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Animate an UV sphere with (4D?) noise

I am using a C# port of libnoise with XNA (I know it's dead) to generate planets.
There is a function in libnoise that receives the coordinates of a vertex in a sphere surface (latitude and longitude) and returns a random value (from -1 to 1).
So with that value, I can change the height of each vertex on the surface of the sphere (the altitude), creating some elevation, simulating the surface of a planet (I'm not simply wrapping a texture around the sphere, I'm actually creating each vertex from scratch).
An example of what I have:
Now I want to animate the sphere, like this
But the thing is, libnoise only works with 3D noise.
The "planet" function maps the latitude and longitude to XYZ coordinates of a cube.
And I believe that, to animate a sphere like I want to, I need an extra coordinate there, to be the "time" dimension. Am I right? Or is it possible to do this with what libnoise offers?
OBS: As I mentioned, I'm using an UV sphere, not an icosphere or a spherical cube.
EDIT: Here is the algorithm used by libnoise to map lat/long to XYZ:
public double GetValue(double latitude, double longitude) {
double x=0, y=0, z=0;
double PI = 3.1415926535897932385;
double DEG_TO_RAD = PI / 180.0;
double r = System.Math.Cos(DEG_TO_RAD * lat);
x = r * System.Math.Cos(DEG_TO_RAD * lon);
y = System.Math.Sin(DEG_TO_RAD * lat);
z = r * System.Math.Sin(DEG_TO_RAD * lon);
return GetNoiseValueAt(x, y, z);
}

An n dimensional noise function takes n independent inputs (i0, i1, ..., in-1, in) & returns a value v, thus 3D noise is sufficient to generate a height map that varies over time. In your case the inputs would be longitude, latitude & time and the output would be the height offset.
The simple general algorithm would be:
at each time step (t){
for each vertex (v) on a sphere centered on some point (c){
calculate the longitude & latitude
get the scalar noise value (n) for the longitude, latitude & time
calculate the new vertex position (p) as follows p = ((v-c)n)+c
}
}
Note: this assumes you are not replacing/modifiying the original vertex values. You could either save a copy of them (uses less computation, but more memory) or recalculate them them based on a distance from c (uses less memory, but more computation). Also, you might get a smoother animation by calculating 2 (or more) larger time steps & interpolating to get the intermediate frames.
To the best of my knowledge, this solution should work for a UV sphere, an icosphere or a spherical cube.

Ok I think I made it.
I just added the time parameter to the mapped XYZ coordinates.
Using the same latitude and longitude but incrementing time by 0.01d gave me a nice result.
Here is my code:
public double GetValue(double latitude, double longitude, double time) {
double x=0, y=0, z=0;
double PI = 3.1415926535897932385;
double DEG_TO_RAD = PI / 180.0;
double r = System.Math.Cos(DEG_TO_RAD * lat);
x = r * System.Math.Cos(DEG_TO_RAD * lon);
y = System.Math.Sin(DEG_TO_RAD * lat);
z = r * System.Math.Sin(DEG_TO_RAD * lon);
return GetNoiseValueAt(x + time, y + time, z + time);
}
If someone has a better solution please share it!

Sorry for the late answer, but I couldn't find a satisfactory answer elsewhere online, so I'm writing this up for anyone who has this problem in the future.
What worked for me was using multiple 3d perlin noise sources, and combining them into 1 single noise source. Adding time to the xyz coordinates just creates a very noticeable effect of terrain moving in the (-1,-1,-1) direction.
Averaging over 4 uncorrelated noise sources does change the noise characteristics a bit, so you might have to adapt some factors to your use case.
This solution still isn't perfect, but I haven't seen any visual artifacts.
Code is C++ libnoise, but it should translate equally well to other languages.
noise::module::Perlin perlin_noise[4];
float get_height(ofVec3f p, float time) {
p*=2;
time /= 10 ;
return (perlin_noise[0].GetValue(p.x, p.y, p.z) +
perlin_noise[1].GetValue(p.x, p.y, time) +
perlin_noise[2].GetValue(p.x, time, p.z) +
perlin_noise[3].GetValue(time, p.y, p.z))/2;
}
Ideally, for a single 3d noise source, you want to multiply you x,y,z coords with a monotonic function of t, such that it explores a constantly expanding sphere surface of the noise source, but I haven't figured out the math yet..
Edit: the framework I use (openframeworks) has a 4d perlin noise function built in ofSignedNoise(glm::vec4)

Conversion of points in one Projected Coordinate System to Another

How can I convert points from one projected coordinate system to another using ArcObjects in C#?
//Coordinates in feet
double feetLong = 2007816.711;
double feetLat = 393153.895;
//Coordinates in decimal degrees (Should be the resulting coordinates)
//long: -97.474575;
//lat: 32.747352;
double[] feetPair = new double[] { feetLong, feetLat };
//Our projection used in GIS
string epsg32038 = "PROJCS[\"NAD27 / Texas North Central\",GEOGCS[\"GCS_North_American_1927\",DATUM[\"D_North_American_1927\",SPHEROID[\"Clarke_1866\",6378206.4,294.9786982138982]],PRIMEM[\"Greenwich\",0],UNIT[\"Degree\",0.017453292519943295]],PROJECTION[\"Lambert_Conformal_Conic\"],PARAMETER[\"standard_parallel_1\",32.13333333333333],PARAMETER[\"standard_parallel_2\",33.96666666666667],PARAMETER[\"latitude_of_origin\",31.66666666666667],PARAMETER[\"central_meridian\",-97.5],PARAMETER[\"false_easting\",2000000],PARAMETER[\"false_northing\",0],UNIT[\"Foot_US\",0.30480060960121924]]";
//Google Maps projection
string epsg3785 = "PROJCS[\"Popular Visualisation CRS / Mercator\",GEOGCS[\"Popular Visualisation CRS\",DATUM[\"D_Popular_Visualisation_Datum\",SPHEROID[\"Popular_Visualisation_Sphere\",6378137,0]],PRIMEM[\"Greenwich\",0],UNIT[\"Degree\",0.017453292519943295]],PROJECTION[\"Mercator\"],PARAMETER[\"central_meridian\",0],PARAMETER[\"scale_factor\",1],PARAMETER[\"false_easting\",0],PARAMETER[\"false_northing\",0],UNIT[\"Meter\",1]]";
This is the beginning of my code. I've tried using the CoordinateSystemFactory but never got anything to work. I intend to use ProjNet to solve this although I am open to any other way. I am really new to using ArcObjects to create custom tools and have been stuck on this for a while.

Could someone describe a 2d interpolation method that is better than bilinear interpolation?

I have a grid of data points that I currently use Bilinear interpolation on to find the missing points in the grid. I was pointed in the directions of Kriging aka thee best linear unbiased estimator, but I was unable to find good source code or an algebraic explanation. Does anyone know of any other interpolation methods I could use?
--Update
#Sam Greenhalgh
I have considered Bicubic Interpolation but the results I received using the code example I found seemed off.
Here is the code example for Bicubic
Note I am coding in C# but I welcome examples from other languages as well.
//array 4
double cubicInterpolate(double[] p, double x)
{
return p[1] + 0.5 * x * (p[2] - p[0] + x * (2.0 * p[0] - 5.0 * p[1] + 4.0 * p[2] - p[3] + x * (3.0 * (p[1] - p[2]) + p[3] - p[0])));
}
//array 4 4
public double bicubicInterpolate(double[][] p, double x, double y)
{
double[] arr = new double[4];
arr[0] = cubicInterpolate(p[0], y);
arr[1] = cubicInterpolate(p[1], y);
arr[2] = cubicInterpolate(p[2], y);
arr[3] = cubicInterpolate(p[3], y);
return cubicInterpolate(arr, x);
}
double[][] p = {
new double[4]{2.728562594,2.30599759,1.907579158,1.739559264},
new double[4]{3.254756633,2.760758022,2.210417411,1.979012766},
new double[4]{4.075740069,3.366434527,2.816093916,2.481060234},
new double[4]{5.430966401,4.896723504,4.219613391,4.004306461}
};
Console.WriteLine(CI.bicubicInterpolate(p, 2, 2));

One widely-used interpolation method is kriging (or Gaussian process regression).
However, the use of kriging is not advised when your data points are on a regular grid. The euclidian distances between data points are used to adjust the parameters of the model. But in a grid, there are much fewer values of distance than in, say, a randomly simulated set of points.
Nevertheless, even if your data points are regularly placed, it could be interesting to give it a try. If you are interested, you can use the following softwares:
DiceKriging package in R language (there exist others like kriging, gstat...)
DACE toolbox in Matlab
STK in Matlab/Octave
And many others (in python for example)...
NOTE: It can be interesting to note (I do not exactly in what context you want to apply kriging) that the kriging interpolation property can very easily be relaxed in order to take into account, for example, possible measurement errors.

If your data points are on a regular grid, I would recommend using a piecewise linear spline in two dimensions. You could fill the data for the rows (x-values) first, then fill the data for the columns (y-values.)
Math.NET Numerics has the piecewise linear spline function that you would need:
MathNet.Numerics.Interpolation.LinearSpline.InterpolateSorted

Is there an algorithm to compute miles between coordinates?

I want to be able to display a Bing map in a Windows 8/Store app with an array of pushpins/waypoints at a zoom setting that will show every location, but no more than that - IOW, I want as much detail as possible while still showing all of the locations/coordinates.
I have this pseudocode:
public static int GetMapZoomSettingForCoordinates(List<String> coordinatesList)
{
string furthestNorth = GetFurthestNorth(coordinatesList);
string furthestSouth = GetFurthestSouth(coordinatesList);
string furthestEast = GetFurthestEast(coordinatesList);
string furthestWest = GetFurthestWest(coordinatesList);
int milesBetweenNorthAndSouthExtremes = GetMilesBetween(furthestNorth, furthestSouth);
int milesBetweenEastAndWestExtremes = GetMilesBetween(furthestEast, furthestWest);
int greaterCardinalDistance = Math.Max(milesBetweenNorthAndSouthExtremes, milesBetweenEastAndWestExtremes);
return GetZoomSettingForDistance(greaterCardinalDistance);
}
...but the "sticking point" (the hard part) are the "milesBetween" functions. Is there an existing algorithm for computing the miles between two coordinates?
I do realize this is a U.S.-centric bunch of code for now (miles vs. kilometers); that is, for now, as designed.
UPDATE
This is my new pseudocode (actual compiling code, but untested):
public static int GetMapZoomSettingForCoordinates(List<string> coordinatePairsList)
{
List<double> LatsList = new List<double>();
List<double> LongsList = new List<double>();
List<string> tempList = new List<string>();
foreach (string s in coordinatePairsList)
{
tempList.AddRange(s.Split(';'));
double dLat;
double.TryParse(tempList[0], out dLat);
double dLong;
double.TryParse(tempList[0], out dLong);
LatsList.Add(dLat);
LongsList.Add(dLong);
tempList.Clear();
}
double furthestNorth = GetFurthestNorth(LatsList);
double furthestSouth = GetFurthestSouth(LatsList);
double furthestEast = GetFurthestEast(LongsList);
double furthestWest = GetFurthestWest(LongsList);
int milesToDisplay =
HaversineInMiles(furthestWest, furthestNorth, furthestEast, furthestSouth);
return GetZoomSettingForDistance(milesToDisplay);
}
private static double GetFurthestNorth(List<double> longitudesList)
{
double northernmostVal = 0.0;
foreach (double d in longitudesList)
{
if (d > northernmostVal)
{
northernmostVal = d;
}
}
return northernmostVal;
}
...I still don't know what GetZoomSettingForDistance() should be/do, though...
UPDATE 2
This is "more better":
public static int GetMapZoomSettingForCoordinates(List<Tuple<double, double>> coordinatePairsList)
{
var LatsList = new List<double>();
var LongsList = new List<double>();
foreach (Tuple<double,double> tupDub in coordinatePairsList)
{
LatsList.Add(tupDub.Item1);
LongsList.Add(tupDub.Item2);
}
double furthestNorth = GetFurthestNorth(LongsList);
double furthestSouth = GetFurthestSouth(LongsList);
double furthestEast = GetFurthestEast(LatsList);
double furthestWest = GetFurthestWest(LatsList);
int milesToDisplay =
HaversineInMiles(furthestWest, furthestNorth, furthestEast, furthestSouth);
return GetZoomSettingForDistance(milesToDisplay);
}
UPDATE 3
I realized that my logic was backwards, or wrong, at any rate, regarding meridians of longitude and parallels of latitude. While it's true that meridians of longitude are the vertical lines ("drawn" North-to-South or vice versa) and that parallels of latitude are the horizontal lines ("drawn" East-to-West), points along those line represent the North-South location based on parallels of latitude, and represent East-West locations based on meridians of longitude. This seemed backwards in my mind until I visualized the lines spinning across (longitude) and up and over (latitude) the earth, rather than simply circling the earth like the rings of Saturn do; what also helped get my perception right was reminding myself that it is the values of the meridians of longitude that determine in which time zone one finds themselves. SO, the code above should change to pass latitudes to determine furthest North and furthest South, and conversely pass longitudes to determine furthest East and furthest West.

You can use the Haversine formula to compute the distance along the surface of a sphere.
Here's a C++ function to compute the distance using the Earth as the size of the sphere. It would easily be convertible to C#.
Note that the formula can be simplified if you want to just find the distance either latitudinally or longitudinally (which it sounds like you are trying to do).

To get the straight line distance you use the Pythagorean Theorem to find the hypotenuse.
d = ((delta x)^2 + (delta y)^2)^.5
Basically square both the changes in the x direction and the y direction, add them, then take the square root.
in your pseudo code it looks like you could have many points and you want to find a maximum distance that should encompass all of them, which makes sense if you are trying to figure out a scale for the zoom of the map. The same formula should work, just use milesBetweenEastAndWestExtremes for delta x, and milesBetweenNorthAndSouthExtremes for delta y. You may opt to add a fixed amount to this just to make sure you don't have points right on the very edge of the map.

How to find the surrounding area 25 miles using latitude & longitude from the current user location

I found Haversine Formula in C# is there any other method better than this.
public double HaversineDistance(LatLng pos1, LatLng pos2, DistanceUnit unit)
{
double R = (unit == DistanceUnit.Miles) ? 3960 : 6371;
var lat = (pos2.Latitude - pos1.Latitude).ToRadians();
var lng = (pos2.Longitude - pos1.Longitude).ToRadians();
var h1 = Math.Sin(lat / 2) * Math.Sin(lat / 2) +
Math.Cos(pos1.Latitude.ToRadians()) * Math.Cos(pos2.Latitude.ToRadians()) *
Math.Sin(lng / 2) * Math.Sin(lng / 2);
var h2 = 2 * Math.Asin(Math.Min(1, Math.Sqrt(h1)));
return R * h2;
}

I suppose it is a matter of what you want to do with it. My guess is that you are trying to calculate distance based on a ZIP (Post) code and you want to know if pos2 is within x distance of pos1.
What you first need to understand is that (unless you have some awesome Geo Spatial data to work with) all calculations do not generally take into account elevation or any other topographical attributes of the given area so your calculations won't be exact. Further these calculations are "as the crow flies" which means point x to point y is a straight line so while point y may lie within 25 miles of central point x it may actually be 30 miles to travel from central point x to point y.
That being said the Haversine Formula is your best bet unless you are calculating small distances (< ~12 miles) in which case you could use Pythagorean's theorem which is expressed as:
d = sqrt((X2 - X1)^2 + (Y2 - Y1)^2)
Where X and Y are your coordinates, obviously. This is much faster but is far less accurate especially as distance increases.
The Haversine Formula is slow especially if you are repeated calling it but I am unaware of any faster methods for calculating distance based on this formula.