Fourier transforms: a continuum of functions to explore landscape dynamics in an open source space

Multi-temporal analysis based on remotely sensed data has played an important role in detecting changes, typically by creating land use maps from remotely sensed images acquired at different dates. However, general classification may present a number of drawbacks such as: i) an implicit degradation of the information content of images due to classification, coupled with ii) the loss of the continuous information about landscape processes, and iii) problems related to downscaling once images are classified with different resolutions. Alternative approaches based on continuous information for detecting landscape changes have been proposed, including fuzzy set theory, spectral unmixing, support vector machines, neural networks. The aim of this study is to describe Fourier transform open source functions to detect potential changes over the landscape.