From 6c8b64d5af34caf88368e5e5d31c005d565854bc Mon Sep 17 00:00:00 2001 From: h9b Date: Sat, 31 Aug 2024 18:22:11 +0200 Subject: [PATCH] add example on vandalism detection --- _toc.yml | 2 +- book/02_vandalism_detection.ipynb | 398 +++++++++++ ...ildings_currentness_DuckDB_PyIceberg.ipynb | 644 +++++++++++++++++- 3 files changed, 1019 insertions(+), 25 deletions(-) create mode 100644 book/02_vandalism_detection.ipynb diff --git a/_toc.yml b/_toc.yml index 821cc9d..955a61e 100644 --- a/_toc.yml +++ b/_toc.yml @@ -16,7 +16,7 @@ parts: - caption: Simple Data Analysis chapters: - file: book/02a_buildings_currentness_DuckDB_PyIceberg.ipynb - - file: book/02_attribute_completeness.ipynb + - file: book/02_vandalism_detection.ipynb - caption: Data Integration chapters: - file: book/03_hot_tm_project_analysis.ipynb diff --git a/book/02_vandalism_detection.ipynb b/book/02_vandalism_detection.ipynb new file mode 100644 index 0000000..011513f --- /dev/null +++ b/book/02_vandalism_detection.ipynb @@ -0,0 +1,398 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "0bdfe714-e55b-419a-b6a3-325a026bf6b1", + "metadata": {}, + "source": [ + "# Vandalism Detection for LineStrings\n", + "In this notebook we demonstrate how you detect and visualize vandalism in OSM. We are going to make use of one of the **enriched attributes** we have added to ohsome-data-insights.\n", + "\n", + "These are the steps you see further down:\n", + "\n", + "* Set the connection parameters.\n", + "* Prepare your input parameters, e.g. define area of interest and shape filters.\n", + "* **Download data** using PyIceberg and DuckDB.\n", + "* Filter and process data with DuckDB.\n", + "* Visualize the results on a map." + ] + }, + { + "cell_type": "markdown", + "id": "99ee41dd-0e24-47c3-96cf-791eb82d15a0", + "metadata": {}, + "source": [ + "## Getting started\n", + "Set connection params." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "3c9da0b3-da38-40eb-b6a1-39b09fca8851", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "\n", + "s3_user = os.environ[\"S3_ACCESS_KEY_ID\"] # add your user here\n", + "s3_password = os.environ[\"S3_SECRET_ACCESS_KEY\"] # add your password here" + ] + }, + { + "cell_type": "markdown", + "id": "8a6484a3-d34a-4010-9987-1200d6b30d54", + "metadata": {}, + "source": [ + "Configure DuckDB." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "47a69811-5dd8-4e54-9d18-1170174a3f73", + "metadata": {}, + "outputs": [], + "source": [ + "import duckdb\n", + "\n", + "con = duckdb.connect(\n", + " config={\n", + " 'threads': 8,\n", + " 'max_memory': '8GB',\n", + " }\n", + ")\n", + "con.install_extension(\"spatial\")\n", + "con.load_extension(\"spatial\")" + ] + }, + { + "cell_type": "markdown", + "id": "655c79b2-f02a-476e-a519-cf80dc2e6941", + "metadata": {}, + "source": [ + "Set the connection params to Iceberg Rest Catalog." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bebd63ea-8ae4-4935-8973-a0a6cfc0f68b", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install \"pyiceberg[s3fs,duckdb,sql-sqlite,pyarrow]\"" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "8eeb2017-f7fc-4b55-aea3-9fa483b41ea4", + "metadata": {}, + "outputs": [], + "source": [ + "from pyiceberg.catalog.rest import RestCatalog\n", + "\n", + "catalog = RestCatalog(\n", + " name=\"default\",\n", + " **{\n", + " \"uri\": \"https://sotm2024.iceberg.ohsome.org\",\n", + " \"s3.endpoint\": \"https://sotm2024.minio.heigit.org\",\n", + " \"py-io-impl\": \"pyiceberg.io.pyarrow.PyArrowFileIO\",\n", + " \"s3.access-key-id\": s3_user,\n", + " \"s3.secret-access-key\": s3_password,\n", + " \"s3.region\": \"eu-central-1\"\n", + " }\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "785a8cb7-d465-4020-9d24-45156653e00d", + "metadata": {}, + "source": [ + "## Prepare the input parameters for your analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "e8b75c69-65cd-4087-8ce5-8461e423de2e", + "metadata": {}, + "outputs": [], + "source": [ + "# Set iceberg table\n", + "namespace = 'geo_sort'\n", + "tablename = 'contributions'\n", + "icebergtable = catalog.load_table((namespace, tablename))\n", + "\n", + "# Define status filter\n", + "status = 'history'\n", + "\n", + "# Define geometry type filter\n", + "geometry_type = 'LineString'\n", + "\n", + "# Define time filter (optional)\n", + "min_timestamp = '2023-01-01T00:00:00'\n", + "\n", + "\n", + "# Define length_delta threshold in meter.\n", + "# This is a 5000 kilometers!\n", + "length_delta_threshold = 5_000_000" + ] + }, + { + "cell_type": "markdown", + "id": "eb76c76b-232d-4d15-9871-4ca0c9bac278", + "metadata": {}, + "source": [ + "## Get the Data\n", + "First, we do an iceberg table scan with a pre-filter. This is a fast way to download all potential OSM elements that are needed for our analysis.\n", + "\n", + "Here we use one of the **enriched attributes** we have calculated in advance for each OSM contribution. We use the `length_delta` attribute to inspect all the OSM elements with an unusual large change. Here we download all linestrings which changed more than 5000 kilometers in length." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "9ddaff8d-c333-4215-8bae-29db150a8c19", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "download took 10.675 sec.\n" + ] + } + ], + "source": [ + "import time\n", + "start_time = time.time()\n", + "\n", + "icebergtable.scan(\n", + " row_filter=(\n", + " f\"status = '{status}' \"\n", + " f\"and geometry_type = '{geometry_type}' \"\n", + " f\"and length_delta >= '{length_delta_threshold}' \"\n", + " ),\n", + " selected_fields=(\n", + " \"user_id\",\n", + " \"osm_id\",\n", + " \"valid_from\",\n", + " \"tags\",\n", + " \"geometry\",\n", + " )\n", + ").to_duckdb('raw_osm_data',connection=con)\n", + "\n", + "download_time = round(time.time() - start_time, 3)\n", + "print(f\"download took {download_time} sec.\")" + ] + }, + { + "cell_type": "markdown", + "id": "a1454405-16e3-44e5-b0e6-097d03607eae", + "metadata": {}, + "source": [ + "## Display OSM user activity on map\n", + "Get data from DucDKB into GeoPandas dataframe." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "55df91e5-0d67-4d7d-ac69-2522f7b5ef60", + "metadata": {}, + "outputs": [], + "source": [ + "import geopandas as gpd\n", + "\n", + "map_query = \"\"\"\n", + " SELECT\n", + " osm_id,\n", + " user_id,\n", + " valid_from::varchar as date,\n", + " epoch_ms(valid_from) as valid_from,\n", + " geometry\n", + " FROM raw_osm_data;\n", + "\"\"\"\n", + "\n", + "df = con.sql(map_query).df()\n", + "\n", + "# convert the data to geodata\n", + "gdf = gpd.GeoDataFrame(\n", + " df,\n", + " geometry=gpd.GeoSeries.from_wkt(df['geometry'])\n", + ").set_crs('epsg:4326')" + ] + }, + { + "cell_type": "markdown", + "id": "2148dba5-cc88-47c1-9d42-f844613a5b89", + "metadata": {}, + "source": [ + "Define map parameters and style." + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "ad79c9ee-cc45-43e5-bcde-49a18455e870", + "metadata": {}, + "outputs": [], + "source": [ + "import datetime\n", + "import lonboard\n", + "from palettable.matplotlib import Viridis_20\n", + "\n", + "# compute lonboard color style for contious color map\n", + "min_valid_from = datetime.datetime(2008,1,1).timestamp()\n", + "max_valid_from = datetime.datetime(2024,7,1).timestamp()\n", + "\n", + "\n", + "# the lonboard map definition\n", + "layer = lonboard.PathLayer.from_geopandas(\n", + " gdf,\n", + " extensions=[lonboard.layer_extension.DataFilterExtension(filter_size=1)],\n", + " get_filter_value=gdf[\"valid_from\"], # replace with desired column\n", + " filter_range=[min_valid_from, max_valid_from], # replace with desired filter range\n", + " get_color=[255, 0, 0, 125],\n", + " get_width=1.5,\n", + " width_units='pixels'\n", + "\n", + ")\n", + "\n", + "currentness_map = lonboard.Map(\n", + " basemap_style=lonboard.basemap.CartoBasemap.DarkMatter,\n", + " layers=[layer]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "1c64c8e9-816f-4735-b165-807d332015e9", + "metadata": {}, + "source": [ + "Define Dates Slider Selection Widget and link to map filter range." + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "id": "6d7587ad-7d28-43bc-9d4c-9fca5d7d7cdc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from datetime import date, timedelta\n", + "import ipywidgets\n", + "from traitlets import directional_link\n", + "\n", + "start = datetime.datetime(2008,1,1)\n", + "end = datetime.datetime(2024,6,1)\n", + "delta = end - start # returns timedelta\n", + "dates = [start + timedelta(days=i) for i in range(delta.days + 1)]\n", + "options = [(i.strftime('%d-%b-%Y'), 1000 * i.timestamp()) for i in dates]\n", + "\n", + "date_slider = ipywidgets.SelectionRangeSlider(\n", + " options=options,\n", + " index=(0, len(dates)-1),\n", + " description='Last Edit:',\n", + " layout=ipywidgets.Layout(width='1000px'),\n", + " disabled=False\n", + ")\n", + "\n", + "directional_link(\n", + " (date_slider, 'value'),\n", + " (layer, 'filter_range')\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "c12f0b00-75a3-44e2-addd-fdeda0de6ad7", + "metadata": {}, + "source": [ + "Display the map. 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loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + " window._bokeh_on_load = on_load\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " var skip = [];\n", + " if (window.requirejs) {\n", + " window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n", + " root._bokeh_is_loading = css_urls.length + 0;\n", + " } else {\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n", + " }\n", + "\n", + " var existing_stylesheets = []\n", + " var links = document.getElementsByTagName('link')\n", + " for (var i = 0; i < links.length; i++) {\n", + " var link = links[i]\n", + " if (link.href != null) {\n", + "\texisting_stylesheets.push(link.href)\n", + " }\n", + " }\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " if (existing_stylesheets.indexOf(url) !== -1) {\n", + "\ton_load()\n", + "\tcontinue;\n", + " 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fully initialized.\n", + " if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n", + " root._bokeh_is_initializing = false;\n", + " root._bokeh_onload_callbacks = undefined;\n", + " console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n", + " load_or_wait();\n", + " } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n", + " setTimeout(load_or_wait, 100);\n", + " } else {\n", + " root._bokeh_is_initializing = true\n", + " root._bokeh_onload_callbacks = []\n", + " var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n", + " if (!reloading && !bokeh_loaded) {\n", + "\troot.Bokeh = undefined;\n", + " }\n", + " load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n", + "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", 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handle) {\n", + " handle_clear_output(event, {cell: {output_area: handle.output_area}})\n", + " handle_add_output(event, handle)\n", + "}\n", + "\n", + "function register_renderer(events, OutputArea) {\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[0]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " events.on('output_added.OutputArea', handle_add_output);\n", + " events.on('output_updated.OutputArea', handle_update_output);\n", + " events.on('clear_output.CodeCell', handle_clear_output);\n", + " events.on('delete.Cell', handle_clear_output);\n", + " events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n", + "\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " safe: true,\n", + " index: 0\n", + " });\n", + "}\n", + "\n", + "if (window.Jupyter !== undefined) {\n", + " try {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " } catch(err) {\n", + " }\n", + "}\n" + ], + "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var 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document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n oldScript.parentNode.replaceChild(newScript, oldScript);\n });\n if (JS_MIME_TYPE in output.data) {\n toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n }\n output_area._hv_plot_id = id;\n if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 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