# How the Network Funds Missions

The LayerDrone Network incentivizes image capture in a way that balances the need to create an initial supply of imagery with the need to respond to imagery demand.

The network, via a governance process, issues missions in different geographies around the world, funded through the initial supply of tokens. These missions will capture background imagery over portions of urban land, primarily cities or land with a dense built environment, and in areas where the network has both an understanding of local restrictions and potential buyers of the data. The goal of this expansion is to prove the initial use case to a market that is unaccustomed to data this fresh, high-resolution, and on-demand. This “supply-led expansion” will build the base library that others can find markets for.

The network also permits third parties to create and fund missions using tokens. This “demand-led expansion” complements the base network growth in three key ways:

* Expand to new areas the LayerDrone Network is not yet covering, though the network will need to respect local drone restrictions
* Fill in gaps in the base library in urban areas
* Capture fresher imagery, for example, wanting to see several city blocks after a flood or a major construction project

These missions typically have a data buyer identified and engaged prior to capture.&#x20;

Over time, demand-led missions should become the primary driver of network expansion.

<figure><img src="/files/Fjw6gOt36e8IdnImliQR" alt=""><figcaption></figcaption></figure>

<br>


---

# Agent Instructions: 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:

```
GET https://layerdrone.gitbook.io/layerdrone/the-layerdrone-protocol/how-the-network-funds-missions.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.
