diff --git a/app.py b/app.py index ad117d6..b4bdce0 100644 --- a/app.py +++ b/app.py @@ -432,7 +432,7 @@ def serve_map( cog_url = f"https://burn-severity-backend.s3.us-east-2.amazonaws.com/public/{affiliation}/{fire_event_name}/{burn_metric}.tif" burn_boundary_geojson_url = f"https://burn-severity-backend.s3.us-east-2.amazonaws.com/public/{affiliation}/{fire_event_name}/boundary.geojson" ecoclass_geojson_url = f"https://burn-severity-backend.s3.us-east-2.amazonaws.com/public/{affiliation}/{fire_event_name}/ecoclass_dominant_cover.geojson" - + severity_obs_geojson_url = f"https://burn-severity-backend.s3.us-east-2.amazonaws.com/public/{affiliation}/{fire_event_name}/burn_field_observations.geojson" cog_tileserver_url_prefix = ( tileserver_endpoint + f"/cog/tiles/WebMercatorQuad/{{z}}/{{x}}/{{y}}.png?url={cog_url}&nodata=-99&return_mask=true" @@ -456,6 +456,7 @@ def serve_map( "cog_tileserver_url_prefix": cog_tileserver_url_prefix, "burn_boundary_geojson_url": burn_boundary_geojson_url, "ecoclass_geojson_url": ecoclass_geojson_url, + "severity_obs_geojson_url": severity_obs_geojson_url }, ) diff --git a/exploratory/ground_truth_comparison_york.ipynb b/exploratory/ground_truth_comparison_york.ipynb index 8e7fc0b..ec71e56 100644 --- a/exploratory/ground_truth_comparison_york.ipynb +++ b/exploratory/ground_truth_comparison_york.ipynb @@ -2,18 +2,24 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 101, "metadata": {}, "outputs": [], "source": [ "import rioxarray as rxr\n", + "import rasterio\n", + "from rasterio.windows import from_bounds\n", + "from rasterio.plot import show\n", "import geopandas as gpd\n", "import pandas as pd\n", "import numpy as np\n", "import requests\n", "import tempfile\n", "import os\n", - "from shapely.geometry import Point\n" + "from shapely.geometry import Point\n", + "from shapely.geometry import mapping\n", + "\n", + "import seaborn as sns\n" ] }, { @@ -442,8 +448,8 @@ " AREA_OR_POINT: Area\n", " scale_factor: 1.0\n", " add_offset: 0.0\n", - " long_name: stackstac-a396c2701a14f53fb07f569bb80fc46e
<xarray.DataArray (band: 4, y: 1277, x: 882)>\n", + "array([[[nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " ...,\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan]],\n", + "\n", + " [[nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " ...,\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan]],\n", + "\n", + " [[nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " ...,\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan]],\n", + "\n", + " [[nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " ...,\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)\n", + "Coordinates:\n", + " * x (x) float64 -115.3 -115.3 -115.3 ... -115.1 -115.1 -115.1\n", + " * y (y) float64 35.48 35.48 35.48 35.48 ... 35.13 35.13 35.13 35.13\n", + " * band (band) <U24 'annual_forb_and_grass' ... 'tree'\n", + " spatial_ref int64 0\n", + "Attributes:\n", + " AREA_OR_POINT: Area\n", + " scale_factor: 1.0\n", + " add_offset: 0.0
\n", + " | FieldDescription | \n", + "TimeStamp | \n", + "Longitude | \n", + "Latitude | \n", + "SeverityFactor | \n", + "geometry | \n", + "mean_rbr | \n", + "median_rbr | \n", + "std_rbr | \n", + "mean_dnbr | \n", + "... | \n", + "std_annual | \n", + "mean_perennial | \n", + "median_perennial | \n", + "std_perennial | \n", + "mean_shrub | \n", + "median_shrub | \n", + "std_shrub | \n", + "mean_tree | \n", + "median_tree | \n", + "std_tree | \n", + "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
FID | \n", + "\n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " |
1 | \n", + "High Severity | \n", + "8/1/2023 0:00 | \n", + "-115.172180 | \n", + "35.296247 | \n", + "3 | \n", + "POINT (-115.17218 35.29625) | \n", + "0.024699 | \n", + "0.024442 | \n", + "0.018938 | \n", + "0.023293 | \n", + "... | \n", + "103.304161 | \n", + "282.522736 | \n", + "257.5 | \n", + "139.753098 | \n", + "162.977280 | \n", + "156.5 | \n", + "33.189190 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
2 | \n", + "High severity | \n", + "8/2/2023 0:00 | \n", + "-115.226196 | \n", + "35.302168 | \n", + "3 | \n", + "POINT (-115.22620 35.30217) | \n", + "0.102397 | \n", + "0.106216 | \n", + "0.020557 | \n", + "0.104615 | \n", + "... | \n", + "112.976540 | \n", + "346.568176 | \n", + "331.5 | \n", + "92.655373 | \n", + "97.295456 | \n", + "94.5 | \n", + "22.640049 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
3 | \n", + "High severity/mortality YUJA woodlands | \n", + "7/31/2023 0:00 | \n", + "-115.257442 | \n", + "35.316332 | \n", + "3 | \n", + "POINT (-115.25744 35.31633) | \n", + "0.106372 | \n", + "0.119165 | \n", + "0.042621 | \n", + "0.100870 | \n", + "... | \n", + "88.111481 | \n", + "267.386353 | \n", + "255.0 | \n", + "77.804596 | \n", + "116.090912 | \n", + "107.5 | \n", + "27.947855 | \n", + "0.409091 | \n", + "0.0 | \n", + "1.642036 | \n", + "
4 | \n", + "Higher burn severity | \n", + "7/31/2023 0:00 | \n", + "-115.215690 | \n", + "35.253257 | \n", + "3 | \n", + "POINT (-115.21569 35.25326) | \n", + "0.060968 | \n", + "0.062762 | \n", + "0.011493 | \n", + "0.060097 | \n", + "... | \n", + "83.382179 | \n", + "89.568184 | \n", + "87.0 | \n", + "40.422428 | \n", + "206.613632 | \n", + "218.0 | \n", + "33.955330 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
5 | \n", + "Higher severity | \n", + "7/31/2023 0:00 | \n", + "-115.227215 | \n", + "35.289627 | \n", + "3 | \n", + "POINT (-115.22722 35.28963) | \n", + "0.111190 | \n", + "0.113145 | \n", + "0.026096 | \n", + "0.110387 | \n", + "... | \n", + "206.073257 | \n", + "307.023804 | \n", + "299.0 | \n", + "128.363785 | \n", + "136.857147 | \n", + "133.0 | \n", + "49.128872 | \n", + "3.238095 | \n", + "3.0 | \n", + "3.235293 | \n", + "
6 | \n", + "Moderate severity | \n", + "7/31/2023 0:00 | \n", + "-115.192904 | \n", + "35.282274 | \n", + "2 | \n", + "POINT (-115.19290 35.28227) | \n", + "0.020500 | \n", + "0.017782 | \n", + "0.016273 | \n", + "0.019169 | \n", + "... | \n", + "39.825161 | \n", + "251.738098 | \n", + "248.0 | \n", + "85.621834 | \n", + "149.785721 | \n", + "150.0 | \n", + "21.808186 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
7 | \n", + "Moderate severity | \n", + "8/1/2023 0:00 | \n", + "-115.094502 | \n", + "35.369178 | \n", + "2 | \n", + "POINT (-115.09450 35.36918) | \n", + "0.001457 | \n", + "0.002989 | \n", + "0.013128 | \n", + "0.001496 | \n", + "... | \n", + "34.542362 | \n", + "140.023254 | \n", + "154.0 | \n", + "47.302826 | \n", + "157.116272 | \n", + "164.0 | \n", + "22.492592 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
8 | \n", + "Moderate severity | \n", + "8/2/2023 0:00 | \n", + "-115.235698 | \n", + "35.271425 | \n", + "2 | \n", + "POINT (-115.23570 35.27143) | \n", + "0.096596 | \n", + "0.093328 | \n", + "0.020483 | \n", + "0.098350 | \n", + "... | \n", + "102.576653 | \n", + "192.659088 | \n", + "183.0 | \n", + "44.351868 | \n", + "291.818176 | \n", + "290.5 | \n", + "37.573730 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
9 | \n", + "Moderate severity YucSch woodlands | \n", + "7/31/2023 0:00 | \n", + "-115.296759 | \n", + "35.333723 | \n", + "2 | \n", + "POINT (-115.29676 35.33372) | \n", + "0.042095 | \n", + "0.039985 | \n", + "0.015772 | \n", + "0.039242 | \n", + "... | \n", + "48.053261 | \n", + "205.804352 | \n", + "200.0 | \n", + "36.980381 | \n", + "57.304348 | \n", + "57.5 | \n", + "11.460461 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
10 | \n", + "Moderate to high burn severity | \n", + "8/1/2023 0:00 | \n", + "-115.122348 | \n", + "35.277762 | \n", + "2 | \n", + "POINT (-115.12235 35.27776) | \n", + "0.012562 | \n", + "0.011840 | \n", + "0.016986 | \n", + "0.011788 | \n", + "... | \n", + "108.329704 | \n", + "161.761902 | \n", + "177.0 | \n", + "88.403244 | \n", + "128.404755 | \n", + "134.5 | \n", + "31.567810 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
11 | \n", + "Unburned island | \n", + "8/1/2023 0:00 | \n", + "-115.129428 | \n", + "35.286565 | \n", + "0 | \n", + "POINT (-115.12943 35.28657) | \n", + "-0.001654 | \n", + "0.003890 | \n", + "0.017782 | \n", + "-0.001566 | \n", + "... | \n", + "61.522537 | \n", + "90.500000 | \n", + "78.5 | \n", + "49.937008 | \n", + "176.159088 | \n", + "176.5 | \n", + "34.917400 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
12 | \n", + "Unburned island | \n", + "8/2/2023 0:00 | \n", + "-115.231058 | \n", + "35.267588 | \n", + "0 | \n", + "POINT (-115.23106 35.26759) | \n", + "0.080986 | \n", + "0.081213 | \n", + "0.021327 | \n", + "0.082158 | \n", + "... | \n", + "131.706543 | \n", + "221.209305 | \n", + "223.0 | \n", + "31.389940 | \n", + "249.255814 | \n", + "268.0 | \n", + "64.227104 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
13 | \n", + "Unburned--finger? | \n", + "7/31/2023 0:00 | \n", + "-115.207741 | \n", + "35.279457 | \n", + "0 | \n", + "POINT (-115.20774 35.27946) | \n", + "-0.006817 | \n", + "-0.006288 | \n", + "0.021808 | \n", + "-0.006431 | \n", + "... | \n", + "61.256382 | \n", + "143.238098 | \n", + "148.0 | \n", + "37.888813 | \n", + "207.119049 | \n", + "211.0 | \n", + "22.410883 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
14 | \n", + "High Severity | \n", + "8/1/2023 0:00 | \n", + "-115.172180 | \n", + "35.296247 | \n", + "3 | \n", + "POINT (-115.17218 35.29625) | \n", + "0.024699 | \n", + "0.024442 | \n", + "0.018938 | \n", + "0.023293 | \n", + "... | \n", + "103.304161 | \n", + "282.522736 | \n", + "257.5 | \n", + "139.753098 | \n", + "162.977280 | \n", + "156.5 | \n", + "33.189190 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
16 | \n", + "High severity PJ | \n", + "8/3/2023 0:00 | \n", + "-115.316134 | \n", + "35.208602 | \n", + "3 | \n", + "POINT (-115.31613 35.20860) | \n", + "0.112572 | \n", + "0.101215 | \n", + "0.047771 | \n", + "0.114672 | \n", + "... | \n", + "179.821365 | \n", + "496.809509 | \n", + "426.0 | \n", + "225.833710 | \n", + "207.809525 | \n", + "198.5 | \n", + "64.740227 | \n", + "11.357142 | \n", + "7.0 | \n", + "13.001504 | \n", + "
17 | \n", + "High severity to West, unburned to east | \n", + "8/3/2023 0:00 | \n", + "-115.224903 | \n", + "35.156179 | \n", + "3 | \n", + "POINT (-115.22490 35.15618) | \n", + "0.033149 | \n", + "0.033944 | \n", + "0.018731 | \n", + "0.031423 | \n", + "... | \n", + "67.173683 | \n", + "111.232559 | \n", + "107.0 | \n", + "45.175026 | \n", + "300.883728 | \n", + "305.0 | \n", + "34.245491 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
18 | \n", + "Low burn severity to south, unburned island to... | \n", + "8/3/2023 0:00 | \n", + "-115.221711 | \n", + "35.204250 | \n", + "1 | \n", + "POINT (-115.22171 35.20425) | \n", + "-0.022651 | \n", + "-0.021357 | \n", + "0.017668 | \n", + "-0.021052 | \n", + "... | \n", + "38.980240 | \n", + "76.534882 | \n", + "69.0 | \n", + "22.414021 | \n", + "211.883728 | \n", + "199.0 | \n", + "31.653067 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
19 | \n", + "Low severity | \n", + "8/3/2023 0:00 | \n", + "-115.301319 | \n", + "35.237364 | \n", + "1 | \n", + "POINT (-115.30132 35.23736) | \n", + "0.148797 | \n", + "0.141168 | \n", + "0.035505 | \n", + "0.150196 | \n", + "... | \n", + "166.941757 | \n", + "903.071411 | \n", + "889.5 | \n", + "108.627235 | \n", + "104.904762 | \n", + "86.0 | \n", + "56.207443 | \n", + "239.738098 | \n", + "174.5 | \n", + "114.852303 | \n", + "
20 | \n", + "Low to moderate severity | \n", + "8/3/2023 0:00 | \n", + "-115.233663 | \n", + "35.206701 | \n", + "1 | \n", + "POINT (-115.23366 35.20670) | \n", + "0.029629 | \n", + "0.028415 | \n", + "0.010081 | \n", + "0.027202 | \n", + "... | \n", + "51.773624 | \n", + "88.046509 | \n", + "72.0 | \n", + "38.465904 | \n", + "282.604645 | \n", + "275.0 | \n", + "32.870529 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
21 | \n", + "Moderate severity | \n", + "8/3/2023 0:00 | \n", + "-115.214888 | \n", + "35.204096 | \n", + "2 | \n", + "POINT (-115.21489 35.20410) | \n", + "0.019244 | \n", + "0.018969 | \n", + "0.016806 | \n", + "0.017979 | \n", + "... | \n", + "56.552025 | \n", + "104.000000 | \n", + "102.0 | \n", + "36.576252 | \n", + "237.422226 | \n", + "233.0 | \n", + "26.598654 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
22 | \n", + "Moderate severity | \n", + "8/3/2023 0:00 | \n", + "-115.220717 | \n", + "35.139797 | \n", + "2 | \n", + "POINT (-115.22072 35.13980) | \n", + "0.016977 | \n", + "0.018449 | \n", + "0.007305 | \n", + "0.016302 | \n", + "... | \n", + "92.808319 | \n", + "66.146339 | \n", + "67.0 | \n", + "26.265587 | \n", + "192.243896 | \n", + "190.0 | \n", + "21.043255 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
23 | \n", + "Moderate to high severity | \n", + "8/3/2023 0:00 | \n", + "-115.303512 | \n", + "35.233042 | \n", + "2 | \n", + "POINT (-115.30351 35.23304) | \n", + "0.200694 | \n", + "0.179267 | \n", + "0.053459 | \n", + "0.209674 | \n", + "... | \n", + "352.549713 | \n", + "676.340881 | \n", + "692.0 | \n", + "184.750320 | \n", + "244.181824 | \n", + "177.0 | \n", + "157.436462 | \n", + "548.431824 | \n", + "386.0 | \n", + "376.202209 | \n", + "
24 | \n", + "Retardant unburned island | \n", + "8/3/2023 0:00 | \n", + "-115.225096 | \n", + "35.173054 | \n", + "0 | \n", + "POINT (-115.22510 35.17305) | \n", + "-0.030324 | \n", + "-0.020591 | \n", + "0.040036 | \n", + "-0.028315 | \n", + "... | \n", + "57.007919 | \n", + "135.555557 | \n", + "131.0 | \n", + "42.802158 | \n", + "267.511108 | \n", + "270.0 | \n", + "14.223021 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
25 | \n", + "Unburned | \n", + "8/3/2023 0:00 | \n", + "-115.188494 | \n", + "35.149512 | \n", + "0 | \n", + "POINT (-115.18849 35.14951) | \n", + "0.002289 | \n", + "-0.001333 | \n", + "0.013747 | \n", + "0.002264 | \n", + "... | \n", + "51.054508 | \n", + "90.619049 | \n", + "94.0 | \n", + "19.827774 | \n", + "166.261902 | \n", + "158.0 | \n", + "29.021387 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
26 | \n", + "Unburned island | \n", + "8/3/2023 0:00 | \n", + "-115.282752 | \n", + "35.213657 | \n", + "0 | \n", + "POINT (-115.28275 35.21366) | \n", + "0.071104 | \n", + "0.069587 | \n", + "0.033753 | \n", + "0.070116 | \n", + "... | \n", + "111.327255 | \n", + "147.000000 | \n", + "140.5 | \n", + "39.517326 | \n", + "407.476196 | \n", + "395.5 | \n", + "55.851521 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
27 | \n", + "Unburned island | \n", + "8/3/2023 0:00 | \n", + "-115.300323 | \n", + "35.225254 | \n", + "0 | \n", + "POINT (-115.30032 35.22525) | \n", + "0.070385 | \n", + "0.056470 | \n", + "0.042253 | \n", + "0.069747 | \n", + "... | \n", + "322.200745 | \n", + "357.738098 | \n", + "368.5 | \n", + "97.129776 | \n", + "202.428574 | \n", + "169.5 | \n", + "93.113640 | \n", + "21.095238 | \n", + "11.0 | \n", + "21.041693 | \n", + "
28 | \n", + "Unburned with patches of light severity | \n", + "8/1/2023 0:00 | \n", + "-115.105516 | \n", + "35.321570 | \n", + "0 | \n", + "POINT (-115.10552 35.32157) | \n", + "-0.059228 | \n", + "-0.060158 | \n", + "0.009884 | \n", + "-0.054010 | \n", + "... | \n", + "28.099245 | \n", + "184.727280 | \n", + "184.5 | \n", + "46.518505 | \n", + "93.568184 | \n", + "89.5 | \n", + "18.868443 | \n", + "0.000000 | \n", + "0.0 | \n", + "0.000000 | \n", + "
27 rows × 24 columns
\n", + "" + ], + "text/plain": [ + " FieldDescription TimeStamp \\\n", + "FID \n", + "1 High Severity 8/1/2023 0:00 \n", + "2 High severity 8/2/2023 0:00 \n", + "3 High severity/mortality YUJA woodlands 7/31/2023 0:00 \n", + "4 Higher burn severity 7/31/2023 0:00 \n", + "5 Higher severity 7/31/2023 0:00 \n", + "6 Moderate severity 7/31/2023 0:00 \n", + "7 Moderate severity 8/1/2023 0:00 \n", + "8 Moderate severity 8/2/2023 0:00 \n", + "9 Moderate severity YucSch woodlands 7/31/2023 0:00 \n", + "10 Moderate to high burn severity 8/1/2023 0:00 \n", + "11 Unburned island 8/1/2023 0:00 \n", + "12 Unburned island 8/2/2023 0:00 \n", + "13 Unburned--finger? 7/31/2023 0:00 \n", + "14 High Severity 8/1/2023 0:00 \n", + "16 High severity PJ 8/3/2023 0:00 \n", + "17 High severity to West, unburned to east 8/3/2023 0:00 \n", + "18 Low burn severity to south, unburned island to... 8/3/2023 0:00 \n", + "19 Low severity 8/3/2023 0:00 \n", + "20 Low to moderate severity 8/3/2023 0:00 \n", + "21 Moderate severity 8/3/2023 0:00 \n", + "22 Moderate severity 8/3/2023 0:00 \n", + "23 Moderate to high severity 8/3/2023 0:00 \n", + "24 Retardant unburned island 8/3/2023 0:00 \n", + "25 Unburned 8/3/2023 0:00 \n", + "26 Unburned island 8/3/2023 0:00 \n", + "27 Unburned island 8/3/2023 0:00 \n", + "28 Unburned with patches of light severity 8/1/2023 0:00 \n", + "\n", + " Longitude Latitude SeverityFactor geometry \\\n", + "FID \n", + "1 -115.172180 35.296247 3 POINT (-115.17218 35.29625) \n", + "2 -115.226196 35.302168 3 POINT (-115.22620 35.30217) \n", + "3 -115.257442 35.316332 3 POINT (-115.25744 35.31633) \n", + "4 -115.215690 35.253257 3 POINT (-115.21569 35.25326) \n", + "5 -115.227215 35.289627 3 POINT (-115.22722 35.28963) \n", + "6 -115.192904 35.282274 2 POINT (-115.19290 35.28227) \n", + "7 -115.094502 35.369178 2 POINT (-115.09450 35.36918) \n", + "8 -115.235698 35.271425 2 POINT (-115.23570 35.27143) \n", + "9 -115.296759 35.333723 2 POINT (-115.29676 35.33372) \n", + "10 -115.122348 35.277762 2 POINT (-115.12235 35.27776) \n", + "11 -115.129428 35.286565 0 POINT (-115.12943 35.28657) \n", + "12 -115.231058 35.267588 0 POINT (-115.23106 35.26759) \n", + "13 -115.207741 35.279457 0 POINT (-115.20774 35.27946) \n", + "14 -115.172180 35.296247 3 POINT (-115.17218 35.29625) \n", + "16 -115.316134 35.208602 3 POINT (-115.31613 35.20860) \n", + "17 -115.224903 35.156179 3 POINT (-115.22490 35.15618) \n", + "18 -115.221711 35.204250 1 POINT (-115.22171 35.20425) \n", + "19 -115.301319 35.237364 1 POINT (-115.30132 35.23736) \n", + "20 -115.233663 35.206701 1 POINT (-115.23366 35.20670) \n", + "21 -115.214888 35.204096 2 POINT (-115.21489 35.20410) \n", + "22 -115.220717 35.139797 2 POINT (-115.22072 35.13980) \n", + "23 -115.303512 35.233042 2 POINT (-115.30351 35.23304) \n", + "24 -115.225096 35.173054 0 POINT (-115.22510 35.17305) \n", + "25 -115.188494 35.149512 0 POINT (-115.18849 35.14951) \n", + "26 -115.282752 35.213657 0 POINT (-115.28275 35.21366) \n", + "27 -115.300323 35.225254 0 POINT (-115.30032 35.22525) \n", + "28 -115.105516 35.321570 0 POINT (-115.10552 35.32157) \n", + "\n", + " mean_rbr median_rbr std_rbr mean_dnbr ... std_annual \\\n", + "FID ... \n", + "1 0.024699 0.024442 0.018938 0.023293 ... 103.304161 \n", + "2 0.102397 0.106216 0.020557 0.104615 ... 112.976540 \n", + "3 0.106372 0.119165 0.042621 0.100870 ... 88.111481 \n", + "4 0.060968 0.062762 0.011493 0.060097 ... 83.382179 \n", + "5 0.111190 0.113145 0.026096 0.110387 ... 206.073257 \n", + "6 0.020500 0.017782 0.016273 0.019169 ... 39.825161 \n", + "7 0.001457 0.002989 0.013128 0.001496 ... 34.542362 \n", + "8 0.096596 0.093328 0.020483 0.098350 ... 102.576653 \n", + "9 0.042095 0.039985 0.015772 0.039242 ... 48.053261 \n", + "10 0.012562 0.011840 0.016986 0.011788 ... 108.329704 \n", + "11 -0.001654 0.003890 0.017782 -0.001566 ... 61.522537 \n", + "12 0.080986 0.081213 0.021327 0.082158 ... 131.706543 \n", + "13 -0.006817 -0.006288 0.021808 -0.006431 ... 61.256382 \n", + "14 0.024699 0.024442 0.018938 0.023293 ... 103.304161 \n", + "16 0.112572 0.101215 0.047771 0.114672 ... 179.821365 \n", + "17 0.033149 0.033944 0.018731 0.031423 ... 67.173683 \n", + "18 -0.022651 -0.021357 0.017668 -0.021052 ... 38.980240 \n", + "19 0.148797 0.141168 0.035505 0.150196 ... 166.941757 \n", + "20 0.029629 0.028415 0.010081 0.027202 ... 51.773624 \n", + "21 0.019244 0.018969 0.016806 0.017979 ... 56.552025 \n", + "22 0.016977 0.018449 0.007305 0.016302 ... 92.808319 \n", + "23 0.200694 0.179267 0.053459 0.209674 ... 352.549713 \n", + "24 -0.030324 -0.020591 0.040036 -0.028315 ... 57.007919 \n", + "25 0.002289 -0.001333 0.013747 0.002264 ... 51.054508 \n", + "26 0.071104 0.069587 0.033753 0.070116 ... 111.327255 \n", + "27 0.070385 0.056470 0.042253 0.069747 ... 322.200745 \n", + "28 -0.059228 -0.060158 0.009884 -0.054010 ... 28.099245 \n", + "\n", + " mean_perennial median_perennial std_perennial mean_shrub \\\n", + "FID \n", + "1 282.522736 257.5 139.753098 162.977280 \n", + "2 346.568176 331.5 92.655373 97.295456 \n", + "3 267.386353 255.0 77.804596 116.090912 \n", + "4 89.568184 87.0 40.422428 206.613632 \n", + "5 307.023804 299.0 128.363785 136.857147 \n", + "6 251.738098 248.0 85.621834 149.785721 \n", + "7 140.023254 154.0 47.302826 157.116272 \n", + "8 192.659088 183.0 44.351868 291.818176 \n", + "9 205.804352 200.0 36.980381 57.304348 \n", + "10 161.761902 177.0 88.403244 128.404755 \n", + "11 90.500000 78.5 49.937008 176.159088 \n", + "12 221.209305 223.0 31.389940 249.255814 \n", + "13 143.238098 148.0 37.888813 207.119049 \n", + "14 282.522736 257.5 139.753098 162.977280 \n", + "16 496.809509 426.0 225.833710 207.809525 \n", + "17 111.232559 107.0 45.175026 300.883728 \n", + "18 76.534882 69.0 22.414021 211.883728 \n", + "19 903.071411 889.5 108.627235 104.904762 \n", + "20 88.046509 72.0 38.465904 282.604645 \n", + "21 104.000000 102.0 36.576252 237.422226 \n", + "22 66.146339 67.0 26.265587 192.243896 \n", + "23 676.340881 692.0 184.750320 244.181824 \n", + "24 135.555557 131.0 42.802158 267.511108 \n", + "25 90.619049 94.0 19.827774 166.261902 \n", + "26 147.000000 140.5 39.517326 407.476196 \n", + "27 357.738098 368.5 97.129776 202.428574 \n", + "28 184.727280 184.5 46.518505 93.568184 \n", + "\n", + " median_shrub std_shrub mean_tree median_tree std_tree \n", + "FID \n", + "1 156.5 33.189190 0.000000 0.0 0.000000 \n", + "2 94.5 22.640049 0.000000 0.0 0.000000 \n", + "3 107.5 27.947855 0.409091 0.0 1.642036 \n", + "4 218.0 33.955330 0.000000 0.0 0.000000 \n", + "5 133.0 49.128872 3.238095 3.0 3.235293 \n", + "6 150.0 21.808186 0.000000 0.0 0.000000 \n", + "7 164.0 22.492592 0.000000 0.0 0.000000 \n", + "8 290.5 37.573730 0.000000 0.0 0.000000 \n", + "9 57.5 11.460461 0.000000 0.0 0.000000 \n", + "10 134.5 31.567810 0.000000 0.0 0.000000 \n", + "11 176.5 34.917400 0.000000 0.0 0.000000 \n", + "12 268.0 64.227104 0.000000 0.0 0.000000 \n", + "13 211.0 22.410883 0.000000 0.0 0.000000 \n", + "14 156.5 33.189190 0.000000 0.0 0.000000 \n", + "16 198.5 64.740227 11.357142 7.0 13.001504 \n", + "17 305.0 34.245491 0.000000 0.0 0.000000 \n", + "18 199.0 31.653067 0.000000 0.0 0.000000 \n", + "19 86.0 56.207443 239.738098 174.5 114.852303 \n", + "20 275.0 32.870529 0.000000 0.0 0.000000 \n", + "21 233.0 26.598654 0.000000 0.0 0.000000 \n", + "22 190.0 21.043255 0.000000 0.0 0.000000 \n", + "23 177.0 157.436462 548.431824 386.0 376.202209 \n", + "24 270.0 14.223021 0.000000 0.0 0.000000 \n", + "25 158.0 29.021387 0.000000 0.0 0.000000 \n", + "26 395.5 55.851521 0.000000 0.0 0.000000 \n", + "27 169.5 93.113640 21.095238 11.0 21.041693 \n", + "28 89.5 18.868443 0.000000 0.0 0.000000 \n", + "\n", + "[27 rows x 24 columns]" + ] + }, + "execution_count": 168, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "gdf_aggr_rap_metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 171, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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