data/notebooks/Lab/10_Met_v0.1_results.ipynb
{
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{
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"source": [
"## 10_Met_v0.1_results\n",
"\n",
"This notebook contains the generation of the result section for the methodology developed as part of the LandGriffon platform. Link here: https://docs.google.com/document/d/1s1rINj-YVDQ36Vu-Q3T1sc55hcVLROJclaaELRF9tck/edit#\n",
"\n",
"The idea would be to compute deforestation in three different location types using satelligence data. The location types to be enalysed are:\n",
"\n",
" - Point of production (selection of a palm oill mill)\n",
" - Agrregation point (50km radius buffer arund that palm oil mill)\n",
" - Administrative area (Aceh in our case)\n",
"\n",
"NOTE: country of production cannot be performed as we are issing this coverege with Satelligence data. We can potentially cover this for a different indicator (e.g. water footprint)\n",
"\n",
" \n",
"Datasets needed:\n",
"\n",
" - palm oil mill locataions\n",
" - deforetation datasets (satelligence)\n",
" - gadm boundaries\n",
" \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "bd4e8955",
"metadata": {},
"outputs": [],
"source": [
"# import libraries\n",
"import geopandas as gpd\n",
"from rasterstats import zonal_stats\n",
"import rasterio as rio\n",
"\n",
"!pip install h3ronpy h3pandas --q\n",
"from h3ronpy import raster\n",
"import h3\n",
"import h3pandas\n",
"import pandas as pd\n",
"from shapely.geometry import Polygon\n",
"\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "50e52649",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"from PIL import Image\n",
"import scipy.ndimage\n",
"import scipy.signal\n",
"from osgeo import gdal"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "0aeee79c",
"metadata": {},
"outputs": [],
"source": [
"def buffer_stats(raster_path, vector_path, buffer=50000, stat_='sum', all_touched = True):\n",
" \"\"\"\n",
" inputs:\n",
" -------------\n",
" raster_path: raster path for retriving the statisticts in EPSG:4326\n",
" vector_path: path to point file in EPSG:4326\n",
" buffer: distance in metres for coputing the buffer\n",
" stats: stadistics to compute\n",
" \n",
" output\n",
" -------\n",
" array with statistics\"\"\"\n",
" \n",
" #open vector file\n",
" gdf = gpd.read_file(vector_path)\n",
" #check projection\n",
" #if gdf.crs != True:\n",
" # print(gdf.crs)\n",
" # #project\n",
" # print('Dataset missing projection. Please assign one!')\n",
" if gdf.crs and gdf.crs == 'EPSG:4326':\n",
" #reproject\n",
" gdf_3857 = gdf.to_crs('EPSG:3857')\n",
" ## TODO:add other validations\n",
" \n",
"\n",
" #get buffer\n",
" gdf_3857_buffer = gdf_3857.buffer(buffer)\n",
" #reproject back to epsg4326\n",
" gdf_4326_buffer = gdf_3857_buffer.to_crs('EPSG:4326')\n",
" #get statistics\n",
" vizz_stats = []\n",
" for geom in gdf_4326_buffer:\n",
" stats = zonal_stats(geom,\n",
" raster_path,\n",
" stats=stat_,\n",
" all_touched = all_touched\n",
" )\n",
" stat_sum = stats[0]['sum']\n",
" vizz_stats.append(stat_sum)\n",
" #add stats in dataframe\n",
" gdf['estimated']=vizz_stats\n",
" return gdf\n",
"\n",
"def raster_to_h3(raster_path, resolution=6, field='value', plot=False):\n",
" \"\"\"convert raster to h3 with a given h3 resolution. Returns a gdf with the h3 geometries.\"\"\"\n",
" \n",
" with rio.open(raster_path) as src:\n",
" gdf = raster.raster_to_geodataframe(src.read(1), src.transform, h3_resolution=resolution, nodata_value=src.profile['nodata'], compacted=False)\n",
"\n",
" gdf = gdf.rename(columns={'value':field})\n",
" if plot:\n",
" gdf.plot(field)\n",
" gdf['h3index'] = gdf['h3index'].apply(hex)\n",
" \n",
" return gdf\n",
" \n",
" \n",
"def focal_mean(raster_path, \n",
" kernel_path, \n",
" output_path):\n",
" #open deforestation array\n",
" ds_def = gdal.Open(raster_path)\n",
" def_array = np.array(ds_def.GetRasterBand(1).ReadAsArray())\n",
" \n",
" #open kernel path\n",
" ds_kernnel = gdal.Open(kernel_path)\n",
" kernnel_array = np.array(ds_kernnel.GetRasterBand(1).ReadAsArray())\n",
" \n",
" #perform the focal mean with convolute\n",
" result_fm = scipy.ndimage.convolve(def_array, weights=kernnel_array) / kernnel_array.size\n",
" im = Image.fromarray(result_fm)\n",
" im.save(output_path)\n",
" \n",
" "
]
},
{
"cell_type": "markdown",
"id": "73970ad5",
"metadata": {},
"source": [
"## 1. Generate h3 dataset from raster\n",
"\n",
"ingets data as density - This values would need to be multiplied by the hex area in the analysis:\n",
"\n",
"\n",
" - 1. multiplies by 1 and remove no data values.\n",
" - 2. downsample to the same resolution used for the otehr datasets ingested using the sum resampling method\n",
" - 3. divides the sum by the total sum in each pixel to get the density\n",
" - 4. Translate to h3\n",
" - 5. Get pixel area ratio\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "c65c5e89",
"metadata": {
"collapsed": true,
"jupyter": {
"outputs_hidden": true
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"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 96.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 97.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 98.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 99.. 100 - Done\n",
"Creating output file that is 40P x 48L.\n",
"Processing ../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01_mask.tif [1/1] : 0Using internal nodata values (e.g. 0) for image ../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01_mask.tif.\n",
"...10...20...30...40...50...60...70...80...90...100 - done.\n",
"0.. 100 - Done\n"
]
}
],
"source": [
"!gdal_calc.py --calc \"A*pixelarea\" --format GTiff --type Float32 --NoDataValue 0.0 -A ../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01.tif --A_band 1 --outfile ../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01_mask.tif;\n",
"!gdalwarp -s_srs EPSG:4326 -t_srs EPSG:4326 -dstnodata 0.0 -tr 0.0833333333333286 0.0833333333333286 -r sum -multi -of GTiff ../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01_mask.tif ../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01_sum.tif\n",
"!gdal_calc.py --calc \"A/1929012.345678793\" --format GTiff --type Float32 --NoDataValue 0.0 -A ../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01_sum.tif --A_band 1 --outfile ../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01_density.tif"
]
},
{
"cell_type": "markdown",
"id": "6c7b7c90",
"metadata": {},
"source": [
"### Sanity check:\n",
"\n",
"Check deforestation computed by satelligence in the different mill versus the one that we obtained using the h3 data ingestion:"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "cdb7f747",
"metadata": {},
"outputs": [],
"source": [
"# get deforestation in buffer zones\n",
"\n",
"vector_path = '../../datasets/processed/Satelligence_data/test_rasters_2/satelligence_mills_4326_50kmbuffer.shp'\n",
"resolution = 6\n",
"\n",
"gdf_vector = gpd.read_file(vector_path)\n",
"clean_gdf = gdf_vector[['gfw_fid','deforestat','geometry']]\n",
"\n",
"_sum_calculated = []\n",
"for i, row in clean_gdf.iterrows():\n",
" filtered_gdf = clean_gdf[i:i+1]\n",
" #convert to h3\n",
" h3_gdf = filtered_gdf.h3.polyfill_resample(resolution)\n",
" h3index_list = [f'0x{h3index}' for h3index in h3_gdf.index]\n",
" _sum = merge_gdf[merge_gdf['h3index'].isin(h3index_list)]['deforestation_km2'].sum()*100\n",
" _sum_calculated.append(_sum)\n",
" \n",
"#_sum_calculated"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "7da2d94d",
"metadata": {},
"outputs": [],
"source": [
"#zonal statistics raster\n",
"stats_ = buffer_stats('../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01.tif',\n",
" '../../datasets/processed/palm_oil_mills/satelligence_mills_4326_point.shp',\n",
" buffer=50000,\n",
" stat_='sum', all_touched = False)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "70054073",
"metadata": {},
"outputs": [],
"source": [
"def_raster = list(stats_['estimated']*6.69019042035408517*6.69019042035408517* 0.0001)"
]
},
{
"cell_type": "markdown",
"id": "3cd370ce",
"metadata": {},
"source": [
"## 2. Kernel landscale-level impact\n",
"\n",
"Based on the LandGriffon v0.1 methodology, for the calculation of the forest loss risk , he production map is buffered using a radius kernel prior to using ir as the weighted layer, in order to capture areas nearby to production regions. The impact factor is calculated as the production weighted average within the sourcing geometry using the buffered production map.\n",
"\n",
"This is not applied for the land impact calculation performed previously. \n",
"\n",
"The formula applied for the forest loss impact is:\n",
"\n",
"\n",
"I c,g = IFgb * I farm-land c,g / sum(Harvest area)\n",
"\n",
"\n",
"Where IFgb is the impact factor associated with the buffered sourcing geometry gb; and, is the harvested area (ha) of crop cr in the buffered sourcing location gb. \n",
"\n",
"IFgb = kernnel Deforestation layer weighted by the production layer\n",
"Harvest area of all mapspam commodities\n",
"\n",
"\n",
"IFgb = Def - pixel * Prod - pixel / sumProd Area\n",
"\n",
"\n",
"\n",
"- apply kernel to deforestation raster\n",
"- calculate deforestation file sum( def * prod) / total prod\n",
"\n",
"- def_impact * land_impact / harvest area all commodities"
]
},
{
"cell_type": "markdown",
"id": "4713dbbb",
"metadata": {},
"source": [
"### 1: Generate deforestation kernel 50km\n"
]
},
{
"cell_type": "code",
"execution_count": 77,
"id": "a258b063",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.. 100 - Done\n"
]
}
],
"source": [
"# ultiply def area in hectares\n",
"# then filter all locations where there is production\n",
"\n",
"def_density = '../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01_density.tif'\n",
"def_area_ha = '../../datasets/raw/methodology_results/update/Deforestation_IDN_2021-01-01-2022-01-01_area_ha.tif'\n",
"kernel_50km = '../../datasets/raw/methodology_results/test_location_buffer_raster.tif'\n",
"\n",
"# pixel area in hectares = 8633.766614450342 \n",
"#calculate deforestation area\n",
"!gdal_calc.py --calc \"A*8633.766614450342\" --format GTiff --type Float32 --NoDataValue 0.0 -A $def_density --A_band 1 --outfile $def_area_ha;\n",
"\n",
"\n",
"## generate kernel\n",
"focal_mean(raster_path = def_area_ha, \n",
" kernel_path = kernel_50km, \n",
" output_path = '../../datasets/raw/methodology_results/update/deforestation_50km_kernel_v2.tif')\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 78,
"id": "c0b6b761",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Driver: GTiff/GeoTIFF\n",
"Files: ../../datasets/raw/methodology_results/scenarios/kernel50_def_coco.tif\n",
"Size is 40, 48\n",
"Coordinate System is:\n",
"GEOGCRS[\"WGS 84\",\n",
" DATUM[\"World Geodetic System 1984\",\n",
" ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n",
" LENGTHUNIT[\"metre\",1]]],\n",
" PRIMEM[\"Greenwich\",0,\n",
" ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
" CS[ellipsoidal,2],\n",
" AXIS[\"geodetic latitude (Lat)\",north,\n",
" ORDER[1],\n",
" ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
" AXIS[\"geodetic longitude (Lon)\",east,\n",
" ORDER[2],\n",
" ANGLEUNIT[\"degree\",0.0174532925199433]],\n",
" ID[\"EPSG\",4326]]\n",
"Data axis to CRS axis mapping: 2,1\n",
"GeoTransform =\n",
" 94.99997999999999, 0.08333333250000016, 0\n",
" 6.100020000000001, -2.220446049250313e-17, -0.08333333333333333\n",
"Metadata:\n",
" AREA_OR_POINT=Area\n",
"Image Structure Metadata:\n",
" INTERLEAVE=BAND\n",
"Corner Coordinates:\n",
"Upper Left ( 94.9999800, 6.1000200) ( 94d59'59.93\"E, 6d 6' 0.07\"N)\n",
"Lower Left ( 94.9999800, 2.1000200) ( 94d59'59.93\"E, 2d 6' 0.07\"N)\n",
"Upper Right ( 98.3333133, 6.1000200) ( 98d19'59.93\"E, 6d 6' 0.07\"N)\n",
"Lower Right ( 98.3333133, 2.1000200) ( 98d19'59.93\"E, 2d 6' 0.07\"N)\n",
"Center ( 96.6666466, 4.1000200) ( 96d39'59.93\"E, 4d 6' 0.07\"N)\n",
"Band 1 Block=40x48 Type=Float32, ColorInterp=Gray\n"
]
}
],
"source": [
"!gdalinfo $output_path"
]
},
{
"cell_type": "code",
"execution_count": 80,
"id": "ee1b9612",
"metadata": {},
"outputs": [],
"source": [
"#set projection\n",
"\n",
"## change extent and set projection\n",
"\n",
"!gdal_edit.py -a_srs EPSG:4326 -a_ulurll 94.9999800 6.1000200 98.3333133 6.1000200 94.9999800 2.1000200 ../../datasets/raw/methodology_results/update/deforestation_50km_kernel_v2.tif"
]
},
{
"cell_type": "markdown",
"id": "10c8487d",
"metadata": {},
"source": [
"## 3. Calculate harvest area for all mapspam crops"
]
},
{
"cell_type": "code",
"execution_count": 152,
"id": "e4bd0b9e",
"metadata": {},
"outputs": [],
"source": [
"empty_array = np.zeros((2160, 4320))\n",
"im = Image.fromarray(empty_array)\n",
"im.save('../../datasets/raw/methodology_results/harvest_area_mapspam/spam2010v2r0_global_harv_area.geotiff/empty.tif')\n",
"# geolocate with new extent\n",
"!gdal_edit.py -a_srs EPSG:4326 -a_ulurll -180.0000000 90.0000000 179.9985600 90.0000000 -180.0000000 -89.9992800 -a_nodata -1 '../../datasets/raw/methodology_results/harvest_area_mapspam/spam2010v2r0_global_harv_area.geotiff/empty.tif'\n"
]
},
{
"cell_type": "code",
"execution_count": 154,
"id": "282126ca",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Done!\n"
]
}
],
"source": [
"all_ha_commodities = [file for file in os.listdir('../../datasets/raw/methodology_results/harvest_area_mapspam/spam2010v2r0_global_harv_area.geotiff') if file.endswith('_A.tif')]\n",
"\n",
"for i in range(0,len(all_ha_commodities)):\n",
" file = '../../datasets/raw/methodology_results/harvest_area_mapspam/spam2010v2r0_global_harv_area.geotiff/'+ all_ha_commodities[i]\n",
" #print(f'Summing {all_ha_commodities[i]}...')\n",
" !gdal_calc.py --calc \"A+B\" --NoDataValue -1 --format GTiff --type Float32 --NoDataValue -1 -A ../../datasets/raw/methodology_results/harvest_area_mapspam/spam2010v2r0_global_harv_area.geotiff/empty.tif --A_band 1 -B $file --outfile ../../datasets/raw/methodology_results/harvest_area_mapspam/spam2010v2r0_global_harv_area.geotiff/empty.tif --q;\n",
"print('Done!')"
]
},
{
"cell_type": "code",
"execution_count": 155,
"id": "244c132b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Input file size is 4320, 2160\n",
"0...10...20...30...40...50...60...70...80...90...100 - done.\n"
]
}
],
"source": [
"#clip data to area of interest\n",
"!gdal_translate -projwin 94.99998 6.10002 98.333313333 2.10002 -of GTiff ../../datasets/raw/methodology_results/harvest_area_mapspam/spam2010v2r0_global_harv_area.geotiff/empty.tif ../../datasets/raw/methodology_results/harvest_area_mapspam/harvest_area_sum_ha_clip.tif;"
]
},
{
"cell_type": "markdown",
"id": "c720fbc9",
"metadata": {},
"source": [
"## H3 Calculations:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "db5a4ed7",
"metadata": {},
"outputs": [
{
"data": {
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>h3index</th>\n",
" <th>def_density</th>\n",
" <th>pixel_area_km2</th>\n",
" <th>prod_t</th>\n",
" <th>harvst_ha</th>\n",
" <th>harvst_all_ha</th>\n",
" <th>kernel_def_ha</th>\n",
" <th>geometry</th>\n",
" <th>def_area_ha</th>\n",
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" <td>98.199997</td>\n",
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],
"text/plain": [
" h3index def_density pixel_area_km2 prod_t harvst_ha \\\n",
"0 866552b07ffffff 0.000063 85.707100 59.200001 53.5 \n",
"1 866552b27ffffff 0.000063 85.707100 59.200001 53.5 \n",
"2 866552b37ffffff 0.000063 85.707100 59.200001 53.5 \n",
"3 866552347ffffff 0.000055 85.648102 98.199997 56.5 \n",
"4 86655234fffffff 0.000055 85.648102 98.199997 56.5 \n",
"\n",
" harvst_all_ha kernel_def_ha \\\n",
"0 1077.400024 2.405604 \n",
"1 1077.400024 2.405604 \n",
"2 1077.400024 2.405604 \n",
"3 2728.700195 1.315351 \n",
"4 2728.700195 1.315351 \n",
"\n",
" geometry def_area_ha h3Area_km2 \\\n",
"0 POLYGON ((95.95279 5.13947, 95.95552 5.17595, ... 0.542053 43.145831 \n",
"1 POLYGON ((95.98051 5.08239, 95.98325 5.11887, ... 0.542053 43.135311 \n",
"2 POLYGON ((96.01645 5.13474, 96.01919 5.17123, ... 0.542053 43.145432 \n",
"3 POLYGON ((95.59505 5.49620, 95.59775 5.53272, ... 0.475080 43.204484 \n",
"4 POLYGON ((95.53131 5.50088, 95.53401 5.53741, ... 0.475080 43.203765 \n",
"\n",
" area_ratio \n",
"0 0.503410 \n",
"1 0.503287 \n",
"2 0.503406 \n",
"3 0.504442 \n",
"4 0.504433 "
]
},
"execution_count": 7,
"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"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"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": [
"#translate density raster to h3\n",
"rp_density = '../../datasets/raw/methodology_results/Deforestation_IDN_2021-01-01-2022-01-01_density.tif'\n",
"rp_area = '../../datasets/processed/Satelligence_data/area_ratio/8_Areakm_clip_ind.tif'\n",
"rp_oil_prod_t = '../../datasets/raw/methodology_results/spam_palm_oil_prod_clip.tif'\n",
"rp_oil_ha = '../../datasets/raw/methodology_results/spam_palm_oil_ha_clip.tif'\n",
"rp_all_comm_ha = '../../datasets/raw/methodology_results/harvest_area_mapspam/harvest_area_sum_ha_clip.tif'\n",
"kernel_Def = '../../datasets/raw/methodology_results/update/deforestation_50km_kernel_v2.tif'\n",
"\n",
"\n",
"resolution = 6\n",
"\n",
"\n",
"\n",
"\n",
"gdf_def_density = raster_to_h3(rp_density, resolution=resolution, field ='def_density', plot=True)\n",
"\n",
"# translate pixel area to h3 to compute pixel area/h3 area ratio\n",
"#translate density raster to h3\n",
"gdf_def_area = raster_to_h3(rp_area, resolution=resolution, field='pixel_area_km2')\n",
"gdf_po_prod = raster_to_h3(rp_oil_prod_t, resolution=resolution, field='prod_t', plot=True)\n",
"gdf_po_ha = raster_to_h3(rp_oil_ha, resolution=resolution, field='harvst_ha', plot=True)\n",
"gdf_allcommodities_ha = raster_to_h3(rp_all_comm_ha, resolution=resolution, field='harvst_all_ha', plot=True)\n",
"gdf_kernel_Def = raster_to_h3(kernel_Def, resolution=resolution, field='kernel_def_ha', plot=True)\n",
"\n",
"\n",
"## merge datasets\n",
"\n",
"gdf_merge = gdf_po_prod.merge(gdf_po_ha, on='h3index', how='outer').merge(gdf_def_area, on='h3index', how='outer')[['h3index', 'pixel_area_km2', 'prod_t', 'harvst_ha', 'geometry']].merge(gdf_def_density, on='h3index', how='outer').merge(gdf_allcommodities_ha, on='h3index', how='outer')\n",
"\n",
"\n",
"#clean merged dataset - get just one geometry\n",
"\n",
"gdf_merge = gdf_merge[['h3index','def_density', 'pixel_area_km2', 'prod_t', 'harvst_ha','harvst_all_ha','geometry_x']].rename(columns={'geometry_x':'geometry'})\n",
"gdf_merge = gdf_merge.merge(gdf_kernel_Def, on='h3index', how='outer')[['h3index','def_density', 'pixel_area_km2', 'prod_t', 'harvst_ha','harvst_all_ha','kernel_def_ha','geometry_x']].rename(columns={'geometry_x':'geometry'})\n",
"\n",
"#calculate deforestation area \n",
"gdf_merge['def_area_ha'] = gdf_merge['pixel_area_km2']*100*gdf_merge['def_density']\n",
"gdf_merge['h3index'] = [h3index.split('x')[1] for h3index in gdf_merge['h3index']]\n",
"gdf_merge['h3Area_km2'] = [h3.cell_area(h3index) for h3index in list(gdf_merge['h3index'])]\n",
"gdf_merge['area_ratio'] = gdf_merge['h3Area_km2']/gdf_merge['pixel_area_km2']\n",
"\n",
"gdf_merge.head()"
]
},
{
"cell_type": "code",
"execution_count": 83,
"id": "fe0b198a",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-83-afa81b12b667>:2: UserWarning: Column names longer than 10 characters will be truncated when saved to ESRI Shapefile.\n",
" gdf_merge.to_file('../../datasets/raw/methodology_results/update/gdf_kernel_Deforestation_v2.shp')\n"
]
}
],
"source": [
"gdf_merge = gdf_merge.set_geometry('geometry')\n",
"gdf_merge.to_file('../../datasets/raw/methodology_results/update/gdf_kernel_Deforestation_v2.shp')"
]
},
{
"cell_type": "markdown",
"id": "cdd26667",
"metadata": {},
"source": [
"### 1. Point of production:\n",
"\n",
" -Example mill name: AGRA BUMI NIAGA\n",
" -Gfw_id = 1873\n",
" -Uml_id = PO1000010250\n",
" -Lat, lon = 4.575718, 97.6190685\n",
" -Country = Indonesia\n",
"\n",
"#### Land impact:\n",
"\n",
"land impact(ha) = volume(T) * sum(Harvest area (ha)) /sum( production (T))\n",
"\n",
"\n",
"forest loss (ha) = deforestation (ha/yr) * land impact (ha) /sum(harvest area) (ha)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "bc032199",
"metadata": {},
"outputs": [
{
"data": {
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"</style>\n",
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" <th>geometry</th>\n",
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" <tr>\n",
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]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"point_location = gpd.read_file('../../datasets/raw/methodology_results/test_location_point.geojson')\n",
"point_location = point_location.h3.geo_to_h3(6).reset_index(drop=False)\n",
"\n",
"point_location = point_location[['h3_06']]\n",
"\n",
"point_location['geometry'] = Polygon(h3.h3_to_geo_boundary(point_location['h3_06'][0], geo_json=True))\n",
"point_location = point_location.set_geometry('geometry')\n",
"#point_location.to_file('../../datasets/raw/methodology_results/test_location_point_h3_res6_v3.shp')\n",
"\n",
"point_location\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "65d6e40d",
"metadata": {},
"outputs": [
{
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>h3index</th>\n",
" <th>def_density</th>\n",
" <th>pixel_area_km2</th>\n",
" <th>prod_t</th>\n",
" <th>harvst_ha</th>\n",
" <th>harvst_all_ha</th>\n",
" <th>kernel_def_ha</th>\n",
" <th>geometry</th>\n",
" <th>def_area_ha</th>\n",
" <th>h3Area_km2</th>\n",
" <th>area_ratio</th>\n",
" </tr>\n",
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" <tr>\n",
" <th>121</th>\n",
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" </tr>\n",
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"text/plain": [
" h3index def_density pixel_area_km2 prod_t harvst_ha \\\n",
"121 866509697ffffff 0.006317 85.771797 14998.599609 947.200012 \n",
"\n",
" harvst_all_ha kernel_def_ha \\\n",
"121 3014.800293 3.945905 \n",
"\n",
" geometry def_area_ha \\\n",
"121 POLYGON ((97.63571 4.57267, 97.63863 4.60908, ... 54.183953 \n",
"\n",
" h3Area_km2 area_ratio \n",
"121 42.993477 0.501254 "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#obtain deforestation that takes places in that hexagon\n",
"\n",
"h3index_list = list(point_location['h3_06'])\n",
"\n",
"def_point_loc = gdf_merge[gdf_merge['h3index'].isin(h3index_list)]\n",
"def_point_loc\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "f6d4be3a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"land impact: 63.15256336431409 ha\n",
"Dif: 3.945905105984504\n",
"Mean cropland area: 3014.80029296875\n",
"Revised forest loss risk:0.08265689200589445 ha\n"
]
}
],
"source": [
"#asumming volume equal to 1T\n",
"land_impact_point = 1000*def_point_loc['harvst_ha'].sum()/def_point_loc['prod_t'].sum()\n",
"print(f'land impact: {land_impact_point} ha')\n",
"\n",
"def_if = sum(def_point_loc['kernel_def_ha'] * def_point_loc['prod_t'])/ def_point_loc['prod_t'].sum()\n",
"print(f'Dif: {def_if}')\n",
"\n",
"#Weighted mean total cropland area per pixel\n",
"def_total_cropland_area_per_pixel = (def_point_loc['harvst_all_ha'] * def_point_loc['prod_t']).dropna().sum() /def_point_loc['prod_t'].sum()\n",
"print(f'Mean cropland area: {def_total_cropland_area_per_pixel}')\n",
"\n",
"def_impact_2 = (def_if * land_impact_point) / def_total_cropland_area_per_pixel\n",
"print(f'Revised forest loss risk:{def_impact_2} ha')"
]
},
{
"cell_type": "markdown",
"id": "70faa933",
"metadata": {},
"source": [
"### 2. Aggergation point - 50km buffer:\n",
"\n",
" -Example mill name: AGRA BUMI NIAGA\n",
" -Gfw_id = 1873\n",
" -Uml_id = PO1000010250\n",
" -Lat, lon = 4.575718, 97.6190685\n",
" -Country = Indonesia\n",
"\n",
"land impact(ha) = volume(T) * sum(Harvest area (ha)) /sum( production (T))\n",
"\n",
"forest loss (ha) = deforestation (ha/yr) * land impact (ha) /sum(harvest area) (ha)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "c21b2b9e",
"metadata": {},
"outputs": [
{
"data": {
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" <th>3</th>\n",
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"</table>\n",
"</div>"
],
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" h3index geometry\n",
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]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"agg_point = gpd.read_file('../../datasets/raw/methodology_results/test_location_point.geojson')\n",
"agg_point = agg_point.to_crs('EPSG:3857')\n",
"agg_point = agg_point.buffer(50000)\n",
"agg_point = agg_point.to_crs('EPSG:4326')\n",
"\n",
"h3_agg_point = h3.polyfill(agg_point.geometry[0].__geo_interface__, 6, geo_json_conformant = True)\n",
"\n",
"agg_point_gdf = gpd.GeoDataFrame(h3_agg_point)\n",
"agg_point_gdf = agg_point_gdf.rename(columns={0:'h3index'})\n",
"agg_point_gdf['geometry'] = [Polygon(h3.h3_to_geo_boundary(h3index, geo_json=True)) for h3index in list(agg_point_gdf['h3index'])]\n",
"#agg_point_gdf.to_file('../../datasets/raw/methodology_results/test_agg_point_h3_res6_v2.shp')\n",
"agg_point_gdf.head()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "69e06b1c",
"metadata": {},
"outputs": [
{
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" <td>NaN</td>\n",
" <td>42.931822</td>\n",
" <td>0.500362</td>\n",
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" <tr>\n",
" <th>53</th>\n",
" <td>86650969fffffff</td>\n",
" <td>0.001056</td>\n",
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" <td>795.5</td>\n",
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" <td>4.196029</td>\n",
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" <td>9.057337</td>\n",
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" <td>85.771797</td>\n",
" <td>795.5</td>\n",
" <td>90.5</td>\n",
" <td>344.300018</td>\n",
" <td>4.402756</td>\n",
" <td>POLYGON ((97.60834 4.62971, 97.61125 4.66612, ...</td>\n",
" <td>6.389491</td>\n",
" <td>43.006872</td>\n",
" <td>0.501410</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55</th>\n",
" <td>866556d37ffffff</td>\n",
" <td>0.000745</td>\n",
" <td>85.771797</td>\n",
" <td>795.5</td>\n",
" <td>90.5</td>\n",
" <td>344.300018</td>\n",
" <td>4.402756</td>\n",
" <td>POLYGON ((97.54483 4.63457, 97.54774 4.67098, ...</td>\n",
" <td>6.389491</td>\n",
" <td>43.011312</td>\n",
" <td>0.501462</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" h3index def_density pixel_area_km2 prod_t harvst_ha \\\n",
"30 866509407ffffff NaN 85.801598 23407.0 1525.0 \n",
"31 86650941fffffff NaN 85.801598 23407.0 1525.0 \n",
"53 86650969fffffff 0.001056 85.771797 795.5 90.5 \n",
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"55 866556d37ffffff 0.000745 85.771797 795.5 90.5 \n",
"\n",
" harvst_all_ha kernel_def_ha \\\n",
"30 5400.299805 2.709576 \n",
"31 5400.299805 2.674173 \n",
"53 344.300018 4.196029 \n",
"54 344.300018 4.402756 \n",
"55 344.300018 4.402756 \n",
"\n",
" geometry def_area_ha \\\n",
"30 POLYGON ((97.99883 4.32516, 98.00178 4.36152, ... NaN \n",
"31 POLYGON ((97.97155 4.38215, 97.97450 4.41852, ... NaN \n",
"53 POLYGON ((97.57222 4.57753, 97.57513 4.61394, ... 9.057337 \n",
"54 POLYGON ((97.60834 4.62971, 97.61125 4.66612, ... 6.389491 \n",
"55 POLYGON ((97.54483 4.63457, 97.54774 4.67098, ... 6.389491 \n",
"\n",
" h3Area_km2 area_ratio \n",
"30 42.917517 0.500195 \n",
"31 42.931822 0.500362 \n",
"53 42.997994 0.501307 \n",
"54 43.006872 0.501410 \n",
"55 43.011312 0.501462 "
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#obtain deforestation that takes places in that hexagon\n",
"h3index_list = list(agg_point_gdf['h3index'])\n",
"\n",
"def_agg_loc = gdf_merge[gdf_merge['h3index'].isin(h3index_list)]\n",
"def_agg_loc.head()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "badd0b0a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"land impact: 71.72121424962671 ha\n",
"Dif: 3.1426641535365127\n",
"Mean cropland area: 3551.81494140625\n",
"Revised forest loss risk:0.06345929976328507 ha\n"
]
}
],
"source": [
"#asumming volume equal to 1T\n",
"land_impact_agg_point = 1000*def_agg_loc['harvst_ha'].sum()/def_agg_loc['prod_t'].sum()\n",
"print(f'land impact: {land_impact_agg_point} ha')\n",
"\n",
"def_if = sum((def_agg_loc['kernel_def_ha'] * def_agg_loc['prod_t']).dropna()) / def_agg_loc['prod_t'].sum()\n",
"print(f'Dif: {def_if}')\n",
"\n",
"#Weighted mean total cropland area per pixel\n",
"def_total_cropland_area_per_pixel = (def_agg_loc['harvst_all_ha'] * def_agg_loc['prod_t']).dropna().sum() /def_agg_loc['prod_t'].sum()\n",
"print(f'Mean cropland area: {def_total_cropland_area_per_pixel}')\n",
"\n",
"def_impact_agg_2 = (def_if * land_impact_agg_point) / def_total_cropland_area_per_pixel\n",
"print(f'Revised forest loss risk:{def_impact_agg_2} ha')\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "59397c1b",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-15-56cda87b5618>:2: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" def_agg_loc['land_impact_ha'] = (def_agg_loc['prod_t']*land_impact_agg_point) / def_agg_loc['prod_t'].sum()\n"
]
},
{
"ename": "NameError",
"evalue": "name 'def_impact_agg' is not defined",
"output_type": "error",
"traceback": [
"\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
"\u001B[0;31mNameError\u001B[0m Traceback (most recent call last)",
"\u001B[0;32m<ipython-input-15-56cda87b5618>\u001B[0m in \u001B[0;36m<module>\u001B[0;34m\u001B[0m\n\u001B[1;32m 1\u001B[0m \u001B[0;31m## map - land impact aggregation point:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 2\u001B[0m \u001B[0mdef_agg_loc\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;34m'land_impact_ha'\u001B[0m\u001B[0;34m]\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0;34m(\u001B[0m\u001B[0mdef_agg_loc\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;34m'prod_t'\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m*\u001B[0m\u001B[0mland_impact_agg_point\u001B[0m\u001B[0;34m)\u001B[0m \u001B[0;34m/\u001B[0m \u001B[0mdef_agg_loc\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;34m'prod_t'\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0msum\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m----> 3\u001B[0;31m \u001B[0mdef_agg_loc\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;34m'def_impact_ha'\u001B[0m\u001B[0;34m]\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0;34m(\u001B[0m\u001B[0mdef_agg_loc\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;34m'prod_t'\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m*\u001B[0m\u001B[0mdef_impact_agg\u001B[0m\u001B[0;34m)\u001B[0m \u001B[0;34m/\u001B[0m \u001B[0mdef_agg_loc\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;34m'prod_t'\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0msum\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m 4\u001B[0m \u001B[0mdef_agg_loc\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mdef_agg_loc\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mset_geometry\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m'geometry'\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 5\u001B[0m \u001B[0;31m#def_agg_loc.to_file('../../datasets/raw/methodology_results/update/agg_point_h3_res6_impact_v1_kernel.shp')\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n",
"\u001B[0;31mNameError\u001B[0m: name 'def_impact_agg' is not defined"
]
}
],
"source": [
"## map - land impact aggregation point:\n",
"def_agg_loc['land_impact_ha'] = (def_agg_loc['prod_t']*land_impact_agg_point) / def_agg_loc['prod_t'].sum()\n",
"def_agg_loc['def_impact_ha'] = (def_agg_loc['prod_t']*def_impact_agg) / def_agg_loc['prod_t'].sum()\n",
"def_agg_loc = def_agg_loc.set_geometry('geometry')\n",
"#def_agg_loc.to_file('../../datasets/raw/methodology_results/update/agg_point_h3_res6_impact_v1_kernel.shp')\n",
"\n",
"def_agg_loc.head()"
]
},
{
"cell_type": "markdown",
"id": "5b1c9850",
"metadata": {},
"source": [
"### 3. Admin area - Aceh:\n",
"\n",
"land impact (ha) = volume(T) * sum(Harvest area (ha)) /sum( production (T))\n",
"\n",
"forest loss (ha) = deforestation (ha/yr) * land impact (ha) /sum(harvest area) (ha)"
]
},
{
"cell_type": "code",
"execution_count": 102,
"id": "89ab218c",
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
" h3index geometry\n",
"0 866573917ffffff POLYGON ((96.64380 2.07756, 96.64658 2.11362, ...\n",
"1 86657064fffffff POLYGON ((96.70686 2.07286, 96.70965 2.10891, ...\n",
"0 86657044fffffff POLYGON ((97.14820 2.03986, 97.15104 2.07590, ...\n",
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]
},
"execution_count": 102,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"adm_loc = gpd.read_file('../../datasets/raw/methodology_results/aceh_loc.geojson')\n",
"adm_loc = adm_loc.explode(index_parts=True)\n",
"h3_multipol = [h3.polyfill(geom.__geo_interface__, 6, geo_json_conformant = True) for geom in list(adm_loc['geometry'])]\n",
"\n",
"for i in range(0,len(h3_multipol)):\n",
" if i == 0:\n",
" df_mult = pd.DataFrame(h3_multipol[i])\n",
" else:\n",
" \n",
" df_ = pd.DataFrame(h3_multipol[i])\n",
" df_mult = pd.concat([df_mult, df_])\n",
"df_mult = df_mult.rename(columns={0:'h3index'})\n",
"df_mult['geometry'] = [Polygon(h3.h3_to_geo_boundary(h3index, geo_json=True)) for h3index in list(df_mult['h3index'])]\n",
"df_mult = df_mult.set_geometry('geometry')\n",
"#df_mult.to_file('../../datasets/raw/methodology_results/test_aceh_h3_res6.shp')\n",
"df_mult.head()"
]
},
{
"cell_type": "code",
"execution_count": 103,
"id": "9e0e56f0",
"metadata": {},
"outputs": [
{
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" <th></th>\n",
" <th>h3index</th>\n",
" <th>def_density</th>\n",
" <th>pixel_area_km2</th>\n",
" <th>prod_t</th>\n",
" <th>harvst_ha</th>\n",
" <th>harvst_all_ha</th>\n",
" <th>kernel_def_ha</th>\n",
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" <td>85.718300</td>\n",
" <td>2457.500000</td>\n",
" <td>404.200012</td>\n",
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" <td>3.479367</td>\n",
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"</table>\n",
"</div>"
],
"text/plain": [
" h3index def_density pixel_area_km2 prod_t harvst_ha \\\n",
"0 866550017ffffff 0.007334 85.781898 1963.099976 378.700012 \n",
"1 866550037ffffff 0.000570 85.781898 1963.099976 378.700012 \n",
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"3 866550d57ffffff 0.000126 85.801598 8304.400391 336.299988 \n",
"4 86655609fffffff 0.000406 85.718300 2457.500000 404.200012 \n",
"\n",
" harvst_all_ha kernel_def_ha \\\n",
"0 1524.099854 2.878644 \n",
"1 1524.099854 2.631647 \n",
"2 1782.599976 4.385420 \n",
"3 1782.599976 4.385420 \n",
"4 1979.599854 6.147684 \n",
"\n",
" geometry def_area_ha h3Area_km2 \\\n",
"0 POLYGON ((95.81241 4.54512, 95.81512 4.58153, ... 62.915216 43.026066 \n",
"1 POLYGON ((95.84010 4.48815, 95.84282 4.52456, ... 4.886686 43.014405 \n",
"2 POLYGON ((96.27655 4.34589, 96.27932 4.38229, ... 1.080853 42.985871 \n",
"3 POLYGON ((96.21304 4.35063, 96.21580 4.38702, ... 1.080853 42.987059 \n",
"4 POLYGON ((96.93507 5.01085, 96.93791 5.04732, ... 3.479367 43.111419 \n",
"\n",
" area_ratio \n",
"0 0.501575 \n",
"1 0.501439 \n",
"2 0.500991 \n",
"3 0.501005 \n",
"4 0.502943 "
]
},
"execution_count": 103,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#obtain deforestation that takes places in that hexagon\n",
"h3index_list = list(df_mult['h3index'])\n",
"\n",
"def_aceh = gdf_merge[gdf_merge['h3index'].isin(h3index_list)]\n",
"def_aceh.head()"
]
},
{
"cell_type": "code",
"execution_count": 110,
"id": "994db305",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"land impact: 87.19526554714088 ha\n",
"Dif: 3.761295795440674\n",
"Forest loss risk:0.00013937714945840143 ha\n"
]
}
],
"source": [
"#asumming volume equal to 1T\n",
"land_impact_aceh = 1000*def_aceh['harvst_ha'].sum()/def_aceh['prod_t'].sum()\n",
"print(f'land impact: {land_impact_aceh} ha')\n",
"\n",
"def_if = (def_aceh['kernel_def_ha'] * def_aceh['prod_t']).dropna().sum() /def_aceh['prod_t'].sum()\n",
"print(f'Dif: {def_if}')\n",
"\n",
"#Weighted mean total cropland area per pixel\n",
"def_total_cropland_area_per_pixel = (def_aceh['harvst_all_ha'] * def_aceh['prod_t']).dropna().sum() /def_aceh['prod_t'].sum()\n",
"print(f'Mean cropland area: {def_total_cropland_area_per_pixel}')\n",
"\n",
"def_impact_aceh_2 = (def_if * land_impact_aceh) / def_total_cropland_area_per_pixel\n",
"print(f'Revised forest loss risk:{def_impact_aceh_2} ha')\n"
]
},
{
"cell_type": "code",
"execution_count": 111,
"id": "8cb1be5a",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.8/site-packages/geopandas/geodataframe.py:1351: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" super().__setitem__(key, value)\n",
"<ipython-input-111-31b9ad4911aa>:4: UserWarning: Column names longer than 10 characters will be truncated when saved to ESRI Shapefile.\n",
" def_aceh.to_file('../../datasets/raw/methodology_results/update/Aceh_h3_res6_impact_v1_kernel.shp')\n"
]
},
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" <td>1.080853</td>\n",
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" <td>0.000406</td>\n",
" <td>85.718300</td>\n",
" <td>2457.500000</td>\n",
" <td>404.200012</td>\n",
" <td>1979.599854</td>\n",
" <td>6.147684</td>\n",
" <td>POLYGON ((96.93507 5.01085, 96.93791 5.04732, ...</td>\n",
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],
"text/plain": [
" h3index def_density pixel_area_km2 prod_t harvst_ha \\\n",
"0 866550017ffffff 0.007334 85.781898 1963.099976 378.700012 \n",
"1 866550037ffffff 0.000570 85.781898 1963.099976 378.700012 \n",
"2 866550d0fffffff 0.000126 85.801598 8304.400391 336.299988 \n",
"3 866550d57ffffff 0.000126 85.801598 8304.400391 336.299988 \n",
"4 86655609fffffff 0.000406 85.718300 2457.500000 404.200012 \n",
"\n",
" harvst_all_ha kernel_def_ha \\\n",
"0 1524.099854 2.878644 \n",
"1 1524.099854 2.631647 \n",
"2 1782.599976 4.385420 \n",
"3 1782.599976 4.385420 \n",
"4 1979.599854 6.147684 \n",
"\n",
" geometry def_area_ha h3Area_km2 \\\n",
"0 POLYGON ((95.81241 4.54512, 95.81512 4.58153, ... 62.915216 43.026066 \n",
"1 POLYGON ((95.84010 4.48815, 95.84282 4.52456, ... 4.886686 43.014405 \n",
"2 POLYGON ((96.27655 4.34589, 96.27932 4.38229, ... 1.080853 42.985871 \n",
"3 POLYGON ((96.21304 4.35063, 96.21580 4.38702, ... 1.080853 42.987059 \n",
"4 POLYGON ((96.93507 5.01085, 96.93791 5.04732, ... 3.479367 43.111419 \n",
"\n",
" area_ratio land_impact_ha def_impact_ha \n",
"0 0.501575 0.033599 5.370679e-08 \n",
"1 0.501439 0.033599 5.370679e-08 \n",
"2 0.500991 0.142133 2.271931e-07 \n",
"3 0.501005 0.142133 2.271931e-07 \n",
"4 0.502943 0.042061 6.723266e-08 "
]
},
"execution_count": 111,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def_aceh['land_impact_ha'] = (def_aceh['prod_t']*land_impact_aceh) / def_aceh['prod_t'].sum()\n",
"def_aceh['def_impact_ha'] = (def_aceh['prod_t']*def_impact_aceh) / def_aceh['prod_t'].sum()\n",
"def_aceh = def_aceh.set_geometry('geometry')\n",
"def_aceh.to_file('../../datasets/raw/methodology_results/update/Aceh_h3_res6_impact_v1_kernel.shp')\n",
"\n",
"def_aceh.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3773eab5",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
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