Submit to Land Review for Land Propose a Special Issue

Journal Browser

► Journal Browser

Multiscale Geospatial Approaches for Landscape Ecology

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Landscape Ecology".

Deadline for manuscript submissions: closed (15 May 2022) | Viewed by 15840

Share This Special Issue

Special Issue Editors

Prof. Dr. Wayne Myers

E-Mail Website
Guest Editor

Department of Ecosystem Science and Management, Pennsylvania State University, State College, PA 16801, USA
Interests: spatial analysis; landscape ecology; conservation; geoinformatics for human-environment interface; multivariate analysis; environmental modelling; sustainable natural resource management; forestry

Dr. Kristen Brubaker

E-Mail Website
Guest Editor

Department of Environmental Studies, Hobart and William Smith Colleges, Geneva, NY 14456, USA
Interests: forest ecology; remote sensing; critical zone science

Special Issue Information

Dear Colleagues,

Spatial specifications of components and conditions have become essential endeavors in landscape ecological investigations, conservation, and stewardship, as have multiple metrics of mosaics. Current challenges extend to the synthesis of spatial structures and disturbance dynamics across a spectrum of scales for cognizance of context in climate change, exotic epidemics, and regional resilience. The term “multiscale” serves here as a euphemistic reference to the scope and stability of a spatial structure, and emphasis lies on the tactics and technology for tracking transference from site to landscape, landscape to locality, locality to vicinity, and reaching to regions over temporal trajectories. Derivatives of one data domain must be entered into ancillary data domains having a different spatial and/or temporal resolution, thematic purview, and software support. Scripting systems often offer perhaps partial platforms for such loose linkage. Each instance involves innovations while yielding insights on practical protocols. Spatial dependencies, anisotropies, and discontinuities along with temporal trends become key considerations, whereas were previously treated more as somewhat esoteric inferential excursions.

Submissions sharing thematic threads will provide additional organizing opportunities. One such thread is the ecology of human interactions with landscape elements whereby site-specific data are collected by various authorities and/or interests that require assembly and integration to obtain sub-regional views. Another is multiple monitoring emplacements under the aegis of different operatives, involving data streams from automated sensors and/or scheduled visitation. Still another is the allocation of plots/points/etc. for special augmentation of coarse resolution data, perhaps to support spatial modeling of habitats or eco-economic aspects of impacts and opportunities where the modeling entails varying degrees of statistical sophistication regarding data dependencies.

Prof. Dr. Wayne Myers
Dr. Kristen Brubaker
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Landscape ecology
Multiscale spatial analysis
Geoinformatics
Environmental modeling
Conservation
Environmental monitoring

Published Papers (6 papers)

Download All Papers

Research

19 pages, 6993 KiB

Open AccessArticle

The Effect of the Human Footprint and Climate Change on Landscape Ecological Risks: A Case Study of the Loess Plateau, China

by Zhi Qu, Yonghua Zhao, Manya Luo, Lei Han, Shuyuan Yang and Lei Zhang

Land 2022, 11(2), 217; https://0-doi-org.brum.beds.ac.uk/10.3390/land11020217 - 30 Jan 2022

Cited by 15 | Viewed by 3011

Abstract

The increase in ecological risks caused by human activities has become a global concern in recent years. The Landscape Ecological Risk Index based on the theory of landscape ecology is more suitable for assessing large-scale ecological risks. Assessing landscape ecological risks and the mechanisms by which humans directly or indirectly affect them will help to manage and control the regions’ ecological risks through scientific and policy methods. In this study, a new model of landscape ecological risk assessment based on the moving window method is proposed. The Loess Plateau of China is used as an example, and the Human Footprint Index dataset of the Loess Plateau is constructed. Different human footprint factors and climate factors are applied, and the human direct and indirect effects on the landscape ecological risks of the Loess Plateau are explored based on the geographical detector model. The results show that, in 2000, 2010 and 2020, the landscape ecological risks of the Loess Plateau are currently in an unstable state, and the highest value area of the Landscape Ecological Risk Index continues to expand, with values of 113,566.1553 km², 114,575.6772 km² and 120,718.5363 km², respectively. Among all the human footprint factors, the population density factor has the highest effect on the landscape ecological risks of the Loess Plateau. Among the climate factors, both the average temperature factor and the average lagged temperature factor have significant effects on the landscape ecological risks of the Loess Plateau. With the interaction of any two human footprint factors and climate factors, the effect of these factors on the landscape ecological risks of the Loess Plateau is enhanced. Full article

(This article belongs to the Special Issue Multiscale Geospatial Approaches for Landscape Ecology)

► Show Figures

Figure 1

15 pages, 31152 KiB

Open AccessArticle

Detectability of the Critically Endangered Araucaria angustifolia Tree Using Worldview-2 Images, Google Earth Engine and UAV-LiDAR

by Felipe Saad, Sumalika Biswas, Qiongyu Huang, Ana Paula Dalla Corte, Márcio Coraiola, Sarah Macey, Marcos Bergmann Carlucci and Peter Leimgruber

Land 2021, 10(12), 1316; https://0-doi-org.brum.beds.ac.uk/10.3390/land10121316 - 30 Nov 2021

Cited by 2 | Viewed by 2040

Abstract

The Brazilian Atlantic Forest is a global biodiversity hotspot and has been extensively mapped using satellite remote sensing. However, past mapping focused on overall forest cover without consideration of keystone plant resources such as Araucaria angustifolia. A. angustifolia is a critically endangered coniferous tree that is essential for supporting overall biodiversity in the Atlantic Forest. A. angustifolia’s distribution has declined dramatically because of overexploitation and land-use changes. Accurate detection and rapid assessments of the distribution and abundance of this species are urgently needed. We compared two approaches for mapping Araucaria angustifolia across two scales (stand vs. individual tree) at three study sites in Brazil. The first approach used Worldview-2 images and Random Forest in Google Earth Engine to detect A. angustifolia at the stand level, with an accuracy of >90% across all three study sites. The second approach relied on object identification using UAV-LiDAR and successfully mapped individual trees (producer’s/user’s accuracy = 94%/64%) at one study site. Both approaches can be employed in tandem to map remaining stands and to determine the exact location of A. angustifolia trees. Each approach has its own strengths and weaknesses, and we discuss their adoptability by managers to inform conservation of A. angustifolia. Full article

(This article belongs to the Special Issue Multiscale Geospatial Approaches for Landscape Ecology)

► Show Figures

Figure 1

25 pages, 2666 KiB

Open AccessArticle

Scalable Shared Scripting for Spatial Structure of Regionalized Ratings

by Wayne L. Myers

Land 2021, 10(8), 859; https://0-doi-org.brum.beds.ac.uk/10.3390/land10080859 - 16 Aug 2021

Viewed by 1736

Abstract

Incisive inquiry involving indicators of ecological and environmental integrity entails exploration of spatial structure at selected scales from landscape level to regional regimes. Conventional colorization of digital displays provides perspective but is largely lacking for localization, elaboration, and explication. An overall objective for recent research is explicit extraction of spatial structure as hyper-hills and proximal propensity. Shared scripting as a computational configuration affords analytical advantage, adaptability and availability. Conservation context captures challenges of changing conditions for complex components at several spatial scales. Hyper-hill hypotheses, relativized ratings, and post patterned nucleated networks supporting secondary scaling scenarios are current contributions. Computational concerns in indicant informatics are also addressed. Retrospective results are cogent comparators for change. Shared scripting couples R software with Python as R||Python (R in parallel with Python), which is supplemented by strategic sequencing of compilation capabilities in general GIS (geographic information systems). The specific research question(s) is/are what is the particular pattern of placement and propagation in intensification of an indicant of biodiversity (avian species richness), and how does this relate to some other co-located indicants of environmental effects. This is addressed in a legacy dataset for Pennsylvania, USA. Emergent emphasis is on truncated trees of topology and impaneled indicators. Shareable software has HIDN (hexagonal indicant dual networking) as an aggregate acronym with duly drawn disclaimers. Full article

(This article belongs to the Special Issue Multiscale Geospatial Approaches for Landscape Ecology)

► Show Figures

Figure 1

17 pages, 2617 KiB

Open AccessArticle

Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types

by Yonghua Zhao, Li Liu, Shuaizhi Kang, Yong Ao, Lei Han and Chaoqun Ma

Land 2021, 10(6), 604; https://0-doi-org.brum.beds.ac.uk/10.3390/land10060604 - 06 Jun 2021

Cited by 27 | Viewed by 2911

Abstract

The Loess Plateau of China suffers from severe erosion, which results in a great variety of economic and ecological problems. For scientific control of soil erosion, the key questions urgently to be addressed in this paper are: (1) Which are the driving factors under diverse geomorphological types? (2) Do these driving factors operate independently or by interacting? (3) Which zones under diverse geomorphological types suffer from severe erosion and need more attention? In this paper, the RUSLE model was applied here to demonstrate the spatio-temporal variations in soil erosion from 2010 to 2017 in Yan’an City, and the Geo-detector model proved to be a useful tool to solve the questions mentioned above. The results showed that the average erosion modulus in Yan’an City decreased by 1927.36 t/km²·a from 2010 to 2017. The intensity of soil erosion in the northern Baota District, central Ganquan County, Luochuan County, Ansai County, and Zhidan County decreased to varying degrees. The effect size of driving factors affecting soil erosion varied significantly in diverse geomorphological types. The effect size of interaction between land-use types and vegetation coverage, land-use types and slope, slope and precipitation was higher than that of a single factor. High-risk zones with severe erosion were closer to cultivated land and forest land with steep slopes (>25°) in the mid-elevation hills of Yan’an City. Additionally, based on the specificity of the study area, the Geo-detector model performed better in a relatively flat region, and factors with macroscopic spatial distributions weaken its explanatory power on soil erosion on a regional scale. Based on data selection, data of different accuracy sparked the issue of “data coupling”, which led to the enormous deviation of model results in mid-elevation plains. Results from our analysis provide insights for a more ecologically sound development of Yan’an City and provide references for the scientific use of the Geo-detector model. Full article

(This article belongs to the Special Issue Multiscale Geospatial Approaches for Landscape Ecology)

► Show Figures

Figure 1

21 pages, 6145 KiB

Open AccessArticle

Fully Portraying Patch Area Scaling with Resolution: An Analytics and Descriptive Statistics-Combined Approach

by Qianning Zhang and Zhu Xu

Land 2021, 10(3), 262; https://0-doi-org.brum.beds.ac.uk/10.3390/land10030262 - 05 Mar 2021

Cited by 2 | Viewed by 1513

Abstract

Scale effects are inherent in spatial analysis. Quantitative knowledge about them is necessary for properly interpreting and scaling analysis results. The objective of this study was to systematically model patch area scaling and the associated uncertainty. A hybrid approach was taken to tackle the difficulty involved. Recognizing that patch’s size and shape play the key role in shaping its scaling behavior, a function model of patch area scaling based on patch morphology was first conceptually formulated. It was then substantiated by sampling and interpolating in the scale-integrated domain of patch morphology, which is characterized by a one-dimensional size index, namely the relative support range (RSR), and a compactness index, namely filling. The area scaling model obtained unveils a simple consistent scaling pattern of all patches and an overall fading range between 0.12 and 3.16 in terms of RSR. The uncertainty model built exhibits a filling-dependent pattern of the variance of patch area, which can be as large as 0.67 (i.e., 67%) in terms of standard deviation. The models were validated by using them to predict patch and class area scaling of the test patches and landscapes. This study demonstrated the basic feasibility of analytically modeling scaling behavior. It also revealed the uncertainty of scale effects is very significant due to the inevitable randomness in rasterization. Full article

(This article belongs to the Special Issue Multiscale Geospatial Approaches for Landscape Ecology)

► Show Figures

Figure 1

16 pages, 2050 KiB

Open AccessArticle

Tropical PeatLand Forest Biomass Estimation Using Polarimetric Parameters Extracted from RadarSAT-2 Images

by Mirza Muhammad Waqar, Rahmi Sukmawati, Yaqi Ji and Josaphat Tetuko Sri Sumantyo

Land 2020, 9(6), 193; https://0-doi-org.brum.beds.ac.uk/10.3390/land9060193 - 10 Jun 2020

Cited by 9 | Viewed by 3464

Abstract

This paper was aimed at estimating the forest aboveground biomass (AGB) in the Central Kalimantan tropical peatland forest, Indonesia, using polarimetric parameters extracted from RadarSAT-2 images. Six consecutive acquisitions of RadarSAT-2 full polarimetric data were acquired and polarimetric parameters were extracted. The backscattering [...] Read more.

σ_{o}

) for HH, HV, VH, and VV channels was computed respectively. Entropy (H) and alpha (

α

) were computed using eign decomposition. In order to understand the scattering behavior, Yamaguchi decomposition was performed to estimate surface scattering (

γ_{s u r f}

) and volume scattering (

γ_{v o l}

) components. Similarly following polarimetric indices were computed; Biomass Index (BMI), Canopy Structure Index (CSI), Volume Scattering Index (VSI), Radar Vegetation Index (RVI) and Pedestal Height (

p_{h}

). The PolSAR parameters were evaluated in terms of their temporal consistency, inter-dependence, and suitability for forest aboveground biomass estimation across rainy and dry conditions. Regression analysis was performed between referenced biomass measurements and polarimetric parameters; VSI, H, RVI,

p_{h}

, and

γ_{v o l}

were found significantly correlated with AGB. Biomass estimation was carried out using significant models. Resultant models were validated using field-based AGB measurements. Validation results show a significant correlation between measured and referenced biomass measurements with temporal consistency over the acquisition time period. Full article

(This article belongs to the Special Issue Multiscale Geospatial Approaches for Landscape Ecology)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Multiscale Geospatial Approaches for Landscape Ecology

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (6 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI