PhenoVis – A tool for visual phenological analysis of digital camera images using chronological percentage maps - Leite, Roger A.; Schnorr, Lucas Mello; Almeida, Jurandy; Alberton, Bruna [UNESP]; Morellato, Leonor Patrícia Cerdeira [UNESP]; Torres, Ricardo da S.; Comba, João L.D. (Elsevier, 2016)
PhenoVis is framework for the visual phenological analysis of forest ecosystems. It contains the chronological percentage maps (CPM), a novel representation that is capable of discovering additional patterns by encoding percentage distributions of the data. Two types of masks are used in PhenoVis: a community mask , which considers all plant species in the image; and a species mask , associated with a given plant species. Among the several images taken at different times of the day, the image taken at noon is preferred for the analysis because it minimizes shadow effects. Therefore, only one image per day is used. The analysis considers the chromatic co- efficients associated with each pixel in the image. In PhenoVis we associate different colors with each bucket of the percentage histogram. The histogram granularity defines the size of a given bucket of the percentage distribution. The number of buckets is given by the number of colors available, and the range of the distribution is given by the IOI. The percentage map of a single input image consists of a normalized stacked bar chart. The chronological percentage map consists of a sequence of percentage maps stacked in chronological order, from top to bottom (portrait) or left to right (landscape).
Keywords: Phenology; Remote sensing; Similarity ranking; Vegetation index; Visual analytics