{ "cells": [ { "cell_type": "markdown", "id": "aff4ae6e", "metadata": { "papermill": { "duration": 0.013153, "end_time": "2024-07-01T13:29:53.832143", "exception": false, "start_time": "2024-07-01T13:29:53.818990", "status": "completed" }, "tags": [] }, "source": [ "# Metadata table" ] }, { "cell_type": "code", "execution_count": 1, "id": "d86129d3", "metadata": { "execution": { "iopub.execute_input": "2024-07-01T13:29:53.845695Z", "iopub.status.busy": "2024-07-01T13:29:53.844725Z", "iopub.status.idle": "2024-07-01T13:29:53.863201Z", "shell.execute_reply": "2024-07-01T13:29:53.861960Z" }, "papermill": { "duration": 0.029031, "end_time": "2024-07-01T13:29:53.866325", "exception": false, "start_time": "2024-07-01T13:29:53.837294", "status": "completed" }, "tags": [ "remove-input" ] }, "outputs": [], "source": [ "# NO CODE\n", "from json2html import json2html\n", "import json, re\n", "from IPython.display import HTML" ] }, { "cell_type": "code", "execution_count": 2, "id": "8a6c6dff", "metadata": { "execution": { "iopub.execute_input": "2024-07-01T13:29:53.883422Z", "iopub.status.busy": "2024-07-01T13:29:53.882832Z", "iopub.status.idle": "2024-07-01T13:29:53.890856Z", "shell.execute_reply": "2024-07-01T13:29:53.889782Z" }, "papermill": { "duration": 0.01944, "end_time": "2024-07-01T13:29:53.894275", "exception": false, "start_time": "2024-07-01T13:29:53.874835", "status": "completed" }, "tags": [ "parameters", "remove-input" ] }, "outputs": [], "source": [ "# NO CODE\n", "# PARAMETERS\n", "path = './meta/environment/meteocat_xema'" ] }, { "cell_type": "code", "execution_count": 3, "id": "23b28792", "metadata": { "execution": { "iopub.execute_input": "2024-07-01T13:29:53.909677Z", "iopub.status.busy": "2024-07-01T13:29:53.909239Z", "iopub.status.idle": "2024-07-01T13:29:53.915115Z", "shell.execute_reply": "2024-07-01T13:29:53.914142Z" }, "papermill": { "duration": 0.015006, "end_time": "2024-07-01T13:29:53.917109", "exception": false, "start_time": "2024-07-01T13:29:53.902103", "status": "completed" }, "tags": [ "injected-parameters" ] }, "outputs": [], "source": [ "# Parameters\n", "path = \"./meta/environment/human_presence\"\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "991c4405", "metadata": { "execution": { "iopub.execute_input": "2024-07-01T13:29:53.933231Z", "iopub.status.busy": "2024-07-01T13:29:53.932549Z", "iopub.status.idle": "2024-07-01T13:29:53.954695Z", "shell.execute_reply": "2024-07-01T13:29:53.953412Z" }, "papermill": { "duration": 0.032795, "end_time": "2024-07-01T13:29:53.957224", "exception": false, "start_time": "2024-07-01T13:29:53.924429", "status": "completed" }, "tags": [ "remove-input", "full-width" ] }, "outputs": [ { "data": { "text/html": [ "
$schema../schema.json
@context
@vocabhttps://schema.org/
qudthttp://qudt.org/schema/qudt/
xsdhttp://www.w3.org/2001/XMLSchema#
@typeDataset
namehuman_presence
conditionsOfAccessPublic
descriptionMulti-band raster with resolution 0.025 degree and worldwide coverage of Köppen-Geiger climatic regions, estimated population density for 2030, Global Administrative Areas (GADM) and terrestrial ecoregions of the world.
licenseFree of charge, worldwide, non-exclusive, royalty free and perpetual.
citation
  • Beck, Hylke E.; E. Zimmermann, Niklaus; McVicar, Tim R.; Vergopolan, Noemi; Berg, Alexis; Wood, Eric F. (2018). Present and future Köppen-Geiger climate classification maps at 1-km resolution. https://doi.org/10.6084/m9.figshare.6396959
  • Schiavina M., Freire S., Carioli A., MacManus K. (2023). GHS-POP R2023A - GHS population grid multitemporal (1975-2030).European Commission, Joint Research Centre (JRC). DOI:10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE
  • Global Administrative Areas (2023). GADM database of Global Administrative Areas, version 4.1. www.gadm.org
  • Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., D'Amico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., Kassem, K. R. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51(11):933-938.
temporalCoverage
spatialCoverage
@typePlace
nameWorldwide
sameAshttps://www.wikidata.org/wiki/Q13780930
distribution
  • @typeDataDownload
    namemosquitoalert_webserver
    descriptionDistribution by HTTP download from MosquitoAlert webserver
    encodingFormatTIF
    workExample./notebook/model_tables.py
    contentUrl
    • http://webserver.mosquitoalert.com/static/tigapublic/models/data_environment/human_presence_multilayer_025.tif
    contentSize27.9MB
variableMeasured
  • @typePropertyValue
    nameBAND 1
    descriptionKöppen-Geiger climate classification (0 == no data).
    unitTextcategorical
    qudt:dataTypexsd:int
  • @typePropertyValue
    nameBAND 2
    descriptionDistribution of residential population, expressed as the number of people per cell (-200 == no data).
    unitTextnumber of people per cell
    qudt:dataTypexsd:int
  • @typePropertyValue
    nameBAND 3
    descriptionGADM database of Global Administrative Areas (0 == no data).
    unitText
    qudt:dataTypexsd:int
  • @typePropertyValue
    nameBAND 4
    descriptionTerrestrial ecoregions of the world (0 == no data).
    unitTextcategorical
    qudt:dataTypexsd:int
creator
  • @typePerson
    @idZJ
    nameJužnič Zonta, Živko
    identifierhttps://orcid.org/0000-0002-2362-9771
    contactPoint
    @typeContactPoint
    roleNamedata engineer
    emailjzivko@gmail.com
    urlhttps://es.linkedin.com/in/zivko
measurementTechnique
  • Satellite images reanalysis
  • Population census of population
" ], "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# NO CODE\n", "# FULL WIDTH\n", "with open(f'{path}.json') as f:\n", " data = json.load(f)\n", "\n", "table = json2html.convert(json=data, clubbing=False)\n", "table_sub = re.sub('', '', table)\n", "\n", "HTML(table_sub)\n", "\n", "# Run the following in the command line to build a html table\n", "# $ jupyter nbconvert --to html --no-input --no-prompt build_tables.ipynb\n" ] }, { "cell_type": "code", "execution_count": null, "id": "7daa26ab", "metadata": { "papermill": { "duration": 0.006062, "end_time": "2024-07-01T13:29:53.971602", "exception": false, "start_time": "2024-07-01T13:29:53.965540", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "interpreter": { "hash": "524d3359b179f3b444361f48db8ae048bd8c237924fac1cd48a4c6f8144f6452" }, "kernelspec": { "display_name": "Python 3.7.10 64-bit ('scidb': conda)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.4" }, "metadata": { "interpreter": { "hash": "e3961729dbf4ff77740ff872c9a3eef08621b5b434e3d8d81026af4505918c74" } }, "papermill": { "default_parameters": {}, "duration": 1.736961, "end_time": "2024-07-01T13:29:54.302530", "environment_variables": {}, "exception": null, "input_path": "build_info.ipynb", "output_path": "./meta_ipynb/human_presence.ipynb", "parameters": { "path": "./meta/environment/human_presence" }, "start_time": "2024-07-01T13:29:52.565569", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }