I am using geopy to simply calculate the distance between two long,lat co-ordinates.
However I am confused on what scale the longitude should be on.
The latitude co-ordinated go from -90 to +90, and currently I've put my Longitude on a scale from 0-360 degrees - should this be -180 to 180 to satisfy :
great_circle(NYC, test).miles
where NYC and test are the co-ord pairs.
Thanks,
Izzy
Geopy Point latitude must be in range [-90; 90], longitude should be in range [-180; 180].
Longitude is automatically normalized (e.g. 185 is normalized to -175), while out-of-band latitudes would result in a ValueError being thrown. See the Point normalization testcases for getting the better idea on how normalization works: test/test_point.py
An example from docs for calculating distance between two points:
>>> from geopy import distance
>>> newport_ri = (41.49008, -71.312796)
>>> cleveland_oh = (41.499498, -81.695391)
>>> print(distance.distance(newport_ri, cleveland_oh).miles)
538.39044536
Related
I'm having trouble understanding what precisely the output of meshgrat means and how this relates to the lat and lon parameters of pcolorm(lat,lon,Z). I have a grid of global data, I'll call Z, at a 1.5 degree latitude x 1.5 degree longitude spatial resolution. Thus I have a matrix that's 120 x 240 (180 degrees of latitude / 1.5 = 120, 360 degrees of longitude / 1.5 = 240). Row 1 is 90 N and column 1 is 180 W (-180).
If I follow the MATLAB documentation, I can use meshgrat to produce the lat and lon arguments that I need to supply to pcolorm as follows.
latlim = [-90 90];
lonlim = [-180 180];
[lat,lon] = meshgrat(latlim,lonlim,[120 240]);
However, I don't understand why the spacing of the output is the way it is. For example, the first five values of lat are [-90.0000, -88.4874, -86.9748,-85.4622,-83.9496...]. The lon values follow the same spacing. The spacing is very close to 1.5 degrees, but it isn't. Why is there a discrepancy? The documentation claims that the paired lat and lon values are the location of the graticule vertices. In that case, these values make some sense, since there will always be one more vertex than actual grid cells. To test this, I made the following adjustment to the meshgrat code by adding one extra row and column:
latlim2 = [-90 90];
lonlim2 = [-180 180];
[lat2,lon2] = meshgrat(latlim2,lonlim2,[121 241]);
This did, indeed, produce the expected output, with the spacing now exactly at 1.5 degrees (i.e [-90.0000, -88.5000, -87.0000, -85.5000, -84.0000...]). Again, this is logical if these are viewed as vertices. But under this scenario lat and lon no longer match Z in size, which goes against how the documentation says to treat lat and lon in this case.
There seems to be a mismatch here: either the spacing in the lat lon grids are not accurate, or the girds are not the same size as the data, which would be fine in my mind as long as MATLAB knows how to interpret them accordingly, but the documentation does not seem to suggest using it this way. I have no detailed knowledge of how the MATLAB functions work at a finer level. Can someone explain to me what I'm missing?
Thus I have a matrix that's 120 x 240 (180 degrees of latitude / 1.5 = 120, 360 degrees of longitude / 1.5 = 240).
180/1.5 is indeed 120. But you also have an element at 0deg (presumably). That's 121.
I have two points as below. I need to get the distance between them in meters.
POINT (80.99456 7.86795)
POINT (80.97454 7.872174)
How can this be done via GeoPandas?
Your points are in a lon, lat coordinate system (EPSG:4326 or WGS 84). To calculate a distance in meters, you would need to either use the Great-circle distance or project them in a local coordinate system to approximate the distance with a good precision.
For Sri Lanka, you can use EPSG:5234 and in GeoPandas, you can use the distance function between two GeoDataFrames.
from shapely.geometry import Point
import geopandas as gpd
pnt1 = Point(80.99456, 7.86795)
pnt2 = Point(80.97454, 7.872174)
points_df = gpd.GeoDataFrame({'geometry': [pnt1, pnt2]}, crs='EPSG:4326')
points_df = points_df.to_crs('EPSG:5234')
points_df2 = points_df.shift() #We shift the dataframe by 1 to align pnt1 with pnt2
points_df.distance(points_df2)
The result should be 2261.92843 m
I am trying to calculate distance between two geographical coordinates and I want to convert geographical coordinates to the km. Therefore I used deg2km function. However, I realise that it is not convert points properly.
For instance, I used these two points.
p_x=[5; 10]; %degree
p_y=[8; 16]; %degree
pos_y=deg2km(p_y,6378);
pos_x=deg2km(p_x,6378);
It returns as:
pos_x= [556.58549846099 1113.17099692198]
pos_y= [890.536797537587 1781.07359507517]
When I calculate distance ( sqrt((556.5-1113.2)^2+(890.5368-1781.1)^2) ) between these points I obtained distance as : 1050.2464
However I checked it google map and also other websites it should be 1042 km.
Do you have any suggestion to calculate distance and also points as kilometers properly?
Thanks in advance!
edited as :
I've points(deg)and I need to convert them km and calculate distance between points.
LAT=[41.000173;41.010134]*pi/180;
LON=[28.995882;28.995584]*pi/180;
I used this code to calculate distance. It calculates properly.
But I can not convert my points to kilometers.
LAT=[41.000173;41.010134]*pi/180;
LON=[28.995882;28.995584]*pi/180;
R=6378; %km
for i=1:length(LAT)-1
psi(i,1) = atan2( sin (LON(i+1)-LON(i)) * cos (LAT(i+1)) , cos (LAT(i)) *sin (LAT(i+1)) - sin (LAT(i)) * cos (LAT(i+1)) * cos (LON(i+1)-LON(i)) );
a=(sin((LAT(i+1)-LAT(i))/2))^2+cos(LAT(i))*cos(LAT(i+1))*(sin((LON(i+1)-LON(i))/2))^2;
c=2*atan2(sqrt(a),sqrt(1-a));
d(i,1)=R*c;
end
I have markers that were plotted in a legacy system on a EPSG4326 map with a bounds of -180 to 180 latitude and -180 to 180 longitude. I'm now trying to plot these onto a EPSG4326 map that has a bounds of -90 to 90 latitude and -180 to 180 longitude. How can I convert the original coordinate to the new coordinate system so it appears on the new map at the same location? I'm trying to tackle this within a JavaScript application using the Leaflet mapping library. Any pointers or insight would be greatly appreciated.
As an example, the location of London on the source map that represents latitude in -180 to 180 range is approximately (Lat: 61.8750, Lon: 0.1278) and on destination map where latitude is -90 to 90 it would be about (Lat: 51.5074, Lon: 0.1278).
I figured it out!
newlat = (180.0/Math.PI*(2.0*Math.atan(Math.exp(oldlat*Math.PI/180.0))-Math.PI/2.0))
Thus if oldlat = 61.8750, newlat = 52.482780222078226 which is what I needed and solves my problem perfectly, converting a latitude with different extents into the new extents.
The reverse (if needing to reconvert) formula is:
oldlat = ((180.0/Math.PI)*Math.log(Math.tan((90.0+newlat)*Math.PI/360.0)))
For projection I am using
m_proj('Mercator')
Next I use the following to convert an array of lon and lat points into x y coordinates.
[x,y] = m_ll2xy(lon,lat)
The [x,y] I got were in some units that I didn't understand. For example the x corresponding to longitude of -180 and 180 degrees are -pi and pi, while the y corresponding to latitude of -85 to 85 degrees are -3.1313 and 3.1313.
I want to get the [x,y] in units of km, which I understand have to be defined from a fixed point. How can I do this? Thanks