Assessing and monitoring landscape pattern structure from multi-scale land-cover maps can utilize morphological spatial pattern analysis (MSPA), only if various influences of scale are known and taken into account. This paper lays part of the foundation for applying MSPA analysis in landscape monitoring by quantifying scale effects on six classes of spatial patterns called: core, edge, perforation, branch, connector and islet. Four forest maps were selected with different forest composition and configuration. The sensitivity of MSPA to scale was studied by comparing frequencies of pattern classes in total forest area for various combinations of pixel size (P) and size parameter (S). It was found that the quantification of forest pattern wit...
Forest Spatial pattern, forest fragmentation and connectivity are policy-relevant indicators of sust...
Since landscape attributes show different patterns at different spatial extents, it is fundamental t...
Spatial patterns at multiple observation scales provide a framework to improve understanding of patt...
Morphological Spatial Pattern Analysis (MSPA) provides an intuitive, repeatable, and scale independe...
Pattern, connectivity, and fragmentation can be considered as key elements for a comprehensive quant...
Landscape-level forest spatial pattern describes the size and spatial configuration of forests. It i...
A theoretical and application framework for monitoring the state and dynamics of forest spatial patt...
Morphological Spatial Pattern Analysis (MSPA) provides an intuitive, repeatable, and scale independe...
Pattern, connectivity, and fragmentation can be considered as key elements for a comprehensive quant...
We propose a procedure to detect significant changes in forest spatial patterns and relevant scales....
The landscape-level spatial pattern of forest cover gives information on the size, shape and spatial...
The perceived realism of simulated maps with contagion (spatial autocorrelation) has led to their us...
Conservation and enhancement of ecological connectivity is widely recognized as one of the key objec...
A new method based on mathematical morphology and combined with customized measures was applied for ...
Understanding the relationship between pattern and scale is a central issue in landscape ecology. Pa...
Forest Spatial pattern, forest fragmentation and connectivity are policy-relevant indicators of sust...
Since landscape attributes show different patterns at different spatial extents, it is fundamental t...
Spatial patterns at multiple observation scales provide a framework to improve understanding of patt...
Morphological Spatial Pattern Analysis (MSPA) provides an intuitive, repeatable, and scale independe...
Pattern, connectivity, and fragmentation can be considered as key elements for a comprehensive quant...
Landscape-level forest spatial pattern describes the size and spatial configuration of forests. It i...
A theoretical and application framework for monitoring the state and dynamics of forest spatial patt...
Morphological Spatial Pattern Analysis (MSPA) provides an intuitive, repeatable, and scale independe...
Pattern, connectivity, and fragmentation can be considered as key elements for a comprehensive quant...
We propose a procedure to detect significant changes in forest spatial patterns and relevant scales....
The landscape-level spatial pattern of forest cover gives information on the size, shape and spatial...
The perceived realism of simulated maps with contagion (spatial autocorrelation) has led to their us...
Conservation and enhancement of ecological connectivity is widely recognized as one of the key objec...
A new method based on mathematical morphology and combined with customized measures was applied for ...
Understanding the relationship between pattern and scale is a central issue in landscape ecology. Pa...
Forest Spatial pattern, forest fragmentation and connectivity are policy-relevant indicators of sust...
Since landscape attributes show different patterns at different spatial extents, it is fundamental t...
Spatial patterns at multiple observation scales provide a framework to improve understanding of patt...