Abstract
Landscape is an ecological category represented by a complex system formed by interactions between society and nature. Spatial patterns of different land uses present in a landscape reveal past and present processes responsible for its dynamics and organisation. Measuring the complexity of these patterns (in the sense of their spatial heterogeneity) allows us to evaluate the integrity and resilience of these complex environmental systems. Here, we show how landscape metrics based on information entropy can be applied to evaluate the complexity (in the sense of spatial heterogeneity) of patches patterns, as well as their transition zones, present in a Cerrado conservation area and its surroundings, located in south-eastern Brazil. The analysis in this study aimed to elucidate how changes in land use and the consequent fragmentation affect the complexity of the landscape. The scripts CompPlex HeROI and CompPlex Janus were created to allow calculation of information entropy (He), variability (He/Hmax), and López-Ruiz, Mancini, and Calbet (LMC) and Shiner, Davison, and Landsberg (SDL) measures. CompPlex HeROI enabled the calculation of these measures for different regions of interest (ROIs) selected in a satellite image of the study area, followed by comparison of the complexity of their patterns, in addition to enabling the generation of complexity signatures for each ROI. CompPlex Janus made it possible to spatialise the results for these four measures in landscape complexity maps. As expected, both for the complexity patterns evaluated by CompPlex HeROI and the complexity maps generated by CompPlex Janus, the areas with vegetation located in a region of intermediate spatial heterogeneity had lower values for the He and He/Hmax measures and higher values for the LMC and SDL measurements. So, these landscape metrics were able to capture the behaviour of the patterns of different types of land use present in the study area, bringing together uses linked to vegetation with increased canopy coverage and differentiating them from urban areas and transition areas that mix different uses. Thus, the algorithms implemented in these scripts were demonstrated to be robust and capable of measuring the variability in information levels from the landscape, not only in terms of spatial datasets but also spectrally. The automation of measurement calculations, owing to informational entropy provided by these scripts, allows a quick assessment of the complexity of patterns present in a landscape, and thus, generates indicators of landscape integrity and resilience.
Highlights
Landscape is a level of ecological organisation comprising ‘natural’ and/or more anthropised ecosystems and is characterised as a complex environmental system
We demonstrated how landscape metrics based on information entropy can be applied to assess the complexity of patches patterns, and their transition zones, present in a Cerrado conservation area and its surroundings, located in south-eastern Brazil
Studies such as this, which seek to assess the complexity of the landscape in areas where the Cerrado has already been largely converted to other types of land use, can serve as a reference on the impacts on integrity and resilience that can be caused by the expansion of the area of agriculture in its core area, as well as in the new agricultural frontiers that shelter areas of cerrado (North and Northeast of Brazil)
Summary
Landscape is a level of ecological organisation comprising ‘natural’ and/or more anthropised ecosystems and is characterised as a complex environmental system These interrelated and interdependent units form heterogeneous spatial mosaic. As noted by Fabrig and Nuttle [3], spatial heterogeneity can be divided into two non-excluding components: 1) compositional heterogeneity, related to different cover types; 2) configurational heterogeneity, associated with spatial pattern. These spatial and temporal complexities in a landscape can be perceived inside each patch and among patches, and at the intersections of these units
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