you can use U.S. National Grid functions. add this code to your index page
<script src=”usng.js” mce_src=”usng.js”></script>
and then run this method:
1.LLtoUSNG(lat, lon, precision) : convert lat/lng decimal degrees to a USNG string
alert(LLtoUSNG(lat, long, 5));
Five digits: 1 meter precision eg. "18S UJ ...
The answer depends on what you mean by "origin"
There are indeed 60 UTM zones numbered 1-60 and it starts at 180 W, so UTM zone 1 is used for longitude in [-180° -174°].
That being said, the origin of the center projection is located in the middle of the extent of each zone. The latitude of the center of projection remains 0 for all zones but the ...
If you check this page, you will notice:
For Level-1C and Level-2A, the granules, also called tiles, are 100x100 km2 ortho-images in UTM/WGS84 projection.
I guess the easiest way to get insight in tiles is to download a tile KML and open it in Google Earth or similar.
Such a tool already exists. It is called Sentinelsat and the source is available on GitHub. It offers a command line interface and a Python API. It works with Sentinel 1 and 2. The spatial query is based on a polygon and not a point, but otherwise this is exactly what you need.
EDIT: 1) you can return the product ID (or product ID list) using the query ...
S2 partitioning in MGRS is tricky specially when the data is between UTM zones and the tiles overlap, see the figure below. Tiles from left to right are 20_M_QE, 20_M_RE, 21_M_SV and 21_M_TV:
A search made through opensearch for the region returns one S2 acquisition broken in two tiles, 20_M_RE and 21_M_TV:
So if you are interested in data in the ...
GeographicLib (written by me) includes a utility GeoConvert to convert between UTM/MGRS/Lat+Long. If you want to try it out before downloading it, use the online version of GeoConvert.
The algorithm used by GeographicLib is an extension of Krüger's 1912 series. The
derivation is given in this 2011 paper in the Journal of Geodesy. You can download a ...
MGRS is based entirely on UTM (Universal Tranverse Mercator) projected Coordinate Reference Systems. The first two numbers of an 8 digit grid, for instance, are the same as the UTM zone (these divide the world into 59 strips, each running from the equator to one of the poles). The difference is in the lettering that MGRS uses - the letter after the UTM ...
Welcome to GIS.SE.
The go-to tool for MGRS is usually GeoTrans. If you want a nice map viewer that supports display in both MGRS and Lat/Long (and UTM), try FalconView (which uses GeoTrans underneath).
If you are on Windows, there are pre-built installers. Make sure you get the version that matches your host operating system (32 or 64 bit) and that you ...
Doing this the "obvious" way will be accurate (and fast) enough: Convert the center of the MGRS square to UTM (exact). Convert UTM to Lat/Long (error = 5 nanometers). Compute the new position as a geodesic calculation (error = 15 nanometers). Convert to UTM (error = 5 nanometers). Convert to MGRS (exact). So the total error is 25 nanometers or less. (...
If you have ArcGIS 10+, you can use the convert Coordinate notation tool, as mentioned by Neil Ayres.
If you don't have ArcGIS, you can use EarthPoint batch converter, which works directly from a spreadsheet.
According to the United States Naval Academy the Military Grid Reference System consists of:
the UTM zone (1-60)
a latitude band (C-X, excluding I and O; A-B and Y-Z are used for North and South Pole in the polar stereographic projection)
A two-letter 100K grid square
1-5 digits easting
1-5 digits northing
The easting and northing define the accuracy and ...
i wrote a blog on this exact topic awhile back.
I am not sure how it would fare on a huge scale like the whole of the US but if you have a metric (well, cartesian) system QGIS' Vector -> Research Tools -> Vector Grid tool will let you create rectangles. The mmqgis plugin's Create -> Create Grid Lines Layer would be another alternative.
Depending on your extends, your local government might already have a ...
In QGIS, use the tool Extract Vertices to convert the vertices of your polygon layer to points. Make sure to save this layer in a geographic coordinate system.
You can view the coordinates of each point by clicking on it with the Identify tool.
To extract all the coordinates as a table, use the Field Calculator to add X and Y fields. Then save the ...
You can use the field calculator to add this values to the attribute table of the layer (may be a virtual field is the best, because this values are recalculated when opening the attribute table).
Open the attribute table of your layer and select field calculator (the abacus icon):
Similar way you can create x_min, y_min and y_max. You can find the bound ...
For UTM (and MGRS), the easting should always be bigger than 100 km and smaller than 900 km. I ran some test points on UTM 11 North.
easting northing latitude longitude
100000 0 0 -120.592
200000 0 0 -119.695
800000 0 0 -114.305
900000 0 0 -113.408
The central meridian of zone 11 is -117,...
First, make sure both the X and Y fields you already have are up to date, as moving features does not update these automatically. Re-calculate Geometry. In a model, I would make these updates a precondition of the MGRS update step.
I have several short Python field calculation scripts. They are designed for my area of interest, so you will have to ...
In response to your comment question "how to simulate this algorithm":
This is a pretty brute solution, but easy to implement and should give good performance:
Use any of the UTM converters that work "as expected", placing the coordinates in 13R.
Then, check if the folder exists in the Sentinel 2 data structure. If yes, you're done, hooray.
If not, check ...
I'm afraid you would have to provide a little more information for a more detailed response. If you are familiar with Python you can use the mgrs library to convert MGRS to Decimal Degrees and then use the reverse geocode tool to get the address.
m = mgrs.MGRS()
coords = m.toLatLon("34TCK9320739642")
output would be a tuple:
I'm not sure if this is going to work but I did this once. Add the data with the first UTM zone (for instance Zone 40) and add the same data again for the second zone (UTM zone 41), merge both layers and clip it for the area of interest.
Open the map and go to near the bottom of the source code.
The file you want is usng.js
Given the definition of the MGRS from wikipedia we know that your example 4QFJ123678 can be split up as follows:
4Q is the Grid Zone (columns in a range of 1-60 and rows in the range C-X omitting I and O). As rows increase go further east, as columns increase go further North.
FJ is the Grid Square (columns in the range A-Z and rows range A-V, both omitting ...
I think you need to approach this by thinking about the precision in cell or grid sizes. For instance 4QFJ 12345 67890 .......precision level 1 m would give you a 1m x1m cell within a grid. So I believe that both these coordinates 4QFJ 1234 6789 to 4QFJ 1230 6785 will give you a cell that is 10m x 10m. If you are after 50m* 50m blocks then the format you ...
Kind of surprised that everyone recommended a software tool over what you wanted
I need an algorithm. Can anyone point me to a reference to such an algorithm, or to open source software that does this conversion?
Fairly well written is a lat/long to UTM conversion function written in Python - https://github.com/Turbo87/utm/blob/master/utm/conversion.py#...
There's almost certainly a more elegant way to do this.
After you generate the grid of points, add the lat/lon (or UTM) values to the attribute table. Then use the Convert Coordinate Notation tool to generate the MGRS strings and use them to label the grid.
there are some ways for drawing a grid on a map. i havent tried them before bacause i have never needed it.
1.you can check out matplotlib library for drawing grid on a map but it looks like a bit complex. it supports lots of projection.
you can find its doc here as Basemap Matplotlib Toolkit 1.0.3 documentation.
2.for qgis, you can try GridPluginLayer ...