UTM | Bidirectional UTM-WGS84 converter | Map library

This question is an extension of the one asked on this thread: Converting latitude and longitude points to UTM. I'm not sure if it should be a reply on there, but am asking it here for now.

I have a dataset containing biological records with lat/long co-ordinates from a number of UTM zones and various attributes (dates, recorders, quantity etc). I would like to convert these to UTM coordinates. I have found ways of converting lat/long to UTM when the points are all in the same UTM zone, but am struggling to find an effective solution when they are all in different zones. The only question asking something similar I can find is this one: Projecting long/lat with multiple UTM zones, where the OP is advised to do something completely different instead.

I have tried the answers in the (first) linked thread, where there is a function for finding the UTM Zone of long/lat co-ordinates, and a function for converting long/lat coordinates to UTM based on a specified zone.

To get a circular subset of a las-dataset with specific area, I would like to use lidR::clip_circular(). To do so, I first calculate the central point of my las-dataset, then I define the radius I want to use, to get a subset of exactly 500m^2 from the centroid of my las-dataset. The operation works and does not throw any error, the result however is not correct, see base::print() at the end of my short code snippet.

I have tried to use lidR::clip_roi() as well, providing a polygon representing my region of interest, but got the same, incorrect result. Now I do not have any clue how to go on. I could imagine, that it is about the crs I am using (EPSG:25832) or because the area is circular and not rectangular...

I recently started using the stars R package. I'm struggling with reassigning NA values to "Unknown". I found a potential solution here, but it doesn't seem to work on NAs. Any suggestions to fix this issue are greatly appreciated. for some reason SO doesn't like huge chunks of code without adding more information, so i'm adding some random text at the bottom.

Here's the code that I used:

I have a large set of coordinates from the critical and endangered habit federal registry. I'm trying to digitize these maps for analysis. Here's a sample of the data as an example.

I am trying to fetch sessions from GA4 which are relevant to specific UTM params.

In GA3 we were able to use segments (sessions::condition::ga:source==X;ga:medium==Y) but I can not find a way to do this on GA4.

I have those lines in the .htaccess file.

I have 14 raster files from each year of land use. I would like to crop these rasters using my shapefile area of interest. With these cut rasters I would like to create a list where each element represents each year cut by the shapefile.

I tried in a very simple and fast way using the for, crop and mask commands, but without success.

my data exemplo: raster and shape files : https://drive.google.com/file/d/1IOGWZ3_ckKj3UoZVd7ikR5l9n04xd6He/view?usp=sharing

my code

I am working with a large amount of CityGML 3d building data (LoD2) and imported the data using the 3D City Database (and its Importer/Exporter tool) (see https://www.3dcitydb.org/3dcitydb/) which creates a new schema in the database and uses java routines to translate the XML-style geodata to PostGIS compatible database input.

The information (spatial and non spatial) for each building is then written to different tables, where "building" table holds building meta data such as building function or street name and "surface_geometry" table holds solid and 3d surface geometries of all buildings. With columns "id", "parent_id" and "root_id" used as PKs and FKs to ensure the elements of one table can be matched to one or more elements of the other table.

Since I need 2d building footprints (or bird view polygones) for most of my analyses, I created queries to make surfaces 2d with st_force2d() before st_union()ing all 2d surface of the same building with group by on the available FK.

Are there any ideas how to improve the following code to effiecntly process a huge dataset?

The queries are

I am trying to see how many users have clicked on an ad campaign and signed up afterwards.

My Logging table has the columns IP, UserID, and Data (this has the $_GET info like utm_source = newsletter). A user may click a link in newsletter and then later sign up on my website (which is indicated when they have a UserID that is not blank). I am trying to group by IP and then see if any IP has had an instance of utm in Data column and a non-blank UserID (but note that these 2 criteria may be true on different rows)

Currently I have: