GEODIST STATA TWO DATASETS HOW TO

Plotregion(margin(small)) graphregion(margin(small)) /// Scatter ylat xlon if inplume, msymbol(x) mcolor(red) /// Scatter ylat xlon if !inplume, msymbol(x) mcolor(green) /// Scatter yplat xplon, msymbol(O) mcolor(red) /// * show the projection details and compute the graph's height * project coordinates before creating a map Gen inplume = inrange(ib, wind-10, wind+10) & d < 4 * identify points within a certain range from the wind direction * calculate distances and initial bearing * form all combinations of sources and points normalize atan2 results (-pi to pi) to range from 0 to 360 degrees

GEODIST STATA TWO DATASETS HOW TO

Note that I kept things simple and did not address how to define a range of bearings that cross over the 360/0 degrees. To illustrate what's going on, I project the coordinates and create a map. From there, you can decide that points that are within a certain range of bearings around the wind direction (and within a certain distance) fall within the plume. The first step to a solution is to form all pairwise combinations of polluters with points of interests and then calculate the distance and initial bearing. Save 'points.dta', replaceNeither geodist nor geonear (both from SSC) calculate bearings between points but the formula for the initial bearing can be found on this excellent web site by Chris Veness. Input byte pid str16 pname double(plat plon) int windĢ 'Lurie Bell Tower' 42.291988 -83.71621 180 The second contains random points around these two 'polluters'. The first includes two 'polluter' locations and a wind direction (in degrees, north is 0) for each. You can then use basic trig to calculate distances and slopes.īefore trying to formulate a solution using geographic coordinates, I will create two demonstration datasets. If you use the default projection (Web Mercator), you will be working with a map where lines of constant bearing are represented as straight lines. You can sidestep the issue by converting geographic coordinates (latitude and longitude) to planar coordinates using geo2xy (from SSC). Conversely, if you travel in a straight line using the shortest path between two points, your bearing will constantly change as you make progress towards your destination. You can follow a line of constant bearing (using a compass) but that's not the shortest path unless you are headed due North or South. The concept of direction is a also a bit difficult to grasp when it relates to geographic coordinates. This sounds pretty complicated to achieve and I have no suggestion on how to go about creating such polygons. You would then use geoinpoly (from SSC) to identify points of interest that fall within these plume polygons. Presumably, time affects the progression and expansion of pollution plumes so intuitively, a solution would most likely require forming polygons that define the borders of each plume. I'm a bit reluctant to give advice because the vagueness on what should be considered downwind from the pollution source.

Geodist stata two datasets