> For the complete documentation index, see [llms.txt](https://docs.basin.global/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.basin.global/appendix/land-cover-classification-and-ecosystem-typologies/ecosystem-classification-frameworks/dynamic-world.md). # Dynamic World [Dynamic World](https://dynamicworld.app/) is a near real-time, 10M resolution, AI-powered global land cover dataset that serves multiple purposes. It is used by scientists and NGOs for monitoring planetary health, by companies to measure environmental impact and guide sustainable investments, and by governments to track their contributions to the Paris Agreement. The dataset, which is peer-reviewed and open-licensed, offers real-time insights into 9 different land use and cover types, and aims to make a positive impact on people and the planet. ## Dynamic World Land Cover Types * Trees * Water * Flooded Vegetation * Bare Ground * Crops * Grass * Shrub & Scrub * Snow/Ice * Built Up Area --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.basin.global/appendix/land-cover-classification-and-ecosystem-typologies/ecosystem-classification-frameworks/dynamic-world.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.