2017
DOI: 10.1080/22797254.2017.1330650
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GuidosToolbox: universal digital image object analysis

Abstract: The increased availability of mapped environmental data calls for better tools to analyze the spatial characteristics and information contained in those maps. Publicly available, userfriendly and universal tools are needed to foster the interdisciplinary development and application of methodologies for the extraction of image object information properties contained in digital raster maps. That is the overarching goal of GuidosToolbox, which is a set of customized, thematically grouped raster image analysis met… Show more

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Cited by 209 publications
(111 citation statements)
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“…We used a moving window of 51 × 51 pixels (corresponding to an area of about 2.34 km 2 ) centered on each forest pixel to compute the percentage of forest pixels in the neighborhood. We used this percentage as an indication of the forest fragmentation (Riitters & Wickham, 2012; Vogt & Riitters, 2017). The size of the moving windows was based on a compromise: a sufficiently high number of cells (here 2601) had to be considered to be able to compute a percentage and a reasonably low number of cells had to be chosen to have a local estimate of the fragmentation.…”
Section: Methodsmentioning
confidence: 99%
“…We used a moving window of 51 × 51 pixels (corresponding to an area of about 2.34 km 2 ) centered on each forest pixel to compute the percentage of forest pixels in the neighborhood. We used this percentage as an indication of the forest fragmentation (Riitters & Wickham, 2012; Vogt & Riitters, 2017). The size of the moving windows was based on a compromise: a sufficiently high number of cells (here 2601) had to be considered to be able to compute a percentage and a reasonably low number of cells had to be chosen to have a local estimate of the fragmentation.…”
Section: Methodsmentioning
confidence: 99%
“…Urban areas and water bodies extents were obtained directly from the CLC dataset. Forest core was determined from CLC forest classes using Morphological Spatial Pattern Analysis (MSPA) (Soille and Vogt, 2009) implemented in the GuidosToolbox software (Vogt, 2016). MSPA is a sequence of mathematical morphological operations that allow to classify geometrical properties of discrete patches or their parts in a raster thematic layer.…”
Section: Sampling Strategy Developmentmentioning
confidence: 99%
“…Foreground Area Density (FAD), a spatial fragmentation measure, was calculated in 20 m buffers from high spatial resolution classifications around the three Krensen creeks with the GUIDOS Toolbox (Vogt and Riitters 2017). Twenty meters is the upper limit of the recommended buffer zone width in Ghana for minor perennial streams (Ministry of Water Resources Works and Housing 2013).…”
Section: Methodsmentioning
confidence: 99%
“…Results are classified into six classes: < 10% (rare), 10-39% (patchy), 40-59% (transitional), 60-89% (dominant), 90-99% (interior), 100% (intact). The proportion of the six FAD classes was calculated for the buffers as the average from the five observation scales (Vogt and Riitters 2017).…”
Section: Methodsmentioning
confidence: 99%