scholarly journals Prediction and Selection of Appropriate Landscape Metrics and Optimal Scale Ranges Based on Multi-Scale Interaction Analysis

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1192
Author(s):  
Gang Fu ◽  
Wei Wang ◽  
Junsheng Li ◽  
Nengwen Xiao ◽  
Yue Qi
Keyword(s):  
Land Use ◽  
Spatial Resolution ◽  
Landscape Metrics ◽  
Landscape Planning ◽  
Interaction Analysis ◽  
Multivariate Adaptive Regression Splines ◽  
Scaling Effects ◽  
Scale Interaction ◽  
Multi Scale ◽  
Optimal Scale

Landscape metrics are widely used in landscape planning and land use management. Understanding how landscape metrics respond with scales can provide more accurate prediction information; however, ignoring the interference of multi-scale interaction may lead to a severe systemic bias. In this study, we quantitatively analyzed the scaling sensitivity of metrics based on multi-scale interaction and predict their optimal scale ranges. Using a big data method, the multivariate adaptive regression splines model (MARS), and the partial dependence model (PHP), we studied the scaling relationships of metrics to changing scales. The results show that multi-scale interaction commonly exists in most landscape metric scaling responses, making a significant contribution. In general, the scaling effects of the three scales (i.e., spatial extent, spatial resolution, and classification of land use) are often in a different direction, and spatial resolution is the primary driving scale in isolation. The findings show that only a few metrics are highly sensitive to the three scales throughout the whole scale spectrum, while the other metrics are limited within a certain threshold range. This study confirms that the scaling-sensitive scalograms can be used as an application guideline for selecting appropriate landscape metrics and optimal scale ranges.

scholarly journals Evaluating the Potential of Landscape Metrics in Supporting Landscape Planning in Atlantic Forest

2013 ◽  
Vol 4 (1) ◽  
pp. 55-67 ◽  
Author(s):  
Ana Paula Dias Turetta ◽  
Rachel Bardy Prado ◽  
Gustavo de Souza Valladares
Keyword(s):  
Land Use ◽  
Landscape Metrics ◽  
Landscape Structure ◽  
Landscape Planning ◽  
Principal Component ◽  
Agricultural Landscapes ◽  
Southeastern Brazil ◽  
Forest Patches ◽  
Dominant Component ◽  
A Site

The landscapes are highly dependent on the dynamics of local land use and land cover, which directly affects landscape structure and determines the spatial patterns of forest patches, as well as to the major land uses within a specific region. The calculation of landscape metrics can support the understanding of such spatial distribution. In this study, 16 landscape metrics were analyzed in a drainage watershed in a high relief region in the Rio de Janeiro state, Southeastern Brazil, with the aim to evaluate the use of landscape metrics as indicators for agricultural management. Metrics calculation was followed by a Principal Component Analysis, which indicated the metrics that were most effective in evidencing the landscape structure in analysis. The results showed that the late-succession forest is the dominant component in the landscape. This class also presented the highest MPS metric value, related to the mean patch size by class. Some PCA results suggest that the metrics association was less effective in clustering the overgrown pasture, clean pasture, and annual crops classes, but this could result from the intrinsic association among those classes, by crop rotation, meaning the abandon of a site formerly occupied by an annual crop. Some metrics better suggested an interaction among land use classes and have potential to be use in the analyses of agricultural landscapes in high relief sites.

scholarly journals Identification of Marginal Landscapes as Support for Sustainable Development: GIS-Based Analysis and Landscape Metrics Assessment in Southern Italy Areas

2020 ◽  
Vol 12 (13) ◽  
pp. 5400 ◽  
Author(s):  
Elena Cervelli ◽  
Ester Scotto di Perta ◽  
Stefania Pindozzi
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Landscape Metrics ◽  
Landscape Planning ◽  
Land Use Changes ◽  
Multicriteria Analysis ◽  
Marginal Lands ◽  
Landscape Governance ◽  
Current Asset ◽  
Strategic Role

Landscape is increasingly characterized by a multifaced nature. In scientific literature and landscape governance, new landscape definitions are often coined to explain new meanings and to define specific intervention strategies and tools. The present study purposes a framework for the identification of hybrid landscapes as support for land-use planners, which aim to guarantee development opportunities as well as natural heritage preservation and valorization. “Marginal lands” were identified starting from EU Directives and scientific approaches, by means of multicriteria analysis. Different scenarios were built: (1) no-change; (2) energy crops; (3) green infrastructures. An ecosystem services approach, via landscape metrics analysis, was used to compare the possible effects of scenarios. About 20% of the study area, an internal area of the southern Apennines, was identified as suitable for land-use change in a medium-short time, and scenarios of land-use changes show a better condition, in terms of fragmentation, than as a current asset. Results showed the strategic role and potentialities of marginal lands, as a trade-off between nature conservation and development issues, suggesting new opportunities for green infrastructures and a renewable energies chain. The study allowed for deepening the close connection among landscape planning approaches, land use change scenarios building and environmental assessment, focused on the ex-ante evaluation stage.

Multi-scale interaction of pedestal instabilities in H-mode plasma on the EAST tokamak

2019 ◽  
Vol 59 (5) ◽  
pp. 056020 ◽  
Author(s):  
T. Zhang ◽  
K.N. Geng ◽  
H.Q. Liu ◽  
Y. Liu ◽  
T.H. Shi ◽  
...  
Keyword(s):  
Scale Interaction ◽  
Multi Scale

scholarly journals The Winter Habitat Selection of Red Deer (Cervus elaphus) Based on a Multi-Scale Model

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2454
Author(s):  
Yue Sun ◽  
Yanze Yu ◽  
Jinhao Guo ◽  
Minghai Zhang
Keyword(s):  
Habitat Selection ◽  
Environmental Factors ◽  
Cervus Elaphus ◽  
Red Deer ◽  
Scale Model ◽  
Winter Habitat ◽  
Multi Scale ◽  
Optimal Scale ◽  
Scale Models ◽  
Selection Of

Single-scale frameworks are often used to analyze the habitat selections of species. Research on habitat selection can be significantly improved using multi-scale models that enable greater in-depth analyses of the scale dependence between species and specific environmental factors. In this study, the winter habitat selection of red deer in the Gogostaihanwula Nature Reserve, Inner Mongolia, was studied using a multi-scale model. Each selected covariate was included in multi-scale models at their “characteristic scale”, and we used an all subsets approach and model selection framework to assess habitat selection. The results showed that: (1) Univariate logistic regression analysis showed that the response scale of red deer to environmental factors was different among different covariate. The optimal scale of the single covariate was 800–3200 m, slope (SLP), altitude (ELE), and ratio of deciduous broad-leaved forests were 800 m in large scale, except that the farmland ratio was 200 m in fine scale. The optimal scale of road density and grassland ratio is both 1600 m, and the optimal scale of net forest production capacity is 3200 m; (2) distance to forest edges, distance to cement roads, distance to villages, altitude, distance to all road, and slope of the region were the most important factors affecting winter habitat selection. The outcomes of this study indicate that future studies on the effectiveness of habitat selections will benefit from multi-scale models. In addition to increasing interpretive and predictive capabilities, multi-scale habitat selection models enhance our understanding of how species respond to their environments and contribute to the formulation of effective conservation and management strategies for ungulata.

Refinement and Scaling Effects on Peridynamic Numerical Solutions

2016 ◽  
Author(s):  
Daniele Dipasquale ◽  
Erkan Oterkus ◽  
Giulia Sarego ◽  
Mirco Zaccariotto ◽  
Ugo Galvanetto
Keyword(s):  
Numerical Solutions ◽  
Whole Body ◽  
Grid Refinement ◽  
Scaling Effects ◽  
Linear Elasticity Theory ◽  
Multi Scale ◽  
Promising Strategy ◽  
Adaptive Grid Refinement ◽  
Unique Framework ◽  
Computational Resources

One of the most common methods to implement peridynamics numerically is based on the discretization of the whole body by means of a structured and regular grid of nodes and a constant horizon size. That leads to an inefficient use of computational resources as well as to the impossibility to explore the multi-scale capabilities of peridynamics within a unique framework. Adaptive grid refinement and scaling seem to be a promising strategy to reduce those limitations, allowing to increase the resolution of the analysis and to reach the interested length-scale only in the desired regions. The application of such an approach in the peridynamic solutions requires certainly to be investigated, in particular, this is done by the comparison of numerical peridynamic solutions with the analytical solutions of classic linear elasticity theory.

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