Configurational Heterogeneity Research Articles

The spatial heterogeneity of urban green space distribution and configuration in Lilongwe City, Malawi.

Urban green spaces provide several benefits related to the quality of urban life. The existence and spatial arrangement of these spaces within neighbourhoods and functional land uses have significant implications for the well-being of urban dwellers. Previous studies on green spaces in urban areas of Malawi have focused on a broader and macro-level perspective, offering insightful information on general trends in different cities. However, there is a significant research shortage in localised understanding, which requires carrying out micro-level assessments concentrating on land use zones and neighbourhoods within these cities. In this study, we used remote sensing data and landscape metrics to understand the distribution and configuration of urban green spaces in the city's neighbourhoods and functional land uses and their relationship with urban form. The study revealed that 20% of neighbourhoods fail to meet the WHO-recommended standard of 9 m2 of green space per person, with a predominant concentration of these undersupplied areas in high-density and quasi-residential zones. In addition, 56.2% of Lilongwe City's total green area was contained under functional land uses. Particularly, high-rise residential, medium-density residential, low-density residential, quasi-residential, high-rise flat area, commercial class, high-rise commercial, heavy industry, light industry, and government land use zones contained 17.3%, 12.0%, 22.2%, 12.0%, 4.1%, 6.4%, 6.1%, 5.0%, 1.6%, and 13.3% of the total green spaces in functional land uses, respectively. Importantly, this research found significant correlations between urban form metrics, namely building coverage, building density, building perimeter area ratio, road density, and the distribution and configuration of urban green spaces. This necessitates an integrated approach to urban planning and design, emphasising the importance of balancing development with green space preservation.

Dynamic archetypes of agricultural land systems in Germany from 1992 to 2019

Grasslands, important agricultural land systems, are undergoing significant shifts such as intensification, abandonment, and conversion to alternative land uses in Europe, leading to biodiversity loss. Despite major efforts, the European Union´s Common Agricultural Policy (CAP) has been unable to halt the decline of grasslands and to appropriately adjust management intensity because implemented policies have not considered the heterogeneity of grassland systems. However, accounting for this heterogeneity is essential to increase the policies´ effectiveness. In this study, we used archetype analysis to identify recurrent patterns in the heterogeneity of farm configurations, using Germany as an example, that can help tailor policy instruments to specific regional conditions. By applying self-organising maps, we reveal nine archetypes integrating 16 farm accountancy indicators. Advancing archetype analysis, we discuss their dynamics (including their emergence, disappearance and persistence) between 1992 and 2019 at the level of federal states and interpret these dynamics in the light of CAP. For example, archetypes in the western federal states are dominated by small crop and dairy farms, while archetypes in the eastern federal states are more diverse, including larger subsidised farms and medium crop farms. Moreover, archetype dynamics in the southern federal states indicate a decline in small dairy farms and an increase in small crop farms, implying the loss of valuable habitats for wild species. Policy instruments tailored to such regional conditions could more appropriately halt this loss. These insights derived from agricultural land systems in Germany can enrich the debate about how to better tailor policy instruments to regional conditions to preserve functional grassland systems in Europe and worldwide.

Exploring optimal features and image analysis methods for crop type classification from the perspective of crop landscape heterogeneity

Agricultural landscape structure (e.g., the shape of fields, crop diversity, and landscape heterogeneity) greatly influences the selection of methods for large-scale crop mapping using remote sensing data. However, in-depth assessments of its impacts on crop mapping remain infrequent in the existing literature. This study investigated the optimal crop identification features and image analysis methods including pixel- and object-based approaches on crop classification, through the integration of spectral and textural features across various quantitative agricultural landscapes. In the experiments, crop fields were initially delineated into four distinct landscapes using the K-means clustering algorithm based on analyzing 13 selected landscape metrics such as PLAND, LSI and SHDI. Both pixel- and object-based approaches were then employed to conduct crop classification was then conducted using 48 selected features including 9 band reflectance, 23 vegetation indices (VIs), and 16 textures) and two image analysis methods. Specifically, five classification schemes for the different combinations of feature datasets and image analysis methods were explored to assess the impacts of crop heterogeneity on crop classification. Results indicated the five landscape metrics (e.g., SPLIT, SHEI, Average distance, etc.) performed best in assessing crop heterogeneity. In general, spectral bands and VIs had a higher contribution in the compositional heterogeneity, while textural features and VIs played a more important role in the configurational heterogeneity. VIs in the object-based approach and texture features in the pixel-based approach can improved crop classification accuracy in configurational landscapes. The findings provide a theoretical basis on selecting optimal features and image analysis methods for crop classification in complex agricultural landscapes.

Vibration localization and reduction of double-plate structures

A thin plate-type resonator is attached to a host-stepped plate to achieve vibration localization and reduction in initial low-order global vibration modes. A semi-analytical method is proposed to analyze the free and forced vibrations of the double-plate structure, considering the geometric configuration's heterogeneity and discontinuity. The double plate structure is divided into several sub-plates for individual modeling, with admissible functions constructed for the displacements of each subdomain. These subdomains are then combined into a unified whole through displacement compatibility conditions. The no-orthogonality between global vibration and localized modes is determined using analytic mode functions obtained by the Ritz method with special admissible functions, which is crucial for suppressing the multiple resonance peaks of global vibration using the integrated plate-type resonator. An intriguing finding is that at the frequency veering point of global vibration modes and localized modes, the non-orthogonality can lead to two coupled global-localized modes that are similar to the initial localized mode, and the vibration of initial global modes can be mainly concentrated in the resonator region outside the plate during free vibration. For force vibration of the double plate, the initial resonance peak splits from one into two smaller resonance peaks due to the two coupled global-localized modes. Furthermore, the coupled global-localized mode allows for a substantial reduction in the host plate vibration while making a negligible impact on the total mass and global vibration frequency. This study presents a promising approach for reducing multimodal vibrations in lightweight structures.

Area and configuration of both semi‐natural habitats and vineyards influence arthropods in South African and central European agricultural landscapes

Abstract Restoring the heterogeneity of farmland mosaics can help mitigate the ongoing global decline of biodiversity. It has been shown that semi‐natural habitats in viticultural landscapes influence biodiversity in vineyards. However, less attention has been paid to the influence of the extent of vineyard fields and their arrangement in the landscape. Using previously published data, we investigated the influence of both semi‐natural habitats and vineyard fields on arthropod diversity in vineyards in 35 viticultural landscapes located in South Africa and Austria. Effects on several arthropod groups were assessed using standardised landscape predictors that integrate compositional (total area) and configurational (shape and spatial arrangement) heterogeneity of semi‐natural habitats and vineyards. In addition, we assessed the influence of within‐vineyard vegetation cover and farming system (organic or non‐organic) to explore local‐scale effects. Within‐vineyard vegetation and flower cover had a consistent positive influence on most arthropod taxa, whereas farming system had little effect. In addition, configurational heterogeneity of semi‐natural vegetation and vineyards influenced several taxa. However, different taxa showed contrasting relationships with configurational heterogeneity, hindering general recommendations for optimal configuration of semi‐natural elements and vineyards in the landscape. The only significant response to compositional heterogeneity was bug abundance in South Africa, which increased with increasing proportion of semi‐natural elements. We found that increasing vegetation cover in vineyards is an effective and easily implementable measure to improve biodiversity in vineyards. In addition, the spatial arrangement of vineyards influences within‐vineyard arthropod diversity as much as the spatial arrangement of semi‐natural vegetation in the landscape, which expands the possibilities for planning viticultural landscapes with high overall biodiversity.

Impacts of the attributes of patches and the surrounding matrix on the phylogenetic diversity of tree species in urban remnant forests

AbstractUrbanization is a major cause of biotic homogenization and evolutionary poverty. Urban remnant forests are biodiversity hotspots in cities but are prone to phylogenetic homogenization. However, how urbanization‐driven changes in patch attributes and landscape heterogeneity levels of the surrounding matrix affect plant phylogenetic diversity in urban remnant forests remains unclear. We quantified tree phylogenetic diversity and structure in 30 remnant forest patches in Guiyang, China, using chloroplast genome data and analyzed the effects of patch attributes and the surrounding matrix on tree phylogenetic diversity and structure in the forests while considering tree species stage. The phylogenetic diversity of saplings/seedlings was lower than that of adult trees. Small patches contributed more than large patches to the overall phylogenetic diversity of remnant forest ecosystems. Additionally, tree phylogenetic diversity was positively associated with configurational heterogeneity of the surrounding matrix, while phylogenetic diversity and relatedness were negatively related to the percentage of surrounding impervious surfaces and patch size. Accordingly, we suggest maintaining configurational heterogeneity and controlling the speed of urban expansion in the surrounding matrix to better conserve urban remnant forests. Furthermore, the preservation of small forest remnants and tree species in the sapling/seedling stage should be prioritized.

Crop and landscape heterogeneity increase biodiversity in agricultural landscapes: A global review and meta-analysis.

Agricultural intensification not only increases food production but also drives widespread biodiversity decline. Increasing landscape heterogeneity has been suggested to increase biodiversity across habitats, while increasing crop heterogeneity may support biodiversity within agroecosystems. These spatial heterogeneity effects can be partitioned into compositional (land-cover type diversity) and configurational heterogeneity (land-cover type arrangement), measured either for the crop mosaic or across the landscape for both crops and semi-natural habitats. However, studies have reported mixed responses of biodiversity to increases in these heterogeneity components across taxa and contexts. Our meta-analysis covering 6397 fields across 122 studies conducted in Asia, Europe, North and South America reveals consistently positive effects of crop and landscape heterogeneity, as well as compositional and configurational heterogeneity for plant, invertebrate, vertebrate, pollinator and predator biodiversity. Vertebrates and plants benefit more from landscape heterogeneity, while invertebrates derive similar benefits from both crop and landscape heterogeneity. Pollinators benefit more from configurational heterogeneity, but predators favour compositional heterogeneity. These positive effects are consistent for invertebrates and vertebrates in both tropical/subtropical and temperate agroecosystems, and in annual and perennial cropping systems, and at small to large spatial scales. Our results suggest that promoting increased landscape heterogeneity by diversifying crops and semi-natural habitats, as suggested in the current UN Decade on Ecosystem Restoration, is key for restoring biodiversity in agricultural landscapes.

Generation of a text description of weakly structured optical coherence tomography images

Computer vision methods help to automate and improve processes in the field of medicine. In the field of ophthalmology, computer vision algorithms can be used to analyze images obtained using optical coherence tomography OCT, to identify pathologies and changes in the structure of the eye, however, due to the heterogeneity of patterns and configurations of tomographs, a comprehensive solution is needed. Within the framework of this work, an approach to the construction of a system for generating a text description of DICOM images using artificial intelligence methods is presented. To build a system of automatic description of anatomical properties and pathologies, a set of models for detection and classification was built on the OCT image. Data augmentation was performed for the task of recognizing areas with retinal slices in the OCT image. The computational experiment of constructing classification models showed recognition accuracy from 0.75 to 0.93 according to the balanced accuracy metric. Based on the developed models, a web service has been developed to demonstrate the functionality, which provides a report on finding 11 tags on an OCT scan.

Diversifying agroecological systems: Plant-pollinator network organisation and landscape heterogeneity matter

Agroecology is a process-based agriculture that implements agrobiodiversification to stabilize ecosystem processes and crop yield, leading to sustainable food systems. Traditionally, agrobiodiversification focused on increasing within-farm plant richness, which may increase local species richness of higher trophic levels. However, it is increasingly recognized that stabilizing ecosystem processes involving plant-animal interactions –e.g., pollination- requires practices that consider the organisation of interactions and heterogeneity effects at landscape level. In this work, we investigated how plant-pollinator interactions organised in agricultural landscapes harbouring agroecological farms and how landscape heterogeneity modulated interactions organisation. We characterized the organisation of 36 plant-pollinator networks describing interactions in nine agricultural landscapes -i.e., agroecological farms and their surroundings- across four flowering peak periods in the Agri-food region of central Córdoba, Argentina. We evaluated (1) centrality to network organisation of plant and pollinator only registered interacting in agroecological farms, farm surroundings (unique species) or in both locations (shared species); and (2) network organisation across gradients of landscape configurational (mean edge density) and compositional (forest proportion) heterogeneity. We found that plant-pollinator networks at landscape scale showed nested structures. Shared plant and pollinator species were the less represented in such networks but were central to networks organisation, i.e., they were connected to most species and with the highest frequency. Results also showed that network organisation changed with landscape configurational heterogeneity. Higher landscape mean edge density was associated with higher total and unique plant richness in networks and lower richness of shared plants. Network connectance and nestedness decreased with higher landscape mean edge density, i.e., plant and pollinator species interacted with less species, shared less interaction partners with more specialist species and showed lower interaction frequency with generalist partners in more heterogeneous landscapes. Our study showed that in agricultural landscapes harbouring agroecological farms (1) a few species inhabiting and showing interactions in both agroecological farms and their surroundings are key to the organisation of plant-pollinator interactions, and (2) landscape heterogeneity modulates such organisation. As interaction networks dynamic is influenced by network organisation, landscape configurational heterogeneity may modulate the stability of the pollination process and ultimately agroecological production. Thus, the agrobiodiversification of agroecological systems may benefit from considering the complexity of plant-pollinator interdependencies across agricultural landscapes and the effects of landscape heterogeneity on such complexity.

Heterogeneity of dynamic synergetic configurations of salience network in children with autism spectrum disorder.

Atypical functional connectivity (FC) patterns have been identified in autism spectrum disorders (ASD), especially within salience network (SN) and between SN and default mode network (DMN) and central executive network (CEN). But whether the dynamic configuration of intra-SN and inter-SN (SN with DMN and CEN) FC in ASD is also heterogeneous remains unknown. Based on the resting-state functional magnetic resonance imaging data from 105 ASD and 102 typically-developing controls (TC), we calculated the time-varying FC of intra-SN and inter-SN (SN with DMN and CEN). Then, the joint recurrence features for the time-varying FC were calculated to assess how the SN dynamically recruits different configurations of network segregation and integration in ASD, that is, synergies, from the dynamical systems perspective. We analyzed the differences in synergetic patterns between ASD subtypes obtained by k-means clustering algorithm based on the synergy of SN and TC, and investigated the relationships between synergy of SN and severity of clinical symptoms of ASD for ASD subtypes. Two ASD subtypes were revealed, where the synergy of SN in ASD subtype 1 has lower stability and periodicity compared to the TC, and ASD subtype 2 exhibits the opposite alteration. Synergy of SN for ASD subtype 1 and 2 was found to predict the severity of communication impairments and restricted and repetitive behaviors in ASD, respectively. These results suggest the existence of subtypes with distinct patterns of the synergy of SN in ASD, and provide insight into the complex pathophysiological mechanism of clinical manifestations of ASD.

Modelling of suffusion in heterogeneous soils using discrete element method

Suffusion is one of the four mechanisms of internal erosion. The embankments and their foundations can exhibit different forms of heterogeneity which can be a major factor initiating suffusion. Although several experimental studies on the effect of heterogeneities have been performed, numerical studies remain less approached. In this paper, the effect of material heterogeneity is examined using the discrete element method and the computational fluid dynamics model (DEM-CFD). The suffusion process is studied by simulating a soils sample in a column, subjected to downward flow. Heterogeneity is addressed by adding coarse particles at two-layer positions (mid-length or downstream) at three coarse fractions (20%, 40%, 60%). Its effect is investigated in terms of erodible particles, retention efficiency, and contact forces at the particle scale. In particular, the numerical simulation results show that the erosion occurs in a heterogeneous way, and the downstream configuration provides more suffusion than the central one. In addition, the introduction of coarse particles can lead to increase the filtration efficiency. The effect of involved heterogeneities on erosion depends simultaneously on the coarse fraction and configuration heterogeneity. The comparison of the numerical results with those obtained by a suffusion test shows a concordance and validates the numerical approach.

Effects of landscape structure and land use on turtle communities across the eastern United States

Landscape context is integral to population ecology, affecting a range of life history parameters, yet very little is known about how landscape structure influences many taxa. We sampled wetlands at 531 sites across 16 states in the eastern U.S. to examine the influence of landscape heterogeneity and anthropogenic land use on the relative abundance of freshwater turtles, one of the most endangered vertebrate clades in the world. Specifically, we aimed to understand how two components of landscape structure — compositional heterogeneity (wetland diversity) and configurational heterogeneity (wetland aggregation) — influence turtles with varying life history traits. Our results suggest that wetland configuration can modulate the relationship between relative abundance and anthropogenic land use. For example, spotted turtle (Clemmys guttata) was negatively associated with hay/pasture cover when wetlands were less aggregated, but this relationship subsided as aggregation increased. Notably, the way wetland aggregation modulated land use relationships varied across species. These results suggest that some anthropogenic cover types are not strictly positive or negative for certain species, but are instead context-dependent. Relative abundance also generally increased with higher wetland diversity, indicating the potential importance of landscape supplementation for turtles. We report a range of responses to roads that did not strictly correspond with well-established predictions related to body size and terrestrial activity patterns, including positive associations for certain species. Overall, our study supports the use of context-driven approaches to land use-related conservation and management decisions rather than blanket prescriptions, and further emphasizes that effective conservation of freshwater systems requires a landscape-level perspective.

Local scale crop compositional heterogeneity suppresses the abundance of a major lepidopteran pest of cruciferous vegetables

Previous studies have recommended preserving semi-natural habitats as a strategy to promote natural enemies and reduce the abundance of agricultural pests. Such non-crop habitats, however, may increase pest abundance, causing spillover from non-crop to crop fields. A potentially more economical and attractive solution for farmers might arise if crop fields were themselves designed to aid in pest control. As part of such a strategy, we examined whether increasing crop compositional heterogeneity (i.e. the number of crop types and their evenness) and crop configurational heterogeneity (i.e. field margin length) could reduce the abundance of Pieris canidia, a major agricultural pest butterfly in several Asian countries. Adult females of P. canidia lay their eggs on cruciferous vegetables (Brassicaceae), and the emerging larvae consume the leaf tissue, causing crop damage. We surveyed adult P. canidia across 52 farmlands in south China when their abundance was at a peak in spring (April to May). Our results showed that the percentage of cruciferous crops (cabbage, oilseed rape, and pak choi) at the 100 m radius local scale was strongly positively associated with P. canidia abundance. However, crop compositional heterogeneity, also at the local scale, significantly reduced the abundance of P. canidia. Field margin type, categorized by the spatial coexistence of the most dominant cover types (sugarcane, corn, vegetables, including crucifers, and weedy vegetation), was also an important explanatory variable, with weedy patches, usually consisting of fallow cropfields adjacent to the field margins, having the highest pest abundance. These results suggest that to control pest attack by P. canidia on cruciferous vegetables, increasing crop compositional heterogeneity could be a more effective strategy than increasing configurational heterogeneity or the amount of non-crop habitat. However, research measuring crop damage by larval butterflies is necessary to confirm this hypothesis.

Length L‐function for network‐constrained point data

AbstractNetwork‐constrained points are constrained by and distributed on road networks, for example, taxi pick‐up and drop‐off locations. The aggregation pattern (clustering) of network‐constrained points (significantly denser than randomly distributed) along roads may indicate spatial anomalies. For example, detecting and quantifying the aggregation with the highest intensity (i.e., the number of taxi pick‐up points per network length) can reveal high taxi demand. The network K‐function and its derivative (incremental network K‐function) have been utilized to identify point aggregations and measure aggregation scale, yet can only identify radius‐based planar‐scale results, thereby mis‐estimating aggregation patterns owing to the network topology configuration heterogeneity. Specifically, complex road networks (e.g., intersections) may incur aggregations despite their low intensity. This study constructs the length L‐function for network‐constrained points, using its first derivative to quantify the true‐to‐life aggregation scale and the local function to extract aggregations. Synthetic and practical data experiments show innovative detection of aggregations at the length‐based scale and with high intensity, providing a new approach to point pattern analysis of networks unaffected by topological complexity.

Landscape composition and configuration relatively affect invasive pest and its associator across multiple spatial scales

Landscape structures affect pests, depending on compositional heterogeneity (the number and proportions of different habitats), configurational heterogeneity (spatial arrangement of habitats), and spatial scales. However, there is limited information on the relative effects of compositional and configurational heterogeneity on invasive pests and their associates (species that can benefit from invasive pests), and how they vary across spatial scales. In this study, we assayed the invasive pest Bactrocera dorsalis (Hendel) and its associated fly Drosophila melanogaster in 15 landscapes centered on mango orchards. We calculated landscape composition (forest percentage, mango percentage, and Shannon's diversity) and configuration (edge density) using two methods: spatial distance scales and combined scales. Spatial distance scales included buffer rings with radii of 0.5, 1.0, and 1.5 km, and combined scales referred to cutting or not cutting a smaller ring from larger ones. Our results shown that compositional heterogeneity positively affected B. dorsalis and D. melanogaster due to forest cover percentage, whereas configurational heterogeneity with high edge density negative effect on B. dorsalis. Forest cover had less of an effect on B. dorsalis than configurational heterogeneity, but the opposite effect was observed for D. melanogaster. Importantly, the direction and strength of forest cover and configurational heterogeneity to species did not vary with spatial distance scales or spatial combined scales. Thus, compositional and configurational heterogeneity exhibit differential effects on this invasive pest and its associator, and revealed that the relative effects of landscape structures are consistent across multiple scales. These results provide new insights into landscape effects on interconnected species using a diverse spatial-scale approach.

Predators do not benefit from crop diversity but respond to configurational heterogeneity in wheat and cotton fields

Predators do not benefit from crop diversity but respond to configurational heterogeneity in wheat and cotton fields

Markov manpower planning models: a review

A manpower system is a network of individuals working together in an organisation for the purpose of achieving the common goal of the organisation. To ensure that the right number of individuals is available to meet the task to be performed by the organisation, manpower planning techniques are needed. This paper reviews the manpower planning literature with specific interest on manpower systems modelled within the Markov chain context. Markov chains provide a convenient framework to analyse the structural mechanisms that underlie social change, extrapolate shifts in the state distribution of the system, control personnel structures by framing optimal promotion and recruitment strategies, evaluate personnel policies, and deal with heterogeneity and uncertainty in the system configuration. This paper surveys these applications areas and highlights the methodological issues arising from varying the unit interval of the Markov manpower system in discrete time.

DNN-based Skeleton Independent Motion Retargeting

In the modern digital world, the use of animated applications has increased significantly and such applications have quietly become an integral part of life. Capturing human motions is a fundamental aspect of these applications which is performed by motion-capturing (MoCap) systems. Due to the heterogeneity of MoCap systems and marker configurations, the captured skeletons may vary in their structure, number of joints, and bone lengths. The need for motion retargeting arises to transfer motion captured from one articulated actor to another. Although motion retargeting is a long-standing issue, current methods cannot automatically execute retargeting between skeletons.This paper presents the retraining of a popular motion retargeting network with a new large-scale motion dataset. The retraining aims to demonstrate the capabilities of the motion retargeting network to handle the problem of motion retargeting between skeletons that may have different structures. The paper first, presents the motion retargeting network that employs an encoder-decoder architecture. Afterward, we re-train the motion retargeting network with a new MoCap dataset. To validate the effectiveness of the network, we visually compare the generated results with the existing retargeting model. The results show that the motion retargeting network effectively retargets the different motions.

The Role of Orchestration in Shaping Musical Form

We introduce a method for computer-assisted analysis of orchestration. We also look into the role that texture and orchestration have in structuring musical form. The method comprises a numerical representation, a hierarchy of ‘textural situations’ and measures for heterogeneity, diversity and complexity of orchestral-textural configurations.

Urban neighbourhood classification and multi-scale heterogeneity analysis of Greater London

We study the compositional and configurational heterogeneity of Greater London at the city- and neighbourhood-scale using Geographic Information System (GIS) data. Urban morphometric indicators are calculated including plan-area indices and fractal dimensions of land cover, frontal area index of buildings, evenness, and contagion. To distinguish between city-scale heterogeneity and neighbourhood-scale heterogeneity, the study area of 720 km2 is divided into 1 [Formula: see text] 1 km2 neighbourhoods. City-scale heterogeneity is represented by categorisation of the neighbourhoods using a k-means clustering algorithm based on the morphometric indicators. This results in six neighbourhood types ranging from “greenspace” to “central business district”. Neighbourhood-scale heterogeneity is quantified using a hierarchical multi-scale analysis for each neighbourhood type. The analysis reveals the dominant length scales for land-cover and neighbourhood types and the resolutions with the most information gain. We analyse multi-scale anisotropy and show that small-scale features are homogeneous, and that anisotropy is present at larger length scales.