Mihai-Sorin Stupariu

Understanding landscape change using historical maps. Case study Sinaia, Romania

Abstract Please click here to download the map associated with this article. The aim of this study is to produce a long term analysis of land cover change in Sinaia (Romanian Southern Carpathians), based on a time series of five maps, realised in the years 1790, 1912, 1970, 1990 and 2009. The maps were digitised and for each of the corresponding time periods, the binary change map and the trajectory of change were generated. The maps were produced within a Geographical Information System (GIS) based on a land cover change derived from cartographic digitisation. The scale of the maps created is 1:100,000 and the area is 5727 ha. The comparison of the maps was completed by using appropriate quantitative techniques and documentary sources or subsequent studies. At a historical scale, the main phenomenon was that of forestation, which mainly occurred during the 19th century. In the first part of the 20th century, Sinaia developed as an elegant tourist location and during the second part of the century it became an urban centre, and this evolution left its mark on the landscape structure. Today, an increasing urban pressure can be identified, due to residential expansion and mass-tourism.

Multi-scale feedbacks between tree regeneration traits and herbivore behavior explain the structure of pasture-woodland mosaics

ContextThe pasture-woodlands of Central Europe are low-intensity grazing systems in which the structural richness of dynamic forest-grassland mosaics is causal for their high biodiversity. Distinct mosaic patterns in Picea abies- and Fagus sylvatica-dominated pasture-woodlands in the Swiss Jura Mountains suggest a strong influence of tree species regeneration ecology on landscape structural properties. At the landscape scale, however, cause-effect relationships are complicated by habitat selectivity of livestock.ObjectivesWe asked which tree species regeneration traits and what kind of feedbacks among local-scale vegetation dynamics and landscape-scale herbivore behavior are causal for the contrasted landscape structural characteristics of Picea- and Fagus-dominated pasture-woodlands.MethodsWe performed simulation experiments of mosaic pattern formation in both pasture-woodland types. The regeneration traits, namely dispersal distance, resistance to browsing and tolerance to shade, and the rules for habitat selection of cattle were modified and the corresponding shifts in landscape structure were analyzed.ResultsDispersal distance showed a significant, but only local, effect promoting forest fringe formation. Saplings’ resistance to browsing mainly determined overall tree cover, but did not influence landscape structure. At the landscape scale, both shade tolerance of saplings and selective habitat use by cattle were responsible for forest-grassland segregation: high shade tolerance triggered segregation, whereas non-selective habitat use hindered it.ConclusionsExisting local-scale theory on pasture-woodland dynamics is complemented by an herbivore-vegetation feedback among spatial scales. In low-intensity pastures, where large herbivores are preferentially “grazers” and trees form dense canopies, an intrinsic trend towards forest-grassland segregation at the expense of forest-grassland ecotones is predicted.

Geometric approaches to computing 3D-landscape metrics

The relationships between patterns and processes lie at the core of modern landscape ecology. These dependences can be quantified by using indices related to the patch-corridor-matrix model. This model conceptualizes landscapes as planar mosaics consisting of discrete patches. On the other hand, relief variability is a key factor for many ecological processes, and therefore these processes can be better modeled by integrating information concerning the third dimension of landscapes. This can be done by generating a triangle mesh which approximates the original terrain. The aim of this methodological paper is to introduce two new constructions of triangulations which replace a digital elevation model. These approximation methods are compared with the method which was already used in the computation of 3D-landscape metrics (firstly for parameterized surfaces and secondly for two landscape mosaics). The statistical analysis shows that all three methods are of almost equal sensitivity in reflecting the relationship between terrain ruggedness and the patches areas and perimeters. In particular, either of the methods can be used for approximating the real values of these basic metrics. However, the two methods introduced in this paper have the advantage of yielding continuous approximations of the terrain, and this fact could be useful for further developments.

Shifts in wind energy potential following land-use driven vegetation dynamics in complex terrain

Many mountainous regions with high wind energy potential are characterized by multi-scale variabilities of vegetation in both spatial and time dimensions, which strongly affect the spatial distribution of wind resource and its time evolution. To this end, we developed a coupled interdisciplinary modeling framework capable of assessing the shifts in wind energy potential following land-use driven vegetation dynamics in complex mountain terrain. It was applied to a case study area in the Romanian Carpathians. The results show that the overall shifts in wind energy potential following the changes of vegetation pattern due to different land-use policies can be dramatic. This suggests that the planning of wind energy project should be integrated with the land-use planning at a specific site to ensure that the expected energy production of the planned wind farm can be reached over its entire lifetime. Moreover, the changes in the spatial distribution of wind and turbulence under different scenarios of land-use are complex, and they must be taken into account in the micro-siting of wind turbines to maximize wind energy production and minimize fatigue loads (and associated maintenance costs). The proposed new modeling framework offers, for the first time, a powerful tool for assessing long-term variability in local wind energy potential that emerges from land-use change driven vegetation dynamics over complex terrain. Following a previously unexplored pathway of cause-effect relationships, it demonstrates a new linkage of agro- and forest policies in landscape development with an ultimate trade-off between renewable energy production and biodiversity targets. Moreover, it can be extended to study the potential effects of micro-climatic changes associated with wind farms on vegetation development (growth and patterning), which could in turn have a long-term feedback effect on wind resource distribution in mountainous regions.

Graph-Based Wavelet Representation of Multi-Variate Terrain Data

Terrain data can be processed from the double perspective of computer graphics and graph theory. We propose a hybrid method that uses geometrical and vertex attribute information to construct a weighted graph reflecting the variability of the vertex data. As a planar graph, a generic terrain data set is subjected to a geometry‐sensitive vertex partitioning procedure. Through the use of a combined, thin‐plate energy and multi‐dimensional quadric metric error, feature estimation heuristic, we construct ‘even’ and ‘odd’ node subsets. Using an invertible lifting scheme, adapted from generic weighted graphs, detail vectors are extracted and used to recover or filter the node information. The design of the prediction and update filters improves the root mean squared error of the signal over general graph‐based approaches. As a key property of this design, preserving the mean of the graph signal becomes essential for decreasing the error measure and conserving the salient shape features.

Heuristic-driven graph wavelet modeling of complex terrain

We present a novel method for building a multi-resolution representation of large digital surface models. The surface points coincide with the nodes of a planar graph which can be processed using a critically sampled, invertible lifting scheme. To drive the lazy wavelet node partitioning, we employ an attribute aware cost function based on the generalized quadric error metric. The resulting algorithm can be applied to multivariate data by storing additional attributes at the graph’s nodes. We discuss how the cost computation mechanism can be coupled with the lifting scheme and examine the results by evaluating the root mean square error. The algorithm is experimentally tested using two multivariate LiDAR sets representing terrain surface and vegetation structure with different sampling densities.

A quiver approach to studying orbit spaces of linear systems

Abstract Orbit spaces associated to linear actions are of particular interest in control theory. Their geometrical properties can be naturally investigated by using the representations of quivers as an abstract framework. The aim of the paper is to bring into attention an application of this approach and to show how the use of quivers makes it easy handling concepts arising in control theory. Specifically, the natural duality between controllable and observable systems, as well as the construction of compactifications for the associated orbit spaces is interpreted in terms of opposite quivers.