I am trying to generate random points for a survey, but I want the points to fall based on 2 polygons. I have created a polygon fishnet, and have a layer of forested habitats. I am trying to generate points so that there is one point per grid, and so that the point falls within a forested habitat in the grid. Is there a straightforward way to do this?
[GIS] Stratified Random sampling in ArcGIS
arcgis-desktop
Related Solutions
Personally I do not like the random point algorithm in ArcGIS. Alternatively, use Geospatial Modelling Environment's (GME) genrandompnts function. You will be able to identify specific polygons where random points will be excluded (see highlighted area in attached .jpg). Best of all this software is free.
GME provides you with a suite of analysis and modelling tools, ranging from small 'building blocks' that you can use to construct a sophisticated work-flow, to completely self-contained analysis programs. It also uses the extraordinarily powerful open source software R as the statistical engine to drive some of the analysis tools. One of the many strengths of R is that it is open source, completely transparent and well documented: important characteristics for any scientific analytical software.
In ArcGIS, this can be done with Create random point if you have spatial analyst or 3D analyst or Advanced(ArcInfo) licence
select each shapefile as "constraining_feature_class" and set the "minimum_allowed_distance"to 250 m.
In QGIS, from what I know, you can use "Vector ‣ Research Tools ‣ Random points" with a constraining feature class, but not for distance. Again, you can use this tool in a loop to add points one by one until you reach the required number.
On the other hand, a solution for simple random sampling with distance contraint is to recursively add your random point and erase the buffer around your random point from the feature class until all your features are completely erased. As mentioned by @Whuber, this will not optimize the number of sample points, but you can control the number of points per strata.
Finally, the optimal number of points with a distance constraint can be achieved by systematic sampling : create a grid (with fishnet) with evenly spaced points (in your case 250 m) and randomly select a rotation angle and shift value betwen 0 and 250 in X and Y direction. This will optimize the number of point samples (and you could randomly subselect some points to reach a given number inside each startum). However, note that systematic sample could be biased because of the spatial autocorrelation.
Best Answer
dissolve your forest as a multipart polygon
intersect with your fishnet
use the create random point tool with the result of your intersection as constraining feature class, and 1 as the number of point
CreateRandomPoints_management (out_path, out_name, {constraining_feature_class}, {constraining_extent}, {number_of_points_or_field}, {minimum_allowed_distance}, {create_multipoint_output}, {multipoint_size})