{"id":45312,"date":"2025-10-28T11:20:26","date_gmt":"2025-10-28T03:20:26","guid":{"rendered":"https:\/\/www.1ai.net\/?p=45312"},"modified":"2025-10-28T11:20:26","modified_gmt":"2025-10-28T03:20:26","slug":"%e8%b0%b7%e6%ad%8c%e6%8e%a8%e5%87%ba-earth-ai-%e6%96%b0%e6%a8%a1%e5%9e%8b%ef%bc%8c%e5%bc%ba%e5%8c%96%e5%9c%b0%e7%90%86%e7%a9%ba%e9%97%b4%e6%8e%a8%e7%90%86%e8%83%bd%e5%8a%9b","status":"publish","type":"post","link":"https:\/\/www.1ai.net\/en\/45312.html","title":{"rendered":"Google launched Earth AI's new model to enhance geospatial reasoning"},"content":{"rendered":"

On October 28th, the day beforeGoogle<\/a>Declare that in Google Earth<\/a> And Google Cloud platform expands its \"Earth AI\" capability to launch a new generation of geospatial space AI Models<\/a>With the reasoning intelligence. The system combines basic models with multi-state reasoning and is designed to provide viable advice on complex global issues\u3002<\/p>\n

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Google states that the central focus of Earth AI is the integration of multidisciplinary models such as images, population and the environment with the reasoning Agent\u3002<\/p>\n

Agent can break down the natural language problem into a multi-step plan, using different models and geospatial tools and integrating the results to produce a holistic answer. For example, when predicting hurricane landings and assessing affected communities, the system can call on both weather forecasting, population dynamics and satellite imagery to identify critical infrastructure\u3002<\/p>\n

It was described that the update included two new models:<\/p>\n

IMAGE BASE MODEL: SUPPORTS NATURAL LANGUAGE REFERENCE SATELLITE IMAGERY, ENHANCES TEXT RETRIEVAL ACCURACY ABOVE 16% AND MORE THAN DOUBLES BASELINE ACCURACY IN ZERO SAMPLE TARGET TESTING<\/p>\n

DEMOGRAPHIC DYNAMIC MODELS: COVERING 17 COUNTRIES, PROVIDING MONTHLY UPDATES OF EMBEDDED VECTORS TO CAPTURE CHANGES IN HUMAN ACTIVITY. IN AN INDEPENDENT STUDY, THE MODEL RAISED THE R2 INDICATOR FOR THE LONG-TERM PREDICTION OF DENGUE FEVER IN BRAZIL FROM 0.456 TO 0.656\u3002<\/p>\n

In addition, Google emphasizes the predictive capacity of multi-model integration. For example, by combining population dynamics with geomorphological features, the prognosis of the United States Federal Emergency Management Agency (FEMA) National Risk Index has increased by an average of 111 TP3T, of which cyclone risk predictions have increased 251 TP3T and river flood risk has increased 171 TP3T\u3002<\/p>\n

In the assessment, Earth AI's geospatial reasoning agent achieved an overall accuracy rate of 0.82 in the question-and-answer benchmarking test, significantly better than the 0.50 of Gemini 2.5 Pro and 0.39 of Gemini 2.5 Flash\u3002<\/p>\n

Currently, Earth AI has been used in disaster response and public health research by United Nations organizations such as GlobalPulse, GiveDirectly, and has attracted business users, including Public Services, CARTO and Visiona Space Technology\u3002<\/p>","protected":false},"excerpt":{"rendered":"

On October 28th, a day ago, Google announced the expansion of its \"Earth AI\" capability on Google Earth and Google Cloud platforms to launch a new generation of geospatial AI models and reasoning intelligence. The system combines underlying models with multi-state reasoning and is designed to provide viable recommendations for complex global issues. Google states that the core of Earth AI is to combine multi-area models such as images, population and environment with reasoning Agent. Agent can break down the natural language problem into a multi-step plan, using different models and geospatial tools and integrating the results to produce a holistic answer. For example, when predicting hurricane landings and assessing affected communities, the system can call both weather forecasts and people<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[146],"tags":[167,7802,281],"collection":[],"class_list":["post-45312","post","type-post","status-publish","format-standard","hentry","category-news","tag-ai","tag-google-earth","tag-281"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/45312","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/comments?post=45312"}],"version-history":[{"count":0,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/45312\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/media?parent=45312"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/categories?post=45312"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/tags?post=45312"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/collection?post=45312"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}