I'm currently drawing up a mock database schema with two tables: Booking and Waypoint.
Booking stores the taxi booking information.
Waypoint stores the pickup and drop off points during the journey, along with the lat lon position. Each sequence is a stop in the journey.
How would I calculate the distance between the different stops in each journey (using the lat/lon data) in Excel?
Is there a way to programmatically define this in Excel, i.e. so that a formula can be placed into the mileage column (Booking table), lookup the matching sequence (via bookingId) for that journey in the Waypoint table and return a result?
Example 1:
A journey with 2 stops:
1 1 1 MK4 4FL, 2, Levens Hall Drive, Westcroft, Milton Keynes 52.002529 -0.797623
2 1 2 MK2 2RD, 55, Westfield Road, Bletchley, Milton Keynes 51.992571 -0.72753
4.1 miles according to Google, entry made in mileage column in Booking table where id = 1
Example 2:
A journey with 3 stops:
6 3 1 MK7 7DT, 2, Spearmint Close, Walnut Tree, Milton Keynes 52.017486 -0.690113
7 3 2 MK18 1JL, H S B C, Market Hill, Buckingham 52.000674 -0.987062
8 3 1 MK17 0FE, 1, Maids Close, Mursley, Milton Keynes 52.040622 -0.759417
27.7 miles according to Google, entry made in mileage column in Booking table where id = 3
If you want to find the distance between two points just use this formula and you will get the result in Km, just convert to miles if needed.
Point A: LAT1, LONG1
Point B: LAT2, LONG2
ACOS(COS(RADIANS(90-Lat1)) *COS(RADIANS(90-Lat2)) +SIN(RADIANS(90-Lat1)) *SIN(RADIANS(90-lat2)) *COS(RADIANS(long1-long2)))*6371
Regards
Until quite recently, accurate maps were constructed by triangulation, which in essence is the application of Pythagoras’s Theorem. For the distance between any pair of co-ordinates take the square root of the sum of the square of the difference in x co-ordinates and the square of the difference in y co-ordinates. The x and y co-ordinates must however be in the same units (eg miles) which involves factoring the latitude and longitude values. This can be complicated because the factor for longitude depends upon latitude (walking all round the North Pole is less far than walking around the Equator) but in your case a factor for 52o North should serve. From this the results (which might be checked here) are around 20% different from the examples you give (in the second case, with pairing IDs 6 and 7 and adding that result to the result from pairing IDs 7 and 8).
Since you say accuracy is not important, and assuming distances are small (say less than 1000 miles) you can use the loxodromic distance.
For this, compute the difference of latitutes (dlat) and difference of longitudes (dlon). If there were any chance (unlikely) that you're crossing meridian 180º, take modulo 360º to ensure the difference of longitudes is between -180º and 180º. Also compute average latitude (alat).
Then compute:
distance= 60*sqrt(dlat^2 + (dlon*cos(alat))^2)
This distance is in nautical miles. Apply conversions as needed.
EXPLANATION: This takes advantage of the fact that one nautical mile is, by definition, always equal to one minute-arc of latitude. The cosine corresponds to the fact that meridians get closer to each other as they approach the poles. The rest is just application of Pythagoras theorem -- which requires that the relevant portion of the globe be flat, which is of course only a good approximation for small distances.
It all depends on what the distance is and what accuracy you require. Calculations based on "Earth locally flat" model will not provide great results for long distances but for short distance they may be ok. Models assuming Earth is a perfect sphere (e.g. Haversine formula) give better accuracy but they still do not produce geodesic grade results.
See Geodesics on an ellipsoid for more details.
One of the high accuracy (fraction of a mm) solutions is known as Vincenty's formulae. For my Excel VBA implementation look here https://github.com/tdjastrzebski/Vincenty-Excel
Related
I work in the oil & gas industry and I'm seeking advice about how to calculate the minimum distance between a set of wells (the wells are drawn as straight lines on a map). My goal is for each individual well to have a unique "spacing" value (measured in feet) which is basically the straight-line horizontal distance to the closest wellbore on a map. Below is a simple example of what I'm trying to accomplish (assume the pipe | symbol is a wellbore and the dashes are the distance between the wells)
|--|---|-|
In the drawing above we have 4 wells. The 1st well (starting from the far left) would have a spacing value of 2 (since there are 2 dashes to the closest well), the 2nd well would also have a value of 2 (since the closest well is the one to the far left which is two spaces away), the 3rd well would have a value of 1, and the 4th well would have a value of 1.
Now imagine that I have hundreds of these wells (each with latitude/longitude points that describe the start & end points of each well) and I have them all mapped in TIBCO Spotfire (scattered across Texas). Do you guys know if it would even be possible to automate a calculation like the above? I would also like to build in a rule that says the max distance between wells is 2640 ft (half of a mile).
Any ideas are appreciated!
I think you should be able to do this without any R or iron python.
Within Spotfire, you can calculate the distance in miles between 2 points using the formula below (substitute 6371 for 3958.756 to get the answer in kilometres).
GreatCircleDistance([Lat 1],[Lon 1],[Lat 2],[Lon 2]) * 3958.756
For your use case, you could cross join your table of locations, so that you have a row for every possible location combination, then calculate the distance between them using the formula above. After that, it should be pretty straight forward to find each wells closest pair.
I have a large set of XYZ Cartesian points in Excel (some 40k actually) and was looking for a formula or macro to compare every point to every other point to get the distances between them.
The math to get the distance value between two 3D points is:
Distance=SQRT((X2 – X1)^2 + (Y2 – Y1)^2 + (Z2 – Z1)^2)
X1=the X value of the 1st point
X2=the X value of the 2nd point
Y1=the Y value of the 1st point
Y2=the Y value of the 2nd point
etc
Here is an example starting with 10 points:
http://i.imgur.com/U3lchMk.jpg
Would anyone know of a way to build this into Excel so that I can just copy the formula across the page to the horizontal limit? Or would you recommend a better way than using Excel?
As a secondary goal, I want to group the points into clusters that can connect by a distance lower than 2. But if I can accomplish the first goal, I can worry about the second later.
Actually, I was able to come up with the solution with a bit more research: i.imgur.com/9JL5Qni.jpg =SQRT(((INDIRECT("A"&$D2))-(INDIRECT("A"&E$1)))^2+((INDIRECT("B"&$D2))-(INDIRECT("B"&E$1)))^2+((INDIRECT("C"&$D2))-(INDIRECT("C"&E$1)))^2)
I have sorted array of real values, say X, drawn from some unknown distribution. I would like draw a box plot for this data.
In the simplest case, I need to know five values: min, Q1, median, Q3, and max.
Trivially, min = X[0], max = X[length(X)-1], and possibly median = X[ceil(length(X)/2)]. But I'm wondering how to determine the lower quartile Q1 and Q3.
When I plot X = [1,2,4] using MATLAB, I obtain following result:
It seems to me like there is some magic how to obtain the values Q1 = 1.25 and Q3 = 3.5, but I don't know what the magic is. Does anybody have experience with this?
If you go to the original definition of box plots (look up John Tukey), you use the median for the midpoint (i.e., 2 in your data set of 1, 2, 4). The endpoints are the min and max.
The top and bottom of the box are not exactly defined by quartiles, instead they are called "hinges". Hinges are the medians of the top and bottom halves of the data. If there is an odd number of observations, the median of the entire set is used in determining both hinges. The lower hinge is the median of (1,2), or 1.5. The top hinge is the median of (2,4), or 3.
There are actually dozens of definitions of a box plot's quartiles (Wikipedia: "There is no universal agreement on choosing the quartile values"). If you want to rationalize MatLab's box plot, you'll have to check its documentation. Otherwise, you could Google your brains out to try to find a method that matches the results.
Minitab gives 1 and 4 for the hinges in your data set. Excel's PERCENTILE function gives 1.5 and 3, which incidentally matches Tukey's algorithm at least in this case.
The median devides the data into two halves. The median of the first half = Q1, and the median of the second half = Q3.
More info: http://www.purplemath.com/modules/boxwhisk.htm
Note on the MatLab boxplot: The Q1 and Q3 are maybe calculated in a different way in MatLab, I'd try with a larger amount of testing data. With my method, Q1 should be 1 and Q3 should be 4.
EDIT:
The possible calculation that MatLab does, is the difference between the median and the first number of the first half, and take a quarter of that. Add that to the first number to get Q1.
The same (roughly) applies to Q3: Take the difference between the median and the highest number, and subtract a quarter of that from the highest number. That is Q3.
Understanding that it would only be an estimate...
How what decimal constant would be able to be used to find a point X Miles away from a point in latitude and longitude to facilitate creating a lat long bounding box.
Unfortunately there is no such simple constant. As you go farther north, the "walking distance" between lines of longitude becomes smaller and smaller. If you were right next to the north pole, you could walk in a circle around it, covering almost no distance at all, and yet you'd still have touched every line of longtiude.
What you need is the great-circle distance between two points on a sphere.
Not sure what you are trying to do. You want a create a bounding box based on distance from a point? Are you looking for a way to calculate new lat/long from given lat/long using a distance in miles?
You can use the manhattan function to get an approximation of distance (realizing that lat/long are based on a spheroid approximating the earth, and truly calculating this requires more math), calculating x and y values with a forumla to follow
Manhattan function:
sqrt(x*x + y*y)
X and Y from Lat/Long:
x = 69.1 * (lat2 - lat1)
y = 53 * (lon2 - lon1)
Still, that method is pretty error-prone.
There's the great circle distance formula too, gotta use some trig for it, but it's probably worth it since you can get pretty good error in approximation depending upon what part of the spheroid (e.g. the lat/long) you start at.
Check out this page:
http://www.meridianworlddata.com/Distance-Calculation.asp
If i have a position specified in latitude and longitude, then it can cover a box, depending on how many digits of accuracy are in the position.
For example, given a position of 55.0° N, 3.0° W (i.e. to 1 decimal place), and assuming a truncation (as opposed to rounding), this could cover anything that's 55.01° to 55.09°. This would cover the area in this box: http://www.openstreetmap.org/?minlat=55.0&maxlat=55.1&maxlon=-3.0&minlon=-3.1&box=yes
Is there anyway to calculate the area of that box? I only want to do this once, so a simple website that provides this calculation would suffice.
The main reason I want to do this is because I have a position to a very high number of decimal places, and I want to see how precise it is.
While the Earth isn't exactly spherical you can treat it as such for these calculations.
The North/South calculation is relatively simple as there are 180° from pole to pole and the distance is 20,014 km (Source) so one degree == 20014/180 = 111.19 km.
The East/West calculation is more difficult as it depends on the latitude. The Equatorial distance is 40,076 km (Source) so one degree = 40076/360 = 111.32 km. The circumference at the poles is (by definition) 0 km. So you can calculate the circumference at any latitude by trigonometry (circumference * sin(latitude)).
I have written an online geodesic area calculator which is available at
http://geographiclib.sf.net/cgi-bin/Planimeter. Enter in the four
corners of your box (counter clockwise) and it will give its area.