{"id":101,"date":"2021-02-06T15:05:28","date_gmt":"2021-02-06T15:05:28","guid":{"rendered":"http:\/\/geospatial-ai.de\/?post_type=rara-portfolio&p=101"},"modified":"2024-09-21T20:26:42","modified_gmt":"2024-09-21T20:26:42","slug":"geoint-api-services","status":"publish","type":"rara-portfolio","link":"https:\/\/geospatial-ai.de\/?rara-portfolio=geoint-api-services","title":{"rendered":"Geospatial Protests API Service"},"content":{"rendered":"\n

Query broadcasted events worldwide and visualize them using spatial aggregations.<\/p>\n\n\n\n

The service filters thousands of online news sources of the last 24 hours mentioning occurred protests or demonstrations. We constructed a web mercator spatial grid having a grid size being optimized for geographic visualization. Each grid cell is enriched with a count attribute representing the number of news article related to locations of the corresponding grid cell.<\/p>\n\n\n\n

The service uses the impressive data source provided by the Global Database of Events, Language and Tone (GDELT) Project (https:\/\/www.gdeltproject.org\/<\/a>).<\/p>\n\n\n\n

The service aggregates locations where some kind of protest took place using geospatial intelligence operations. The geospatial results support the GeoJSON and Esri Features format out of the box.<\/p>\n\n\n\n

Every geospatial result support the GeoJSON and Esri FeatureSet format out of the box. All endpoints support an optional date parameter for filtering the results. For best performance, the serverless cloud-backend calculate the geospatial aggregations of the last 24 hours between midnight and 1 AM UTC. The serverless functions save these geospatial features since November 19, 2021 and yesterday should be the latest available date. Without specifying a date, we have to calculate the geospatial features of the last 24 hours on-the-fly.<\/p>\n\n\n\n

\"\"
Aggregated broadcasted news<\/figcaption><\/figure>\n\n\n\n

Learn Path for geoprotests API<\/h2>\n\n\n\n

Analyze the broadcasted news related to protests, and identify hot- and cold spots.<\/p>\n\n\n\n

Ramp up your development environment<\/h3>\n\n\n\n

Setup your development environment and start with the first tutorial activating your Geospatial Knowledge skills. You will learn how to analyse the broadcasted news of the last 24 hours.<\/p>\n\n\n\n

<\/i><\/i><\/i>Beginner<\/em>
<\/i><\/i><\/i>25 minutes<\/em><\/p>\n\n\n\n

\n
Start coding<\/a><\/div>\n<\/div>\n\n\n\n
\n\n\n\n

Map historic demonstrations<\/h3>\n\n\n\n

Query hot spots and visualize them using a map widget. You will learn how to query the broadcasted news of the past and create stunning map views.<\/p>\n\n\n\n

<\/i><\/i><\/i>Intermediate<\/em>
<\/i><\/i><\/i>45 minutes<\/em><\/p>\n\n\n\n

\n\n\n\n

Publish and share insights using web maps and dashboards<\/h3>\n\n\n\n

Collaboration and communication are the key for every geospatial intelligence engineer. You will learn how to share your web maps and create easy-to-use dashboards on top of it.<\/p>\n\n\n\n

<\/i><\/i><\/i>Intermediate<\/em>
<\/i><\/i><\/i>30 minutes<\/em><\/p>\n\n\n\n

References:<\/strong><\/p>\n\n\n\n

[1] geoprotests API @RapidAPI<\/a>
Query broadcasted events worldwide and visualize them using spatial aggregations.<\/em>
<\/p>\n\n\n\n

\n
Terms of Use<\/a><\/div>\n<\/div>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Query broadcasted events worldwide and visualize them using spatial aggregations. The service filters thousands of online news sources of the last 24 hours mentioning occurred protests or demonstrations. We constructed a web mercator spatial grid having a grid size being optimized for geographic visualization. Each grid cell is enriched with a count attribute representing the … <\/p>\n","protected":false},"author":1,"featured_media":351,"template":"","rara_portfolio_categories":[10],"class_list":["post-101","rara-portfolio","type-rara-portfolio","status-publish","has-post-thumbnail","hentry","rara_portfolio_categories-api-services"],"_links":{"self":[{"href":"https:\/\/geospatial-ai.de\/index.php?rest_route=\/wp\/v2\/rara-portfolio\/101","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/geospatial-ai.de\/index.php?rest_route=\/wp\/v2\/rara-portfolio"}],"about":[{"href":"https:\/\/geospatial-ai.de\/index.php?rest_route=\/wp\/v2\/types\/rara-portfolio"}],"author":[{"embeddable":true,"href":"https:\/\/geospatial-ai.de\/index.php?rest_route=\/wp\/v2\/users\/1"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/geospatial-ai.de\/index.php?rest_route=\/wp\/v2\/media\/351"}],"wp:attachment":[{"href":"https:\/\/geospatial-ai.de\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=101"}],"wp:term":[{"taxonomy":"rara_portfolio_categories","embeddable":true,"href":"https:\/\/geospatial-ai.de\/index.php?rest_route=%2Fwp%2Fv2%2Frara_portfolio_categories&post=101"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}