It’s been chronicled before, but bears repeating: In the great race to grab a person’s location, there are many entities who could already map out interesting — and spooky — data about our whereabouts. For those of you using plastic to buy things, your credit card companies know where you purchase items, and for those living in the future with Square Card Case, they know, too. The cell phone carriers that charge you monthly fees for questionable signals certainly know your location, as do the handset makers and those who make operating systems on those phones. And, the big social networks — Facebook and Twitter — know our whereabouts, as well, capturing data about us every time we log a status update on the go.

Of course, en masse we don’t fully trust these kind of entities with our location data, even though they hold the keys to it. As a result, this has created an opportunity for developers to build software systems at the application layer to extract a user’s location in exchange for something useful, delightful, or both. It has been discussed endlessly “why” these applications want your location, but I want to take a slightly different tack — let’s explore “how” they go about getting that data, as well as the challenges and opportunities it presents to all participants.

There are three main ways a mobile application can collect your location data: (1) via explicit signals, such as checking in at a location (e.g. Foursquare); (2) via implicit signals, such as revealing your location at a specific point in time when you take a specific action (e.g. capturing a picture using Instagram); or (3) via passive data collection, or tracking, where the application works in the background to grab your location, whether or not you are actively using that application (e.g. Highlight).

Obtaining this location information is not easy work. Despite this, my belief is that there isn’t just one type of “location” that users create, and that because of these different types of location that we can generate, map, and broadcast, the “location category” can and will likely produce multiple winners, some with potentially big outcomes.

One of the biggest surprises of Facebook acquisition of Instagram is that we realized how much access Instagram had to location data that Facebook can now tap. While Instagram did an incredible job innovating around the camera software and social engagement features, they were also able to briefly capture a user’s location implicitly at the time an image was captured, so much so that if you took an Instagram at a Giants game and then clicked on the location-stamp, you could see a kaleidoscope of other Instagrams from the same ballpark.

The mindspace around mobile location at the application layer is currently owned by Foursquare, a company and product that, in my opinion, is one of the best mobile applications out there. Like Instagram, it is on my iPhone home screen. Everyone knows that Foursquare collects your location data when you explicitly inform the application that you’d like to check-in at a particular place. By creating an addictive game around this behavior, Foursquare also built out a database of places on the backs of gallivanting users, additionally encouraging them to broadcast their whereabouts into other social networks, as well as leaving tips for others and creating checklists for yourself. I now use the app for as my primary tool for local searches on the go, benefiting from others’ location data, behaviors, and recommendations.

Some products work to passively collect location data. These include Highlight and Glympse, among others, as well as apps used to help people track items or other people, find their friends, or track their children, such as Lookout and Footprints, among others — and also creeps people out more. While great software technologies are present today, battery degradation seems to be roadblock today, though one would have to imagine that battery performance will get better eventually and widen opportunities in this space.

Which each type of location data collected, there is a trade between the application and user– in exchange for being able to filter and share my photographs, Instagram knows where I am; in exchange for unlocking rewards or broadcasting that I’m at a cool place, Foursquare knows where I am; and in exchange for alerting me as to who may be around, Highlight grabs my location, too. I’ve been willing to offer my location to each of these applications, though I’d argue it’s not a relationship to take for granted — the product has to generate enough usefulness in order for me to continue using it.

Ultimately, I believe there will be winners in each “type” of location data collection, and some could be large outcomes, most likely through M&A. There are also new apps emerging, such as Pinwheel and Kullect, that could disrupt the current leaders. Despite the fact that these applications have yet to uncover robust business models (a common yet misplaced gripe), they could be incredibly valuable to larger companies (or even handset makers) who want to act on this data but don’t want to be seen as grafting it without permission.

Certain segments of consumers seem likely to trust applications with their location data, rather than larger platforms, but the tricky part is that consumers may grow suspicious if their location apps fall into the hands of larger entities they don’t trust as much. This is what *could* happen with Instagram now that it is in the hands of a powerful and capable owner, though by the looks of my Twitter feed, the rate of Instagrams is only increasing. For the moment, both Facebook and Twitter’s mobile apps don’t naturally incorporate location data into the mobile experience, which in turn creates opportunities for startups to help fill the void. This seems to indicate that for the right mobile product experiences, some consumers will continue to offer their location, and the developers building these applications have many great prizes to pursue.