imagery | Image server / proxy that can resize images

Context: I am trying to find the directional heading from a small image of a compass. Directional heading meaning if the red (north) point is 90 degrees counter-clockwise from the top, the viewer is facing East, 180 degrees is south, 270 is west, 0 is north. etc. I understand there are limitations with such a small blurry image but I'd like to be as accurate as possible. The compass is overlaid on street view imagery meaning the background is noisy and unpredictable.

The first strategy I thought of was to find the red pixel that is furthest away from the center and calculate the directional heading from that. The math is simple enough.

The tough part for me is differentiating the red pixels from everything else. Especially because almost any color could be in the background.

My first thought was to black out the completely transparent parts to eliminate the everything but the white transparent ring and the tips of the compass.

True Compass Values: 35.9901, 84.8366, 104.4101

These values are taken from the source code.

I then used this solution to find the closest RGB value to a user given list of colors. After calibrating the list of colors I was able to create a list that found some of the compass's inner most pixels. This yielded the correct result within +/- 3 degrees. However, when I tried altering the list to include every pixel of the red compass tip, there would be background pixels that would be registered as "red" and therefore mess up the calculation.

I have manually found the end of the tip using this tool and the result always ends up within +/- 1 degree ( .5 in most cases ) so I hope this should be possible

The original RGB value of the red in the compass is (184, 42, 42) and (204, 47, 48) but the images are from screenshots of a video which results in the tip/edge pixels being blurred and blackish/greyish.

Is there a better way of going about this than the closest_color() method? If so, what, if not, how can I calibrate a list of colors that will work?

I'm fairly new to GEE, and I'm trying to process some imagery, then download the results. I need to mask about 30 years of Landsat data to isolate different land cover types, remove clouds, and calculate vegetation indices. Then, I need to export these data to do further analyses in R. I've managed to do all of the masking and calculating vegetation indices, but when I go to export the data, it gives me the user memory limit exceeded error. I tried to only download 1 year of data at a time but got the same error. I'm not sure how to accomplish what I'm doing, which is to do the heavy processing of the data in GEE then export it to do the additional analyses elsewhere. Any recommendations? Code below.

Edit: Added the ROI information as recommended.

I'm mostly a python developer but I'm trying my way in JavaScript and HTML for a university project. I'm using Leaflet to create a map and am currently trying to add some nodes to the map, using the coordinates, and subsequently adding edges to them. But for some reason it won't recognize the longitude. Here are my code and error:

1. HTML

I am writing code to get data and display it as list view on screen using flutter, but am getting NoSuchMethodError-- The method 'contains' was called on null. Tried calling contains(null). I thought the issue would be resolved by including the if statement(within the Widget getBody()), as, it points out specific actions to be taken if a certain state is returned, but had no luck.

here's the code for reference-- import 'dart:convert';

Google Earth (not engine) satellite view has varying spatial resolutions (i.e., pixel size) depending on various factors.

Let's say I'm interested in the below image, I can see it was taken on February 27, 2016, where do I find which satellite took this image and what is the spatial resolution of that image?

I read some answers such as here, but they are not up to date or just don't work.

I have a list of .tif imagery in a directory, which I loop through to do some raster math later on. I would like the .tif files to be ordered by date, so that when the loop is run I know which date corresponds to which .tif file based on its order in the list. I think I need to either rename the files, or figure out some way to sort them after the loop.

For example:

I tried to apply barchart using L.minichart in my map. When I use my own data from database it didnt follow my data. here is my code

I am cathing one API and I cannot deserialize a JSON property and I do not know where is the problem.

So I have an object from convertJSON2CSharp :

I am trying to convert a netCDF file from GOES Full disk to geotiff but have an error on last step.

Apparently the process of generating the tif from NC works and fulldisk.tif is generated but not georeferenced and I need it to overlay in a leaflet map.