There are a lot of good mapping and stitching tools out there. Most cost [a lot of] money, but many of these have free demos if you are just doing some experimentation. Drone deploy and pix4d are among the easiest to use ... just upload your images to the cloud and wait for an email saying your map is done.
For the 100% free route, take a look at "open drone map". That will produce your classic 3d model + orthophoto stitch. The quality may not be quite as good as the premier commercial programs, but it's definitely worth taking a look at.
There is another 100% free option that I have developed myself via research projects at the U of MN aerospace dept. It is done in a 'guts out' style for education and research purposes; written entirely in python to be as open as possible. Our use-case is surveying large areas and then looking for "needles in the haystack." (Specifically invasive plants.) The traditional orthophotos and 3d models that the premier tools create don't work very well for my purposes, so we rolled our own software. Our tools create a map mosaic that is othorectified, yet preserves all the original images. (It's bit hard to describe in a few sentences.) The final result is all the original pictures are presented in a big pile: arranged, lined up, and stetched, and positioned in their exact correct locations. Then we can go search through the map (with no quality or information loss) much like browsing a google map -- but you are looking at all the raw original images. As I'm viewing the final map, I can call forward any image that covers the current center of view, so I can see all the original angles of something of interest. This let's me spot vines crawling up tree trunks for example. I know, I'm pretty far out there in my own la-la land.
If anyone wants to take a peek, here is the link to the software (scroll down through the readme to see some screenshots and more details):
https://github.com/UASLab/ImageAnalysis
Here are a couple videos that show the map results in action:
As you've started to see, the quality of your survey images go a long way towards determining the quality of your final maps. The rule of thumb is to have about 70% overlap (end-to-end and side-to-side) so the stiching algorithms can do their thing reliably. Low altitude surveys over crops/trees can be especially difficult to stitch. That is one of the things I addressed in my project to some level of success. I was able to stitch image sets that completely blew up drone deploy or pix4d.
Aerial mapping is a big field with a lot to learn on many levels. (I know a few things, but only a few ...) If anyone is interested in trying out our UMN mapping tools, feel free to ask questions. Some things are documented pretty well, some things not so much.
Thanks,
Curt.