Today's post in my continental divide series demonstrates the final computational step and shows one procedure for visualizing the Pacific and Atlantic catchment basins. In my previous... 더 읽어보기 >>

My colleague Greg Wilson, creator of the course Software Carpentry, proposed a couple of programming problems as prerequisites for the course. The idea is that if you can solve the problems... 더 읽어보기 >>

Today, in part 5 of my series on computing the US continental divide, we'll look at a technique called minima imposition. Previously we looked at data import and display, the watershed transform... 더 읽어보기 >>

Welcome to part 4 of my series on computing the US continental divide. Previously we looked at data import and display, the watershed transform and label matrices, and different kinds of... 더 읽어보기 >>

In the previous post in this series on computing the US continental divide, we used the watershed function to find catchment basins in a DEM (digital elevation model). The result was more than... 더 읽어보기 >>

This post is the second in my series on computing the location of the US continental divide. Today I'm going to look at the watershed transform, including how to compute and visualize it... 더 읽어보기 >>

Today I'm introducing a series on computing the location of the US continental divide. (I was inspired to tackle this topic by Brian Hayes' blog post on the divide; thanks very much to... 더 읽어보기 >>

Blog reader André recently asked me how to count the number of times each color appears in an image. One short solution involves optional output arguments from the function... 더 읽어보기 >>

In a blog comment earlier this summer, someone asked how to find "which labeled regions have a bright spot greater than some threshold?" That's a good question. It can be done efficiently... 더 읽어보기 >>

At the beginning of the upslope area series, I posted code showing how to compute the direction of maximum slope for a triangular facet, and how to compute the flow direction for a pixel. This... 더 읽어보기 >>