062</td>\n",
" <td>f130410t01p00r10</td>\n",
" <td>Bay Area Box Line 5</td>\n",
" <td>f130410t01p00r10_sc01</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y13...</td>\n",
" <td>POLYGON ((-121.83758 36.63106, -121.70684 36.6...</td>\n",
" <td>POLYGON ((-122.41061 37.48980, -122.40944 37.4...</td>\n",
" <td>MULTIPOLYGON Z (((-123.24439 38.90783 0.00000,...</td>\n",
" <td>Ox Mountain Landfill</td>\n",
" <td>1.230834e+06</td>\n",
" <td>29</td>\n",
" <td>7.1</td>\n",
" <td>MARINE WEST COAST FOREST</td>\n",
" </tr>\n",
" <tr>\n",
" <td>2062</td>\n",
" <td>f130410t01p00r10</td>\n",
" <td>Bay Area Box Line 5</td>\n",
" <td>f130410t01p00r10_sc01</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y13...</td>\n",
" <td>POLYGON ((-121.83758 36.63106, -121.70684 36.6...</td>\n",
" <td>POLYGON ((-122.07717 37.09147, -122.07683 37.0...</td>\n",
" <td>MULTIPOLYGON Z (((-123.24439 38.90783 0.00000,...</td>\n",
" <td>Ben Lomond Transfer Station</td>\n",
" <td>1.710278e+05</td>\n",
" <td>31</td>\n",
" <td>7.1</td>\n",
" <td>MARINE WEST COAST FOREST</td>\n",
" </tr>\n",
" <tr>\n",
" <td>2063</td>\n",
" <td>f130410t01p00r11</td>\n",
" <td>Bay Area Box Line 4</td>\n",
" <td>f130410t01p00r11_sc01</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y13...</td>\n",
" <td>POLYGON ((-121.99729 36.40649, -121.70702 36.5...</td>\n",
" <td>POLYGON ((-122.40862 37.48052, -122.40794 37.4...</td>\n",
" <td>MULTIPOLYGON Z (((-123.63492 39.33193 0.00000,...</td>\n",
" <td>Ox Mountain Sanitary Landfill</td>\n",
" <td>1.027866e+05</td>\n",
" <td>30</td>\n",
" <td>7.1</td>\n",
" <td>MARINE WEST COAST FOREST</td>\n",
" </tr>\n",
" <tr>\n",
" <td>2063</td>\n",
" <td>f130410t01p00r11</td>\n",
" <td>Bay Area Box Line 4</td>\n",
" <td>f130410t01p00r11_sc01</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y13...</td>\n",
" <td>POLYGON ((-121.99729 36.40649, -121.70702 36.5...</td>\n",
" <td>POLYGON ((-122.41061 37.48980, -122.40944 37.4...</td>\n",
" <td>MULTIPOLYGON Z (((-123.63492 39.33193 0.00000,...</td>\n",
" <td>Ox Mountain Landfill</td>\n",
" <td>1.230834e+06</td>\n",
" <td>29</td>\n",
" <td>7.1</td>\n",
" <td>MARINE WEST COAST FOREST</td>\n",
" </tr>\n",
" <tr>\n",
" <td>2063</td>\n",
" <td>f130410t01p00r11</td>\n",
" <td>Bay Area Box Line 4</td>\n",
" <td>f130410t01p00r11_sc01</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y13...</td>\n",
" <td>POLYGON ((-121.99729 36.40649, -121.70702 36.5...</td>\n",
" <td>POLYGON ((-122.19820 37.01947, -122.19831 37.0...</td>\n",
" <td>MULTIPOLYGON Z (((-123.63492 39.33193 0.00000,...</td>\n",
" <td>None</td>\n",
" <td>1.439942e+04</td>\n",
" <td>32</td>\n",
" <td>7.1</td>\n",
" <td>MARINE WEST COAST FOREST</td>\n",
" </tr>\n",
" <tr>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <td>3937</td>\n",
" <td>f180917t01p00r05</td>\n",
" <td>HyspIRI_3_line51</td>\n",
" <td>f180917t01p00r05_sc01</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y18...</td>\n",
" <td>POLYGON ((-118.52041 36.15015, -118.35515 36.1...</td>\n",
" <td>POLYGON ((-118.17908 36.78975, -118.17899 36.7...</td>\n",
" <td>MULTIPOLYGON Z (((-115.81530 41.32497 0.00000,...</td>\n",
" <td>None</td>\n",
" <td>9.210236e+04</td>\n",
" <td>240</td>\n",
" <td>10.1</td>\n",
" <td>COLD DESERTS</td>\n",
" </tr>\n",
" <tr>\n",
" <td>3940</td>\n",
" <td>f180918t01p00r06</td>\n",
" <td>HyspIRI_3_line48</td>\n",
" <td>f180918t01p00r06_sc01</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y18...</td>\n",
" <td>POLYGON ((-118.96598 36.26503, -118.79059 36.2...</td>\n",
" <td>POLYGON ((-118.40065 37.33223, -118.40065 37.3...</td>\n",
" <td>MULTIPOLYGON Z (((-116.29398 41.52568 0.00000,...</td>\n",
" <td>None</td>\n",
" <td>4.721976e+05</td>\n",
" <td>241</td>\n",
" <td>10.1</td>\n",
" <td>COLD DESERTS</td>\n",
" </tr>\n",
" <tr>\n",
" <td>3988</td>\n",
" <td>f190808t01p00r14</td>\n",
" <td>NOAA</td>\n",
" <td>f190808t01p00r14_sc01</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y19...</td>\n",
" <td>POLYGON ((-113.90866 46.97859, -113.74979 47.0...</td>\n",
" <td>POLYGON ((-114.23302 48.01515, -114.23402 48.0...</td>\n",
" <td>MULTIPOLYGON Z (((-114.39700 48.16432 0.00000,...</td>\n",
" <td>Lakeside Dump</td>\n",
" <td>6.116457e+04</td>\n",
" <td>152</td>\n",
" <td>6.2</td>\n",
" <td>WESTERN CORDILLERA</td>\n",
" </tr>\n",
" <tr>\n",
" <td>3991</td>\n",
" <td>f190808t01p00r17</td>\n",
" <td>U of Mt &amp; ISS</td>\n",
" <td>f190808t01p00r17_sc01</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y19...</td>\n",
" <td>POLYGON ((-113.10473 46.60822, -113.04788 46.7...</td>\n",
" <td>POLYGON ((-114.05383 46.91810, -114.05387 46.9...</td>\n",
" <td>MULTIPOLYGON Z (((-114.86876 47.11444 0.00000,...</td>\n",
" <td>None</td>\n",
" <td>3.068175e+05</td>\n",
" <td>119</td>\n",
" <td>6.2</td>\n",
" <td>WESTERN CORDILLERA</td>\n",
" </tr>\n",
" <tr>\n",
" <td>3991</td>\n",
" <td>f190808t01p00r17</td>\n",
" <td>U of Mt &amp; ISS</td>\n",
" <td>f190808t01p00r17_sc01</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y19...</td>\n",
" <td>POLYGON ((-113.10473 46.60822, -113.04788 46.7...</td>\n",
" <td>POLYGON ((-114.01335 46.89862, -114.01250 46.8...</td>\n",
" <td>MULTIPOLYGON Z (((-114.86876 47.11444 0.00000,...</td>\n",
" <td>None</td>\n",
" <td>5.301465e+05</td>\n",
" <td>118</td>\n",
" <td>6.2</td>\n",
" <td>WESTERN CORDILLERA</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>178 rows × 15 columns</p>\n",
"</div>"
],
"text/plain": [
" Name Site Name Flight Scene RDN Ver \\\n",
"2062 f130410t01p00r10 Bay Area Box Line 5 f130410t01p00r10_sc01 e \n",
"2062 f130410t01p00r10 Bay Area Box Line 5 f130410t01p00r10_sc01 e \n",
"2063 f130410t01p00r11 Bay Area Box Line 4 f130410t01p00r11_sc01 e \n",
"2063 f130410t01p00r11 Bay Area Box Line 4 f130410t01p00r11_sc01 e \n",
"2063 f130410t01p00r11 Bay Area Box Line 4 f130410t01p00r11_sc01 e \n",
"... ... ... ... ... \n",
"3937 f180917t01p00r05 HyspIRI_3_line51 f180917t01p00r05_sc01 e \n",
"3940 f180918t01p00r06 HyspIRI_3_line48 f180918t01p00r06_sc01 e \n",
"3988 f190808t01p00r14 NOAA f190808t01p00r14_sc01 e \n",
"3991 f190808t01p00r17 U of Mt & ISS f190808t01p00r17_sc01 e \n",
"3991 f190808t01p00r17 U of Mt & ISS f190808t01p00r17_sc01 e \n",
"\n",
" Scene GEO Ver link_ftp \\\n",
"2062 sc01 ort ftp://avoil:[email protected]/y13... \n",
"2062 sc01 ort ftp://avoil:[email protected]/y13... \n",
"2063 sc01 ort ftp://avoil:[email protected]/y13... \n",
"2063 sc01 ort ftp://avoil:[email protected]/y13... \n",
"2063 sc01 ort ftp://avoil:[email protected]/y13... \n",
"... ... ... ... \n",
"3937 sc01 ort ftp://avoil:[email protected]/y18... \n",
"3940 sc01 ort ftp://avoil:[email protected]/y18... \n",
"3988 sc01 ort ftp://avoil:[email protected]/y19... \n",
"3991 sc01 ort ftp://avoil:[email protected]/y19... \n",
"3991 sc01 ort ftp://avoil:[email protected]/y19... \n",
"\n",
" geometry \\\n",
"2062 POLYGON ((-121.83758 36.63106, -121.70684 36.6... \n",
"2062 POLYGON ((-121.83758 36.63106, -121.70684 36.6... \n",
"2063 POLYGON ((-121.99729 36.40649, -121.70702 36.5... \n",
"2063 POLYGON ((-121.99729 36.40649, -121.70702 36.5... \n",
"2063 POLYGON ((-121.99729 36.40649, -121.70702 36.5... \n",
"... ... \n",
"3937 POLYGON ((-118.52041 36.15015, -118.35515 36.1... \n",
"3940 POLYGON ((-118.96598 36.26503, -118.79059 36.2... \n",
"3988 POLYGON ((-113.90866 46.97859, -113.74979 47.0... \n",
"3991 POLYGON ((-113.10473 46.60822, -113.04788 46.7... \n",
"3991 POLYGON ((-113.10473 46.60822, -113.04788 46.7... \n",
"\n",
" lfgeom \\\n",
"2062 POLYGON ((-122.41061 37.48980, -122.40944 37.4... \n",
"2062 POLYGON ((-122.07717 37.09147, -122.07683 37.0... \n",
"2063 POLYGON ((-122.40862 37.48052, -122.40794 37.4... \n",
"2063 POLYGON ((-122.41061 37.48980, -122.40944 37.4... \n",
"2063 POLYGON ((-122.19820 37.01947, -122.19831 37.0... \n",
"... ... \n",
"3937 POLYGON ((-118.17908 36.78975, -118.17899 36.7... \n",
"3940 POLYGON ((-118.40065 37.33223, -118.40065 37.3... \n",
"3988 POLYGON ((-114.23302 48.01515, -114.23402 48.0... \n",
"3991 POLYGON ((-114.05383 46.91810, -114.05387 46.9... \n",
"3991 POLYGON ((-114.01335 46.89862, -114.01250 46.8... \n",
"\n",
" full_geom \\\n",
"2062 MULTIPOLYGON Z (((-123.24439 38.90783 0.00000,... \n",
"2062 MULTIPOLYGON Z (((-123.24439 38.90783 0.00000,... \n",
"2063 MULTIPOLYGON Z (((-123.63492 39.33193 0.00000,... \n",
"2063 MULTIPOLYGON Z (((-123.63492 39.33193 0.00000,... \n",
"2063 MULTIPOLYGON Z (((-123.63492 39.33193 0.00000,... \n",
"... ... \n",
"3937 MULTIPOLYGON Z (((-115.81530 41.32497 0.00000,... \n",
"3940 MULTIPOLYGON Z (((-116.29398 41.52568 0.00000,... \n",
"3988 MULTIPOLYGON Z (((-114.39700 48.16432 0.00000,... \n",
"3991 MULTIPOLYGON Z (((-114.86876 47.11444 0.00000,... \n",
"3991 MULTIPOLYGON Z (((-114.86876 47.11444 0.00000,... \n",
"\n",
" name area landfill_id zone \\\n",
"2062 Ox Mountain Landfill 1.230834e+06 29 7.1 \n",
"2062 Ben Lomond Transfer Station 1.710278e+05 31 7.1 \n",
"2063 Ox Mountain Sanitary Landfill 1.027866e+05 30 7.1 \n",
"2063 Ox Mountain Landfill 1.230834e+06 29 7.1 \n",
"2063 None 1.439942e+04 32 7.1 \n",
"... ... ... ... ... \n",
"3937 None 9.210236e+04 240 10.1 \n",
"3940 None 4.721976e+05 241 10.1 \n",
"3988 Lakeside Dump 6.116457e+04 152 6.2 \n",
"3991 None 3.068175e+05 119 6.2 \n",
"3991 None 5.301465e+05 118 6.2 \n",
"\n",
" zone_name \n",
"2062 MARINE WEST COAST FOREST \n",
"2062 MARINE WEST COAST FOREST \n",
"2063 MARINE WEST COAST FOREST \n",
"2063 MARINE WEST COAST FOREST \n",
"2063 MARINE WEST COAST FOREST \n",
"... ... \n",
"3937 COLD DESERTS \n",
"3940 COLD DESERTS \n",
"3988 WESTERN CORDILLERA \n",
"3991 WESTERN CORDILLERA \n",
"3991 WESTERN CORDILLERA \n",
"\n",
"[178 rows x 15 columns]"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matches = gp.sjoin(aviris_l2, bigguns, op='contains').rename(columns={'index_right': 'landfill_id', 'index_zone': 'zone', 'NA_L2NAME': 'zone_name'})\n",
"matches = gp.GeoDataFrame(matches.sort_values('area', ascending=False)[['Name', 'Site Name', 'Flight Scene', 'RDN Ver', 'Scene', 'GEO Ver', 'link_ftp', 'geometry', 'lfgeom', 'full_geom', 'name', 'area', 'landfill_id', 'zone', 'zone_name']], crs=aviris_l2.crs)\n",
"big_matches = matches.sort_values('Name').groupby(['landfill_id']).head(5)\n",
"big_matches"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Name</th>\n",
" <th>Site Name</th>\n",
" <th>Flight Scene</th>\n",
" <th>RDN Ver</th>\n",
" <th>Scene</th>\n",
" <th>GEO Ver</th>\n",
" <th>link_ftp</th>\n",
" <th>geometry</th>\n",
" <th>lfgeom</th>\n",
" <th>full_geom</th>\n",
" <th>name</th>\n",
" <th>area</th>\n",
" <th>landfill_id</th>\n",
" <th>zone_name</th>\n",
" </tr>\n",
" <tr>\n",
" <th>zone</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td>10.1</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>8</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <td>10.2</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>15</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <td>11.1</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>50</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" </tr>\n",
" <tr>\n",
" <td>6.2</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>4</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <td>7.1</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" <td>21</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <td>8.3</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>4</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <td>8.4</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <td>8.5</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <td>9.4</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Name Site Name Flight Scene RDN Ver Scene GEO Ver link_ftp \\\n",
"zone \n",
"10.1 11 11 11 11 11 11 11 \n",
"10.2 25 25 25 25 25 25 25 \n",
"11.1 74 74 74 74 74 74 74 \n",
"6.2 17 17 17 17 17 17 17 \n",
"7.1 36 36 36 36 36 36 36 \n",
"8.3 6 6 6 6 6 6 6 \n",
"8.4 7 7 7 7 7 7 7 \n",
"8.5 1 1 1 1 1 1 1 \n",
"9.4 1 1 1 1 1 1 1 \n",
"\n",
" geometry lfgeom full_geom name area landfill_id zone_name \n",
"zone \n",
"10.1 11 11 11 8 11 11 11 \n",
"10.2 25 25 25 15 25 25 25 \n",
"11.1 74 74 74 50 74 74 74 \n",
"6.2 17 17 17 4 17 17 17 \n",
"7.1 36 36 36 21 36 36 36 \n",
"8.3 6 6 6 4 6 6 6 \n",
"8.4 7 7 7 0 7 7 7 \n",
"8.5 1 1 1 0 1 1 1 \n",
"9.4 1 1 1 0 1 1 1 "
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"big_matches.groupby(['zone']).count()"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'aviris_f130410t01p00r10_sc01',\n",
" 'aviris_f130410t01p00r11_sc01',\n",
" 'aviris_f130410t01p00r13_sc01',\n",
" 'aviris_f130410t01p00r14_sc01',\n",
" 'aviris_f130410t01p00r15_sc01',\n",
" 'aviris_f130410t01p00r16_sc01',\n",
" 'aviris_f130410t01p00r18_sc01',\n",
" 'aviris_f130410t01p00r19_sc01',\n",
" 'aviris_f130412t01p00r07_sc01',\n",
" 'aviris_f130412t01p00r08_sc01',\n",
" 'aviris_f130412t01p00r09_sc01',\n",
" 'aviris_f130412t01p00r11_sc01',\n",
" 'aviris_f130412t01p00r13_sc01',\n",
" 'aviris_f130412t01p00r14_sc01',\n",
" 'aviris_f130419t01p00r08_sc01',\n",
" 'aviris_f130419t01p00r09_sc01',\n",
" 'aviris_f130419t01p00r10_sc01',\n",
" 'aviris_f130419t01p00r12_sc01',\n",
" 'aviris_f130419t01p00r13_sc01',\n",
" 'aviris_f130419t01p00r14_sc01',\n",
" 'aviris_f130419t01p00r15_sc01',\n",
" 'aviris_f130502t01p00r07_sc01',\n",
" 'aviris_f130502t01p00r18_sc01',\n",
" 'aviris_f130502t01p00r23_sc01',\n",
" 'aviris_f130503t01p00r14_sc01',\n",
" 'aviris_f130503t01p00r15_sc01',\n",
" 'aviris_f130503t01p00r22_sc01',\n",
" 'aviris_f130522t01p00r07_sc01',\n",
" 'aviris_f130522t01p00r08_sc01',\n",
" 'aviris_f130522t01p00r09_sc01',\n",
" 'aviris_f130522t01p00r11_sc01',\n",
" 'aviris_f130522t01p00r12_sc01',\n",
" 'aviris_f130522t01p00r13_sc01',\n",
" 'aviris_f130522t01p00r14_sc01',\n",
" 'aviris_f130522t01p00r15_sc01',\n",
" 'aviris_f130604t01p00r11_sc01',\n",
" 'aviris_f130606t01p00r05_sc01',\n",
" 'aviris_f130607t01p00r05_sc01',\n",
" 'aviris_f130607t01p00r08_sc01',\n",
" 'aviris_f130607t01p00r09_sc01',\n",
" 'aviris_f130607t01p00r10_sc01',\n",
" 'aviris_f130607t01p00r11_sc01',\n",
" 'aviris_f130607t01p00r12_sc01',\n",
" 'aviris_f130607t01p00r13_sc01',\n",
" 'aviris_f130607t01p00r14_sc01',\n",
" 'aviris_f130612t01p00r06_sc01',\n",
" 'aviris_f130612t01p00r07_sc01',\n",
" 'aviris_f130612t01p00r14_sc01',\n",
" 'aviris_f130626t01p00r07_sc01',\n",
" 'aviris_f130924t01p00r07_sc01',\n",
" 'aviris_f130924t01p00r08_sc01',\n",
" 'aviris_f130924t01p00r09_sc01',\n",
" 'aviris_f130924t01p00r11_sc01',\n",
" 'aviris_f130924t01p00r12_sc01',\n",
" 'aviris_f130924t01p00r13_sc01',\n",
" 'aviris_f131117t01p00r05_sc01',\n",
" 'aviris_f140331t01p00r12_sc01',\n",
" 'aviris_f140410t01p00r13_sc01',\n",
" 'aviris_f140414t01p00r07_sc01',\n",
" 'aviris_f140414t01p00r08_sc01',\n",
" 'aviris_f140414t01p00r11_sc01',\n",
" 'aviris_f140414t01p00r12_sc01',\n",
" 'aviris_f140414t01p00r13_sc01',\n",
" 'aviris_f140414t01p00r14_sc01',\n",
" 'aviris_f140418t01p00r07_sc01',\n",
" 'aviris_f140418t01p00r09_sc01',\n",
" 'aviris_f140418t01p00r10_sc01',\n",
" 'aviris_f140418t01p00r11_sc01',\n",
" 'aviris_f140423t01p00r07_sc01',\n",
" 'aviris_f140423t01p00r08_sc01',\n",
" 'aviris_f140507t01p00r06_sc01',\n",
" 'aviris_f140507t01p00r07_sc01',\n",
" 'aviris_f140507t01p00r13_sc01',\n",
" 'aviris_f140507t01p00r15_sc01',\n",
" 'aviris_f140528t01p00r06_sc01',\n",
" 'aviris_f140528t01p00r07_sc01',\n",
" 'aviris_f140528t01p00r08_sc01',\n",
" 'aviris_f140528t01p00r10_sc01',\n",
" 'aviris_f140602t01p00r15_sc01',\n",
" 'aviris_f140919t01p00r14_sc01',\n",
" 'aviris_f141027t01p00r07_sc01',\n",
" 'aviris_f151026t01p00r09_sc01',\n",
" 'aviris_f160518t01p00r09_sc01',\n",
" 'aviris_f170411t01p00r09_sc01',\n",
" 'aviris_f170416t01p00r14_sc01',\n",
" 'aviris_f170418t01p00r09_sc01',\n",
" 'aviris_f170418t01p00r11_sc01',\n",
" 'aviris_f170418t01p00r12_sc01',\n",
" 'aviris_f170514t01p00r29_sc01',\n",
" 'aviris_f171204t01p00r25_sc01',\n",
" 'aviris_f171214t01p00r08_sc01',\n",
" 'aviris_f171221t01p00r09_sc01',\n",
" 'aviris_f180529t01p00r06_sc01',\n",
" 'aviris_f180601t01p00r06_sc01',\n",
" 'aviris_f180604t01p00r07_sc01',\n",
" 'aviris_f180612t01p00r08_sc01',\n",
" 'aviris_f180612t01p00r10_sc01',\n",
" 'aviris_f180828t01p00r10_sc01',\n",
" 'aviris_f180831t01p00r08_sc01',\n",
" 'aviris_f180831t01p00r09_sc01',\n",
" 'aviris_f180904t01p00r06_sc01',\n",
" 'aviris_f180904t01p00r08_sc01',\n",
" 'aviris_f180917t01p00r05_sc01',\n",
" 'aviris_f180918t01p00r06_sc01',\n",
" 'aviris_f190808t01p00r14_sc01',\n",
" 'aviris_f190808t01p00r17_sc01'}"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matched_scenes = set(big_matches.apply(lambda r: 'aviris_' + r.Name + '_' + r.Scene, axis=1))\n",
"matched_scenes"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"106"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(matched_scenes)"
]
},
{
"cell_type": "code",
"execution_count": 474,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>index</th>\n",
" <th>Name</th>\n",
" <th>Site Name</th>\n",
" <th>RDN Ver</th>\n",
" <th>Scene</th>\n",
" <th>GEO Ver</th>\n",
" <th>link_ftp</th>\n",
" <th>geometry</th>\n",
" <th>lfgeom</th>\n",
" <th>name</th>\n",
" <th>area</th>\n",
" <th>landfill_id</th>\n",
" <th>NA_L2NAME</th>\n",
" <th>zone</th>\n",
" </tr>\n",
" <tr>\n",
" <th>index_right</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td>10.1</td>\n",
" <td>3701</td>\n",
" <td>f180529t01p00r06</td>\n",
" <td>HyspIRI_3_line32</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y18...</td>\n",
" <td>POLYGON ((-121.04159 36.73080, -120.85714 36.6...</td>\n",
" <td>POLYGON ((-119.62084 39.49681, -119.62092 39.4...</td>\n",
" <td>None</td>\n",
" <td>1.435014e+06</td>\n",
" <td>137</td>\n",
" <td>COLD DESERTS</td>\n",
" <td>10.1</td>\n",
" </tr>\n",
" <tr>\n",
" <td>10.2</td>\n",
" <td>3055</td>\n",
" <td>f160616t01p00r08</td>\n",
" <td>Southern California Box Line 2 (SC2)</td>\n",
" <td>b</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y16...</td>\n",
" <td>POLYGON ((-114.87205 33.21594, -114.81120 33.3...</td>\n",
" <td>POLYGON ((-116.14657 33.72820, -116.14663 33.7...</td>\n",
" <td>Coachella Valley Landfill</td>\n",
" <td>9.875919e+05</td>\n",
" <td>94</td>\n",
" <td>WARM DESERTS</td>\n",
" <td>10.2</td>\n",
" </tr>\n",
" <tr>\n",
" <td>11.1</td>\n",
" <td>3995</td>\n",
" <td>f190812t01p00r07</td>\n",
" <td>Caltech</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y19...</td>\n",
" <td>POLYGON ((-117.47714 33.75272, -117.40519 33.8...</td>\n",
" <td>POLYGON ((-117.48422 33.78428, -117.48441 33.7...</td>\n",
" <td>El Sobrante Landfill</td>\n",
" <td>3.089133e+06</td>\n",
" <td>73</td>\n",
" <td>MEDITERRANEAN CALIFORNIA</td>\n",
" <td>11.1</td>\n",
" </tr>\n",
" <tr>\n",
" <td>6.2</td>\n",
" <td>3991</td>\n",
" <td>f190808t01p00r17</td>\n",
" <td>U of Mt &amp; ISS</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y19...</td>\n",
" <td>POLYGON ((-113.10473 46.60822, -113.04788 46.7...</td>\n",
" <td>POLYGON ((-114.01335 46.89862, -114.01250 46.8...</td>\n",
" <td>None</td>\n",
" <td>5.301465e+05</td>\n",
" <td>118</td>\n",
" <td>WESTERN CORDILLERA</td>\n",
" <td>6.2</td>\n",
" </tr>\n",
" <tr>\n",
" <td>7.1</td>\n",
" <td>2189</td>\n",
" <td>f130607t01p00r14</td>\n",
" <td>Bay Area Box Line 3 (BA50)</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y13...</td>\n",
" <td>POLYGON ((-121.80473 36.40116, -121.67876 36.4...</td>\n",
" <td>POLYGON ((-122.41061 37.48980, -122.40944 37.4...</td>\n",
" <td>Ox Mountain Landfill</td>\n",
" <td>1.230834e+06</td>\n",
" <td>29</td>\n",
" <td>MARINE WEST COAST FOREST</td>\n",
" <td>7.1</td>\n",
" </tr>\n",
" <tr>\n",
" <td>8.4</td>\n",
" <td>3252</td>\n",
" <td>f170418t01p00r08</td>\n",
" <td>TBD</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y17...</td>\n",
" <td>POLYGON ((-86.68424 33.55326, -86.15099 33.613...</td>\n",
" <td>POLYGON ((-86.25551 33.68915, -86.25600 33.688...</td>\n",
" <td>None</td>\n",
" <td>5.718664e+05</td>\n",
" <td>164</td>\n",
" <td>OZARK/OUACHITA-APPALACHIAN FORESTS</td>\n",
" <td>8.4</td>\n",
" </tr>\n",
" <tr>\n",
" <td>8.5</td>\n",
" <td>3368</td>\n",
" <td>f170514t01p00r29</td>\n",
" <td>TBD</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y17...</td>\n",
" <td>POLYGON ((-81.14514 28.70486, -81.02047 28.763...</td>\n",
" <td>POLYGON ((-81.66279 29.71570, -81.66319 29.726...</td>\n",
" <td>None</td>\n",
" <td>7.159499e+05</td>\n",
" <td>256</td>\n",
" <td>MISSISSIPPI ALLUVIAL AND SOUTHEAST USA COASTAL...</td>\n",
" <td>8.5</td>\n",
" </tr>\n",
" <tr>\n",
" <td>9.4</td>\n",
" <td>3248</td>\n",
" <td>f170416t01p00r14</td>\n",
" <td>TBD</td>\n",
" <td>e</td>\n",
" <td>sc01</td>\n",
" <td>ort</td>\n",
" <td>ftp://avoil:[email protected]/y17...</td>\n",
" <td>POLYGON ((-94.61848 35.97854, -94.58005 36.660...</td>\n",
" <td>POLYGON ((-96.20002 36.16955, -96.20029 36.162...</td>\n",
" <td>None</td>\n",
" <td>1.361625e+06</td>\n",
" <td>187</td>\n",
" <td>SOUTH CENTRAL SEMI-ARID PRAIRIES</td>\n",
" <td>9.4</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" index Name Site Name \\\n",
"index_right \n",
"10.1 3701 f180529t01p00r06 HyspIRI_3_line32 \n",
"10.2 3055 f160616t01p00r08 Southern California Box Line 2 (SC2) \n",
"11.1 3995 f190812t01p00r07 Caltech \n",
"6.2 3991 f190808t01p00r17 U of Mt & ISS \n",
"7.1 2189 f130607t01p00r14 Bay Area Box Line 3 (BA50) \n",
"8.4 3252 f170418t01p00r08 TBD \n",
"8.5 3368 f170514t01p00r29 TBD \n",
"9.4 3248 f170416t01p00r14 TBD \n",
"\n",
" RDN Ver Scene GEO Ver \\\n",
"index_right \n",
"10.1 e sc01 ort \n",
"10.2 b sc01 ort \n",
"11.1 e sc01 ort \n",
"6.2 e sc01 ort \n",
"7.1 e sc01 ort \n",
"8.4 e sc01 ort \n",
"8.5 e sc01 ort \n",
"9.4 e sc01 ort \n",
"\n",
" link_ftp \\\n",
"index_right \n",
"10.1 ftp://avoil:[email protected]/y18... \n",
"10.2 ftp://avoil:[email protected]/y16... \n",
"11.1 ftp://avoil:[email protected]/y19... \n",
"6.2 ftp://avoil:[email protected]/y19... \n",
"7.1 ftp://avoil:[email protected]/y13... \n",
"8.4 ftp://avoil:[email protected]/y17... \n",
"8.5 ftp://avoil:[email protected]/y17... \n",
"9.4 ftp://avoil:[email protected]/y17... \n",
"\n",
" geometry \\\n",
"index_right \n",
"10.1 POLYGON ((-121.04159 36.73080, -120.85714 36.6... \n",
"10.2 POLYGON ((-114.87205 33.21594, -114.81120 33.3... \n",
"11.1 POLYGON ((-117.47714 33.75272, -117.40519 33.8... \n",
"6.2 POLYGON ((-113.10473 46.60822, -113.04788 46.7... \n",
"7.1 POLYGON ((-121.80473 36.40116, -121.67876 36.4... \n",
"8.4 POLYGON ((-86.68424 33.55326, -86.15099 33.613... \n",
"8.5 POLYGON ((-81.14514 28.70486, -81.02047 28.763... \n",
"9.4 POLYGON ((-94.61848 35.97854, -94.58005 36.660... \n",
"\n",
" lfgeom \\\n",
"index_right \n",
"10.1 POLYGON ((-119.62084 39.49681, -119.62092 39.4... \n",
"10.2 POLYGON ((-116.14657 33.72820, -116.14663 33.7... \n",
"11.1 POLYGON ((-117.48422 33.78428, -117.48441 33.7... \n",
"6.2 POLYGON ((-114.01335 46.89862, -114.01250 46.8... \n",
"7.1 POLYGON ((-122.41061 37.48980, -122.40944 37.4... \n",
"8.4 POLYGON ((-86.25551 33.68915, -86.25600 33.688... \n",
"8.5 POLYGON ((-81.66279 29.71570, -81.66319 29.726... \n",
"9.4 POLYGON ((-96.20002 36.16955, -96.20029 36.162... \n",
"\n",
" name area landfill_id \\\n",
"index_right \n",
"10.1 None 1.435014e+06 137 \n",
"10.2 Coachella Valley Landfill 9.875919e+05 94 \n",
"11.1 El Sobrante Landfill 3.089133e+06 73 \n",
"6.2 None 5.301465e+05 118 \n",
"7.1 Ox Mountain Landfill 1.230834e+06 29 \n",
"8.4 None 5.718664e+05 164 \n",
"8.5 None 7.159499e+05 256 \n",
"9.4 None 1.361625e+06 187 \n",
"\n",
" NA_L2NAME zone \n",
"index_right \n",
"10.1 COLD DESERTS 10.1 \n",
"10.2 WARM DESERTS 10.2 \n",
"11.1 MEDITERRANEAN CALIFORNIA 11.1 \n",
"6.2 WESTERN CORDILLERA 6.2 \n",
"7.1 MARINE WEST COAST FOREST 7.1 \n",
"8.4 OZARK/OUACHITA-APPALACHIAN FORESTS 8.4 \n",
"8.5 MISSISSIPPI ALLUVIAL AND SOUTHEAST USA COASTAL... 8.5 \n",
"9.4 SOUTH CENTRAL SEMI-ARID PRAIRIES 9.4 "
]
},
"execution_count": 474,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = matches_l2.reset_index()\n",
"large_lf = df.loc[df.groupby(['index_right'])['area'].idxmax()]\n",
"large_lf['zone'] = large_lf.index_right\n",
"large_lf.set_index('index_right', inplace=True)\n",
"del df\n",
"large_lf"
]
},
{
"cell_type": "code",
"execution_count": 475,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"index 3252\n",
"Name f170418t01p00r08\n",
"Site Name TBD\n",
"RDN Ver e\n",
"Scene sc01\n",
"GEO Ver ort\n",
"link_ftp ftp://avoil:[email protected]/y17...\n",
"geometry POLYGON ((-86.68424 33.553263, -86.150993 33.6...\n",
"lfgeom POLYGON ((-86.25550749999999 33.6891476, -86.2...\n",
"name None\n",
"area 571866\n",
"landfill_id 164\n",
"NA_L2NAME OZARK/OUACHITA-APPALACHIAN FORESTS\n",
"zone 8.4\n",
"Name: 8.4, dtype: object"
]
},
"execution_count": 475,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"selection = large_lf.loc['8.4']\n",
"selection"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Fetch AVIRIS data\n",
"\n",
"Only run this once, as it is time- and storage-intensive."
]
},
{
"cell_type": "code",
"execution_count": 476,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'f170418t01p00r08_refl.tar.gz'"
]
},
"execution_count": 476,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filename = '{}_refl.tar.gz'.format(selection.Name)\n",
"filename"
]
},
{
"cell_type": "code",
"execution_count": 477,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "04130d70e55640be9ab01c0beff26b7d",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"HBox(children=(HTML(value=''), FloatProgress(value=0.0, max=7483543352.0), HTML(value='')))"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"# Run this to download. MAY TAKE A LONG TIME\n",
"ftpurl = urlparse(selection.link_ftp)\n",
"ftpurl\n",
"\n",
"ftp = ftplib.FTP(ftpurl.hostname)\n",
"ftp.login(ftpurl.username, ftpurl.password)\n",
"ftp.cwd(dirname(ftpurl.path))\n",
"\n",
"with tqdm(total=ftp.size(filename)) as pb:\n",
" with open(os.path.join('data', filename), 'wb') as f:\n",
" def cb(data):\n",
" f.write(data)\n",
" pb.update(len(data))\n",
" \n",
" ftp.retrbinary('RETR ' + filename, cb)\n",
" \n",
"ftp.close()"
]
},
{
"cell_type": "code",
"execution_count": 479,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 479,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.system('tar xzf data/{} -C data'.format(filename))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load Hyperspectral Raster Data"
]
},
{
"cell_type": "code",
"execution_count": 480,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"('data/f170418t01p00r08_rfl_v1f5', 'f170418t01p00r08_corr_v1f5_img')"
]
},
"execution_count": 480,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"refl_dir, refl_file = [(d, list(filter(lambda f: '_corr' in f and not f.endswith('.hdr'), files))[0]) for (d, sds, files) in os.walk('data') if any(list(filter(lambda f: re.match('{}.*_corr.*'.format(selection.Name), f), files)))][0]\n",
"refl_dir, refl_file"
]
},
{
"cell_type": "code",
"execution_count": 481,
"metadata": {},
"outputs": [],
"source": [
"ds = rio.open(os.path.join(refl_dir, refl_file))"
]
},
{
"cell_type": "code",
"execution_count": 482,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"BoundingBox(left=497353.54, bottom=3712652.6835146835, right=578777.1591389138, top=3947013.812889095)"
]
},
"execution_count": 482,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds.bounds"
]
},
{
"cell_type": "code",
"execution_count": 483,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"300\" height=\"300\" viewBox=\"568684.3752147474 3726999.3858332774 847.7859150797594 1001.2109095044434\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,7454999.982576059)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"6.67473939669629\" opacity=\"0.6\" d=\"M 569002.4441650489,3727938.827409535 L 568957.2668862847,3727860.308043948 L 568886.3306153731,3727905.325405534 L 568844.8865091887,3727860.486073875 L 568921.1329604725,3727767.9937973223 L 568806.7508675428,3727632.5384632233 L 568721.4571002846,3727461.6670588525 L 568940.2928476395,3727040.548187161 L 569266.0403494154,3727036.4677188145 L 569426.3976716115,3727072.7673991397 L 569495.0792442899,3727202.9529571687 L 569459.2801945762,3727887.68812368 L 569405.0250968585,3727963.5148572447 L 569002.4441650489,3727938.827409535 z\" /></g></svg>"
],
"text/plain": [
"<shapely.geometry.polygon.Polygon at 0x7f71710e4e48>"
]
},
"execution_count": 483,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trans = partial(pyproj.transform, pyproj.Proj(init='EPSG:4326'), pyproj.Proj(ds.crs.to_string()))\n",
"footprint_utm = shapely.ops.transform(trans, selection.lfgeom)\n",
"footprint_utm"
]
},
{
"cell_type": "code",
"execution_count": 484,
"metadata": {},
"outputs": [],
"source": [
"xy_of = partial(rio.transform.xy, ds.transform)"
]
},
{
"cell_type": "code",
"execution_count": 485,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"300\" height=\"300\" viewBox=\"487989.2191356687 3703288.362650352 100152.26086757635 253089.77110307384\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,7659666.496403778)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"1687.265140687159\" opacity=\"0.6\" d=\"M 497362.9143617085,3940055.1359117674 L 546809.7717845676,3947004.438527386 L 578767.7847772053,3719611.3604920106 L 529320.9273543463,3712662.057876392 L 497362.9143617085,3940055.1359117674 z M 569002.4441650489,3727938.827409535 L 568957.2668862847,3727860.308043948 L 568886.3306153731,3727905.325405534 L 568844.8865091887,3727860.486073875 L 568921.1329604725,3727767.9937973223 L 568806.7508675428,3727632.5384632233 L 568721.4571002846,3727461.6670588525 L 568940.2928476395,3727040.548187161 L 569266.0403494154,3727036.4677188145 L 569426.3976716115,3727072.7673991397 L 569495.0792442899,3727202.9529571687 L 569459.2801945762,3727887.68812368 L 569405.0250968585,3727963.5148572447 L 569002.4441650489,3727938.827409535 z\" /></g></svg>"
],
"text/plain": [
"<shapely.geometry.polygon.Polygon at 0x7f7170dd0e80>"
]
},
"execution_count": 485,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(r, c) = ds.shape\n",
"swath = shapely.ops.transform(xy_of, shapely.geometry.Polygon([(0,0), (r-1,0), (r-1, c-1), (0,c-1), (0,0)]))\n",
"swath.difference(footprint_utm)"
]
},
{
"cell_type": "code",
"execution_count": 486,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Window(col_off=2466, row_off=13246, width=65, height=74)\n"
]
},
{
"data": {
"image/svg+xml": [
"<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"300\" height=\"300\" viewBox=\"568448.0998048221 3726754.6409638566 1328.5399078273913 1455.6934960139915\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,7454964.975423727)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"9.704623306759943\" opacity=\"0.6\" d=\"M 568502.0143787486,3728008.562383484 L 569554.0751749796,3728156.419885944 L 569722.725138723,3726956.413040243 L 568670.664342492,3726808.555537783 L 568502.0143787486,3728008.562383484 z M 569002.4441650489,3727938.827409535 L 568957.2668862847,3727860.308043948 L 568886.3306153731,3727905.325405534 L 568844.8865091887,3727860.486073875 L 568921.1329604725,3727767.9937973223 L 568806.7508675428,3727632.5384632233 L 568721.4571002846,3727461.6670588525 L 568940.2928476395,3727040.548187161 L 569266.0403494154,3727036.4677188145 L 569426.3976716115,3727072.7673991397 L 569495.0792442899,3727202.9529571687 L 569459.2801945762,3727887.68812368 L 569405.0250968585,3727963.5148572447 L 569002.4441650489,3727938.827409535 z\" /></g></svg>"
],
"text/plain": [
"<shapely.geometry.polygon.Polygon at 0x7f7170b5ecf8>"
]
},
"execution_count": 486,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"w = rio.features.geometry_window(ds, [footprint_utm], rotated=True, pad_x=.5, pad_y=.5)\n",
"print(w)\n",
"shapely.ops.transform(xy_of, shapely.geometry.Polygon(\n",
" [(w.row_off,w.col_off), \n",
" (w.row_off + w.height - 1,w.col_off), \n",
" (w.row_off + w.height - 1, w.col_off + w.width - 1), \n",
" (w.row_off,w.col_off + w.width - 1), \n",
" (w.row_off,w.col_off)])).difference(footprint_utm)"
]
},
{
"cell_type": "code",
"execution_count": 487,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7f711d32be10>"
]
},
"execution_count": 487,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"lf_rgb = ds.read([30,20,10], window=w)\n",
"fig, ax = plt.subplots(1,1,figsize=(10,10))\n",
"ax.imshow(np.dstack(lf_rgb)/np.max(lf_rgb))"
]
},
{
"cell_type": "code",
"execution_count": 488,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7f717115d630>"
]
},
"execution_count": 488,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"lf_tmp = ds.read(30)\n",
"plt.imshow(lf_tmp)"
]
},
{
"cell_type": "code",
"execution_count": 275,
"metadata": {},
"outputs": [],
"source": [
"import pysptools"
]
},
{
"cell_type": "code",
"execution_count": 489,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(224, 74, 65)"
]
},
"execution_count": 489,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lf_area = ds.read(window=w)\n",
"lf_area.shape"
]
},
{
"cell_type": "code",
"execution_count": 490,
"metadata": {},
"outputs": [],
"source": [
"from pysptools.eea import nfindr"
]
},
{
"cell_type": "code",
"execution_count": 491,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f70ee66ed68>]"
]
},
"execution_count": 491,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(lf_area[:,0,0])"
]
},
{
"cell_type": "code",
"execution_count": 493,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7f70ee0f4588>"
]
},
"execution_count": 493,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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0OH8X+BsROQ74wIdUNbmqqf8o6aBbpkNkw8X0FxKY4dT7xYy4NwI3FqY6ILUNT4tTRGJ3Rsfzhl2LXHu+Rb3kGj3ovPFlHrozF+qAzIdx2Q3TPZH42OV+NYc9dTs0m7cGLgkGAnuOXpnQVtHUDFCT5twBQw10QYe+hCTR3ZzVQRsF3lESe2FCuzAN1lV087VKQH0tNyFdpf0pEhroqEdAL2pgrzBnontRAwdkYzlqYEfNmwvSXA7LoFcE1n3YxM3KhZe9z5wwmFBYOAlBFqp5DQwElsECeqO1Pydl+IV+UkQOWv6fF1rnPmbEXh8Ukd+vlfuuogE1RZehkUutrOoXCvA5y//zFgAROYdgS/JXmmv+KXSxaBJddp9Pg+s4NoxXZtxbyS80BxcBXzLOTf9LoJeWuov1ZkKbTlV12sDLjGv9laFeNiXEXmf8QktgGabWbA+1or88VB1GXAF8imBh66eAzxA4+Dpjyi/U26Gl1wKWIbGEcM5UshlCQKVX6nZtha6qHgqPReQLwNfNTyex1yREPGR11Q4IE5pZ5gyA58WyJCNLbSIslKzORSgrEi7Ftu8dviS+tSjQFtTDSIdAoNWWhfB6X2PpkDA/tnje+rRwW6owQ6gxs04mKhEoIqdZIq7vBMIe6s3AdSLyWeClBH6h/+10U0uzJVMCK3yDRyNk69bgeHUlJvCoMcVJ4sPzoU6L7wd6LqEahGqqHppuD9LwRxK8NEfWZ+JM3UMVCYnZmATxRqN4/f+WWJlYDx8x9wqlUyZgdG5sHbgpDYAUVPULfZOI7CYwoY8CHwyeQe8VkRuA+whc7i9V1eJ1rrbQj/UAM6IFEhMYqh7p2kqkuSK+H8TZmAQ1M0RSKcn3A/Ge6LfG8S3VRF0xoj0jQVdGeGENnFgSIuG+8z6IxqvqJdSrGY1gYmqwpdQUif5EspNe/HzhS+GwN0VHpLZ26LnjEkNGS62wTSQLr5WyyjPHxoTuX7+u21JbkJC9Sp6daRu8KL6IzBZs0sSFvzMUoLIkK2c2v8rMYYw8kqfScdGCCfPedBvYOJKCr8nTid/iWYSX0Au1xXymChPS20DLlIX5LESo22apAkf5sl7SiMCl0AuVkmM78RCbwEhDrVjhKYqXrI1pSoHJMBfB1zCNML7nxfmyXproZUpTS7FfroKRejcILCkzIp6fboKK7mEPNxxqU1SQjtJX0zJb4ZBGp4+z8mqpFZYRGOoGgTWQ+rYme6/JwvIcdx4rqdgb1ToSNSdNHjpJUtZkRT9MqMQmEWYLP2FeswRfJacdBeI2SP1IxDW+6exAPurqSzAOjMZkWVsT+BpdL2GttUXyVi290GMpY8ronsYMiwSWpuudGPEEb+uWOCCLwLCQV1fg5JOC0yesIRtBIXjPHUE9QTYmMTlWG6lbzUB6/TisreKvWo8/NoV2LJ4hWT8l2NNpsurhr3is/jIoSW8jLnTfjBXFV2Ti4z0fxJH149FAPhzcT045Mbpu9OQzwUGoIWq3y+O4fZfjG/B8dtl1gkCY7rUVtmWTSVTb5Ng4ftsnE8RPqNzaZsgUpEx8dP04XtgmiaBGV1uOxzVw9EIQ3zvmoSseo6MbM3HCl4eJIr4fkSXHN4LeNUQkeYetqpTQC1XfR6z82M+ah24Q6CsYPeqpLn0Sdq/w2eeCoBcOx0KvfkrX3CbwiLXxhzdtsqMis64dP20NIzxHvdBJOIzwoym9qHOzHhMYaWZbArGatDT2+Qx0g8A82KYlTZB865ZYfvnw0VijemoBp5kCMzrbTCZB2zm2SfTic2HSJwa7yejaCB15jJ43c622dLI1PcfGJJ4LDdu40ShqO2Xb1uiyqBcdqfRamtn2NGDBO9MNAj0PsSZ6Z97ApBi4N4ommnX7lsiMiZgvDOGcaBAYmynTiZCJj66M47lJjzi+Nc85+ZWgXZ5sGeGveKyYgvUsE6rjWAhdJj7eEXPPlXGQzjhuA/0TYwK98CWwdbjDPEQC8GZeN+dzeicIVN/HP3LUOb6IwGEjjuF50WceDQsh5zMUGDOdI64eYmzuMU5uLZADW/5Zk2G/+GUUz0+a47QvHMnwtDwW5mgeKJhKCxEJA0D85ibHT8k2o8aqooiuEgTO5CVLMXipBF/B6YFSP0zZO7+mSis3oNpa6xYT69ma11zuDoFVkUZ8Bxx154WqfqFftnxCHxWRe0x4O3qhAzLhUgOvAv4BuCYMUNU/Co9F5DPAM1b8R1R1d1MZbAV2u1T1+hBZ+w3OyQq4KDV9W0TOTDsnwezsu4C3NJutAjSx3LlpUYOq9y/aEqHlgfwbgUOq+pAVdpaIfB94FviEqv5nzTRmUfXtrltD8va4LeoNF6HiM9Ul8GLgeuu3s16oiOwF9gJsYVvNbDiirlnLqy0L6jjV0QsdA38IfDkMK6MXqqr7VHWPqu5ZYS0tSnUUma82FSfmLNBeJ6XfAx5Q1cfCgM7rhWYVbhNid8lzcyLRZRhxPfBd4BUi8piIfMCcejfT5hMCvdAfmGHFV+ijXmhZ7e4Fb4lQVS8UVX1fSlh/9ELrDiVc04BW01mOFbpptaBszSgyjx1FP6fSXAbSeWEu55LnO0pivwis0wFZJFyHHRXGkj14+gF56FcNXCYkOzgVrUs/COyDmVwQ+kHgMqPmyzm82j3HQGDP0W0Ch7avEN0uIdsndEAqhtLpObpN4FD7CjEMIyrAXg6+aOG9bhI41DxnuHzQPV1EviUi94nIvSLyYRO+Q0T2i8hD5v+LTLiIyOeNZugPROQ1bT/EZobLq74BfFRVzwHOBS41uqCXA7ep6i7gNvMb4AICV4pdBE5LV5TOVYf3aQBKa3q2iUICVfVxVb3bHD8H3E8gIXkRcLWJdjXwDnN8EXCNBrgdOFlETquUuw6T2BWUamyMg++rge8BOy3Bu58BO82xs2aoEwYSc+FMoIicQODv8pGkn6fZhryUPakj+DoghhOBIrJCQN61qvpVE3woNI3m/xMm3EkztFW/0E0El16oEOxafb+qftY6dTNwiTm+BPiaFf5e0xs9F3jGMrXV0PFOTS3UfDaXceDrgfcAPwyXkQEfBz4N3GD8RH9CsMgF4BbgQgLB88PA+yvnbpmRJK3ivK+LX+h3IFNp8byU+ApcWjonA2bdKxxqZjdnYrKQ9UAu/iV59yta2lV3ZqjFlUrDnFXP0a8amAXXdfJ5Ncll6ViVmthy52s5CEyiaGu55LqIrOO867PiD9uQDyiD5ayBbcOlls4Jm7MGLtGkwOYkcIkwENg0erRGvr+oUsAddfPYnJ2YKm2g6zVDJ2ZAGfS/Bmap+7rMc87DLA4zMQVI+yyT99v1XE8wmNCeo781sO1PQE1i6SWXhemtdwrje+n7EZXYfi55bSqSO5ml7RuRsbNZ4WaRRRs/2nG6vvWO6+5l0ZoE9SP5aU2T5kgKjZvjZNzCXcLC3VXytsbL2wewquh5CWntTmzBKiJPAi8AP190XmrgxbSX/19T1VPTTnSCQAARuTNrn9g+YFH571BLP6AKBgJ7ji4RuG/RGaiJheS/M23ggGroUg0cUAELJ1BEzheRB82K3suLr+gGzI41PzQ71NxpwlJXLbeJhRJoBNL/kWBV7znAxWb1b1/wZlXdbQ0fslYtt4ZF18DXAg+r6gFVXQe+RLDCt6/IWrXcGhZNYLOreecLBW4VkbvMJiaQvWq5NXRjLrSfeIOqHhSRlwD7ReQB+6Sqqoi03sVfdA10Ws3bRajqQfP/CeAmguYga9Vya1g0gXcAu0TkLBFZJdhM5OYF56kQIrJdRE4Mj4G3AT8ie9Vya1ioCVXVDRG5DPgmMAKuVNV7F5knR+wEbjLfE8fAdar6DRG5g/RVy61hmInpORZtQgfUxEBgzzEQ2HMMBPYcA4E9x0BgzzEQ2HMMBPYc/w9Ujq2NHwg6JAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(lf_area[:,:,50])"
]
},
{
"cell_type": "code",
"execution_count": 496,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7f70edfe9978>"
]
},
"execution_count": 496,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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