It helps to ‘fill in the gaps’ between known data points. Spatial interpolation is useful in a wide variety of contexts, such as estimating rainfall, groundwater pollution, temperature, or the spread of a disease. There are several types of spatial interpolation, including inverse distance weighting (IDW), spline, and Kriging. Spatial interpolation is a method that uses the known values at given locations to estimate a continuous surface. An evaluation of different models using statistical tests.Guidelines for making sure the data meets the necessary assumptions.A (relatively) jargon-free overview of Kriging.So, I’m writing the blog post I wish I had found while doing research for my Kriging analysis for my project with the American Red Cross. Though there is a wealth of information available online, much of it assumes that the reader already has much of this background information. The method presents an array of options and requires a bit of background statistical knowledge. Kriging is a complex and useful tool for GIS analysts. To see more blog posts about Summer of Maps, click here. Azavea’s Summer of Maps Fellowship Program provides impactful pro bono spatial analysis for nonprofits, while fellows benefit from Azavea mentors’ expertise. This post is part of a series of articles written by 2016 Summer of Maps Fellows.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |