I imagine lidar gets you one step closer to the data you're really after.
Given that, it would be foolhardy to proceed with vision and sound only because humans can get by with mostly just those. Better sensors push down the intelligence requirements for complex behavior. For example, insects as a group have a wider variety of sensors than any other group of organisms. With pin sized brains and milliwatt power, they forage, hunt, fly, walk and some even learn or communicate with an elaborate (combinatorial) language. Their array of specialized sensors plays a large role in allowing for their surprisingly rich sets of behavior.
While I'm here, I'll also note that optical illusions are not things to get fooled by but instead, show the strength or assumptions of our predictive world models. Brains do not see the world as it is (see the checker shadow illusion and inattentive blindness), they predict based on, smooth, filter and adjust their inputs to more effectively act in the world. All inferential systems must have particular structural biases to do well in their target domain. In animals, between what was evolved and what is learned based on early environment; expectation and experience ends up top-down affecting what we see. It's very non-trivial -- many were surprised to learn for example, that even the "simple" retina receives inputs also from non-visual areas (and the details differ from species to species).
This is used a lot in mapping and research into e.g. forest canopies in the amazon. LIDAR has been extensively deployed on aircraft for this kind of purpose.
I've seen high-res LIDAR scans made available by my country's state survey for e.g. archeologists and it has the 'true ground' through the vegetation. Its like the vegetation has been stripped away and has a clinical feel when rendered.
Some lidars also offer two distance estimates per point, a first distance and a secondary distance. On the lidar I used that had this capability, the secondary distance was not always robust. But on permeable materials like vegetation, the secondary distance would typically indicate solid materials behind the initial curtain of material.
Anyway, the presence of multiple distance returns in a small solid-angle area (whether from the above primary/secondary, or from nearby scan points) can indicate density of vegetation. You can certainly see "through" the small gaps in a hedge. Depending on the lidar, and the range, gaps as small as a few cm^2 could be enough (talking about vehicle-mounded lidar for autonomous navigation, not remote sensing of forest canopy).