The Landat Surface Reflectance (SR) product sometimes contains saturation in one or more bands (a value of 16,000 reflectance units or 160% reflectance). Presumably, these correspond to saturation at the detector; the same kind of saturation that is likely to occur over clouds or snow-covered areas. Such clouds and …
Clipping rasters can be trivial with a desktop GIS like QGIS or with command line tools like GDAL. However, I recently ran into a situation where I needed to clip large rasters in an automated, online Python process. It simply wouldn't do to interrupt the procedure and clip them myself …
I recently needed to develop a way of detecting water bodes in a Landsat image in order to mask them. Here's a surprisingly robust solution that's easy to implement.
For ongoing work I'm doing with Landsat data, I recently needed to generate some quick validation points against high-resolution aerial photography. I wanted to generate a fixed number of random rectangles, 90-meters squared (3 by 3 Landsat pixels), within the extent of a high-resolution aerial photograph I was using as …
The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) is a software system for generating surface reflectance data for Landsat 4, 5, and 7 TM or ETM+ sensors. The installation can be difficult, so I've prepared a guide based on my last successful installation of version 2.2.0.
The philosophical tension between the worldviews of holism and reductionism persists in today's ecology classroom. This debate traces roots to the "individualistic" versus "organismal" debate at the beginning of the twentieth century between the population and community ecology schools [1]. The chief actors in this debate were Henry Gleason, proponent …
Fine-grained customization of citation styles in LaTeX's default bibliography environment can be hard to achieve. Here, I'll describe an alternative to the standard bibliography environment that I found for style customization without sacrificing the raw power of LaTeX.
I experimented with Bayesian networks for land cover classification in the Detroit metro area using census data as predictors. An example of using Bayesian networks for land cover classification in R is presented with code samples.
A cross-posted article from AmericaView, this tutorial discusses how to access raster data in a PostGIS 2.x database and provide potential solutions, including code samples.