In Google maps, the closer one gets to the pole, the more strechted out the map gets and sp each pixel of map represents less movment (asymtotically to 0 at the north pole)
I'm looking for a formula to connect the width of a pixel in degrees to the latitute (i.e. the real world distance represented by a pixel on the map). I have some data points here for zoom level 12 (IIRC)
Lat Width
0 0.703107352
4.214943141 0.701522096
11.86735091 0.688949038
21.28937436 0.656590105
30.14512718 0.60989762
35.46066995 0.574739011
39.90973623 0.541457085
41.5085773 0.528679228
44.08758503 0.507194173
47.04018214 0.481321842
48.45835188 0.468430215
51.17934298 0.442887842
63.23362741 0.318394373
72.81607372 0.208953319
80.05804956 0.122131316
90 0
The reason for doing this is I want to input lat/lng pairs and sort out exactly what pixel they would be located with respect to 0,0
I might be wrong but are you sure thos points are the pixel height? They seem to be a cosine which would be the pixel width not the height.
After a little trigonometry the pixel height adjusts to the formula:
where R is the earth radius, phi is the latitude and h is the height of a pixel in the equator.
This formula does not adjust to your points, that's why I asked if it was the width instead.
Anyway if you want so much precision that you cannot use the approximation in the previous answer you should also consider the R variable with the latitude and even with that I don't think you'll get the exact result.
Update:
Then the formula would be a cosine. If you want to take the variable radius of the earth the formula would be:
where R is the radius of the earth and d(0) is your pixel width at the equator. You may use this formula for R assuming the eearth to be an ellipsoid:
with a = 6378.1 (equator) and b = 6356.8 (poles)
While I am not sure what "height of a pixel" means, the plot of data (shown below) seems to fit the equation
y = a + bx + cx^2 + dx^3 where y = height, x = latitude
with coefficients
a = 7.0240278979641990E-01
b = 3.7784208874521786E-04
c = -1.2602864112736206E-04
d = 3.8304225582846095E-07
The general approach to find the equation is to first plot the data, then hypothesize the type of function, and then do a regression to find the coefficients.
Related
what's the algorithm to be able locate and display places around me within a particular distance such as 100m,using easting and northing and name of the place where I'm based .
To be more clear, lets suppose I'm based in charing cross and I want to find all places within 100m using easting and northing data for example, easting =10000m and easting=20000m.
Thank you
Pythagoras is the relevant maths.
If your position is (x,y) then you can calc a distance to any other point (x2,y2) with:
distance = sqrt((x2-x)^2 + (y2-y)^2)
So you could just loop over all points, calc their distance and order the results by nearest first.
For large data sets this may become impractical, in which case you'll want to partition the points into large rectangles. The first stage then is to identify which rectangle your (x,y) is within and the adjacent rectangles, then loop through all points in those rectangles. You need the adjacent rectangles because your (x,y) might be right on the boundary of its rectangle.
More generally this partitioning approach comes under the general heading of spatial hashing. For very large areas you want a tree structure known as a quadtree, that breaks large areas down into smaller and smaller regions, but that might be overkill for what you want.
I am assuming by Cartesian coordinates you also mean linear. If you are trying to do this using actual earth coordinates this answer gets more complicated (as we aren't on a flat earth). For simple linear coordinates you could do something like:
bool contains( x, y)
{
return (x >= minx) && (x <= maxx) && (y >= miny) && (y <= maxy);
}
The min, max coordinates would be your current position + how far out you wanted to go. I think this is what you wanted to know. If you need accurate earth coordinates you might look into some geospatial libraries. If you need and estimate you can still use the algorithm above but I would use something like Rhumb lines to calculate the min, max coordinates.
Hello Programming World,
I am using the Google Maps API v3 and I have a map overlay that I need specific coordinates from.
In the image, I've managed to convert the two pixel coordinate sets from the top left and bottom right into latitude and longitude coordinates manually. I've found these equalities:
Top Left:
(1px [x-axis], 1px [y-axis]) in pixels equals...
(-109.05005006119609° [Longitude], 41.00062580014626° [Latitude]) in latitude/longitude
Bottom Right:
(575px [x-axis], 423px [y-axis]) in pixels equals...
(-102.0423399657011° [Longitude], 36.99314427042206° [Latitude]) in latitude/longitude
However, my boss later decided that he'd rather have Google Maps draw this with Google's polyline drawing class (so I need every border angle that I drew in my overlay in latitude/longitude coordinates).
My question is, given these two sets of coordinates, is there some sort of equation or formula that I can use so that I can find the pixel coordinate (which I already have in an image map file) and convert it to a latitude/longitude coordinate.
Example: Point of interest at 132px x-axis and 10px y-axis = a° Longitude and b° Latitude
Find a and b.
I appreciate the help,
Llewgnolm
I talked to a friend of mine and he answered my question, so I figured I'd post the results here for anyone who'd like to know.
What we did was create a system of linear equations:
Lat/Lng = Multiplier*Pixels+Constant (L=m*p+c)
We substituted the numbers that I found manually into two equations for the system, i.e. (for Longitude):
-109.05...=m*(1)+c and
-102.04...=m*575+c and solved both for m and c
Eventually, the numbers came out to be (for longitude):
m = 0.01220895749767
c = -109.06228374530811
We can then use our values for m and c to plug in any pixel value to this equation and find the Latitude/Longitude, i.e (from the example numbers listed above again, for Longitude):
L = 0.01220895749767(132) - 109.06228374530811
L (Longitude at 132px in the x-direction) = -107.45070135561566°
This finds the degree values based off of the images pixels down to the 14th decimal (more than enough). For latitude, I just made a different system of equations with the latitude-based numbers inside to find different m and c values. Hope this helps anyone who stumbles across a similar problem.
I am trying to create a Circle Geometry in MySQL using the co-ordinates of the center and a radius. I searched everywhere...all i could find in the MySQL doc on the site were for polygons. May be i am looking in the wrong place. can anybody help me with an appropriate SQL that can help me create a table that stores this Circle geometry as one of the columns in the table?
Also, i am not even sure if there is a way to do so in MySQL?..The version i am using is MySQL 5.6.
Thanks in advance.
As of MySQL v5.6.1, you can use Buffer(g, d):
Returns a geometry that represents all points whose distance from the geometry value g is less than or equal to a distance of d.
Obviously, in your case g should be the point at the centre of the circle and d should be its radius.
There are two Parts:
A.For given tested points you have to check their relation with given circle.
B.You want to generate points on circumference of given circle.
A.Yes, First of all take the distance between your given point(test Point) and the centre of circle point. Both of these points are defined in Latitude and longitude. Distance formula between two points(x1,y1) and (x2,y2) is distance d= sqrt[ (x2-x1)^2 + (y2-y1)^2 ].
Now,
If this distance is less than radius of circle then your tested point is inside your circle.
If this distance is Greater than radius then tested point is outside the circle.
If this calculated distance is equal to radius of circle then this tested point is on your circle i.e. on the circumference of your circle.
B. In a circle the total angle theta is 360 degree or 2*Pi in radians.
For given Circle whose centre is (x1, y1) and radius is r.
x = x1 + r * cos(theta)
y = y1 + r * sin(theta)
where, theta is running from Zero to 2*Pi and Pi is 3.1415.
Depending upon how you do it. Example: if you wants 10 points on circle, then increment=(2*Pi-Zero)/10.
fist theta is zero, then theta is Zero+increment, then theta is Zero +increment+increment i.e. 2* increment and then zero + 3*increment and then so on. unless you get theta equal to 2*Pi.
For all above thetas calculate x and y. These all x and y coordinate points are on the circumference of the circle.
I'm receiving data from GPS and store them in MySQL database. I have following columns:
User ID (int)
Latitude (double)
Longitude (double)
Horizontal Accuracy (double)
Horizontal accuracy is radius around Lat/Long, so my user with equivalent probability can be in any point of this area.
I need to find out probability that two users was intersecting. But I also have vision area, which is 30 meters. If horizontal accuracy would be 0 I could just measure area of intersection of two circles that have radius of 30 meters around lat/long. But in my case that's not possible because horizontal accuracy could be in range from 5 to 3000. Usually it's more than my vision area.
I think I can measure area of intersection of two cones where inner circle of this cone will have radius of horizontal accuracy + 30 meters and outer circle will have radius of horizontal accuracy. But this solution seems to be little bit complicated.
I want to hear some thoughts about that and other possible solution.
I've checked MySQL Spatial extension and as far I can see it can't do such calculations for me.
Thanks.
I worked on just such a problem as you are describing. How I approached it was to convert the Lat/Long (world coordinates) into X/Y (Cartesian coordinates) then I applied the Pythagorean Theorem a^2 + b^2 = c^2 to solve the problem.
First you need to convert the Lat/Long Coordinates.
To get X you Multiply the Radius by the cosine (cos) of the angle (NOTE: this angle has to be expressed as radians).
To get Y you do the same as above but use the sine function (sin).
To convert degrees to radials Multiply the angle by the quantity of PI (Approx. 3.14159...) / 180.
Radians = Angle * (PI / 180);
To solve for the c^2 "C Squared" c = SQRT (a*a + b*b);
For more information on Degrees to Radians: http://www.mathwarehouse.com/trigonometry/radians/convert-degee-to-radians.php
For more information on: Converting Lat/Long to X/Y coordinates: http://www.mathsisfun.com/polar-cartesian-coordinates.html
I usually find the information that I need for this kind of problem by asking a question on ask.com.
All the best.
Allan
I am creating a 3D sphere gallery with ActionScript 3 and the Flash 10 3D (2.5D) APIs. I have found a method that works but is not ideal. I would like to see if there is a better method.
My algorithm goes like this:
Let n = the number of images
h = the height of each image
w = the width of each image
Approximate the radius of the circle by assuming (incorrectly) that the surface area of the images is equal to the surface area of the sphere we want to create.To calculate the radius solve for r in nwh = 4πr2. This is the part that needs to be improved.
Calculate the angle between rows. rowAngle = 2atan(h / 2 / r).
Calculate the number of rows.rows = floor(π / rowAngle).
Because step one is an approximation, the number of rows will not fit perfectly, so for presentation add padding rowAngle.rowAngle += (π - rowAngle * rows) / rows.
For each i in rows:
Calculate the radius of the circle of latitude for the row.latitudeRadius = radius * cos(π / 2 - rowAngle * i.
Calculate the angle between columns.columnAngle = atan(w / 2 / latitudeRadius) * 2.
Calculate the number of colums.columns = floor(2 * π / columnAngle)
Because step one is an approximation, the number of columns will not fit perfectly, so for presentation add padding to columnAngle.columnAngle += (2 * π - columnAngle * column) / column.
For each j in columns, translate -radius along the Z axis, rotate π / 2 + rowAngle * i around the X axis, and rotate columnAngle * j around the Y axis.
To see this in action, click here. alternate link. Notice that with the default settings, the number of items actually in the sphere are less by 13. I believe is the error introduced by my approximation in the first step.
I am not able to figure out a method for determining what the exact radius of such a sphere should be. I'm hoping to learn either a better method, the correct method, or that what I am trying to do is hard or very hard (in which case I will be happy with what I have).
I would divide this problem into two connected problems.
Given a radius, how do you pack things on to the sphere?
Given a number of things, how do you find the right radius?
If you have a solution to the first problem, the second is easy to solve. Here it is in pseudo-code.
lowerRadius = somethingTooSmall
fittedItems = itemsForRadius(lowerRadius)
while fittedItems < wantedItems:
lowerRadius *= 2
fittedItems = itemsForRadius(lowerRadius)
upperRadius = 2 * lowerRadius
while threshold < upperRadius - lowerRadius:
middleRadius = (upperRadius + lowerRadius)/2
if itemsForRadius(middleRadius) < wantedItems:
lowerRadius = middleRadius
else:
upperRadius = middleRadius
This will find the smallest radius that will pack the desired number of things with your packing algorithm. If you wish you could start with a better starting point - your current estimate is pretty close. But I don't think that an analytic formula will do it.
Now let's turn to the first problem. You have a very reasonable approach. It does have one serious bug though. The bug is that your columnAngle should not be calculated for the middle of your row. What you need to do is figure out the latitude which your items are in that is closest to the pole, and use that for the calculation. This is why when you try to fit 10 items you find a packing that causes the corners to overlap.
If you want a denser packing, you can try squishing rows towards the equator. This will result in sometimes having room for more items in a row so you'll get more things in a smaller sphere. But visually it may not look as nice. Play with it, and decide whether you like the result.
BTW I like the idea. It looks nice.
In the case of squares, it seems to be an approximate formula for knowing the relationship between the radius, the square's side and the number of squares embedded.
Following this, the number of squares is:
Floor[4 Pi/Integrate[(x^2 + y^2 + r^2)^(-3/2), {x, -a/2, a/2}, {y, -a/2, a/2}]]
or
Floor[(Pi r)/ArcCot[(2 Sqrt[2] r Sqrt[a^2+2 r^2])/a^2]]
where
r = Radius
a = Square side
If you plot for r=1, as a function of a:
Where you can see the case a=2 is the boundary for n=6, meaning a cube:
Still working to see if it can be extended to the case of a generic rectangle.
Edit
For rectangles, the corresponding formula is:
Floor[4 Pi/Integrate[(x^2 + y^2 + r^2)^(-3/2), {x, -a/2, a/2}, {y, -b/2, b/2}]]
which gives:
Floor[(2 Pi r)/(Pi-2 ArcTan[(2 r Sqrt[a^2+b^2+4 r^2])/(a b)])]
where
r = Radius
a,b = Rectangle sides
Let's suppose we want rectangles with one side half of the other (b = a/2) and a sphere of radius 1.
So, the number of rectangles as a function of a gives:
Where you may see that a rectangle with a "large" side of size 2 allows 10 rectangles in the sphere, while a rectangle of "large" side 4 allows only 4 rectangles.