Spatial Analysis for Landscape Changes

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: closed (15 September 2021) | Viewed by 12754

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Consiglio Nazionale delle Ricerche—Istituto di Scienze del Patrimonio Culturale (ISPC), Tito Scalo, Potenza, Italy
Interests: tectonic geomorphology; landscape evolution; drainage network morphometry; geomorphological mapping; sediment yield; landslide analysis; geoarchaeology
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Institute of Heritage Science, National Research Council (ISPC CNR), I-85050 Tito, Potenza, Italy
Interests: GIS; geocomputation; remote sensing; geophysics; cultural heritage; landscape archaeology
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Special Issue Information

Dear Colleagues,

Landscape is the backcloth over which environmental and cultural events occur, with changes to the landscape itself also involved. At the same time, the last few years have also seen a great improvement in the availability of high-resolution DEMs, GIS tools and of landscape data in general. This has promoted the development and application of spatial analyses (from map algebra to geostatistics, from machine learning to location-based cellular automata) for the quantitative evaluation of landscape changes in many geomorphological, territorial and archaeological applications. This Special Issue aims to collect contributions concerning the application of traditional and innovative methods in all application fields that are connected to these changes, such as geomorphology, urban and territorial systems and archaeology. We would like to invite you to submit articles about your recent work, experimental research or case studies dealing with the quantitative analysis of landscape changes in a variety of application fields and at different spatial and temporal scales. Relevant topics for the SI include:

  1. Multitemporal analysis of DEMs and reconstruction of short- and long-term topographic changes;
  2. Extraction of parameters and indexes to investigate landscape changes and related surface processes;
  3. Two- and three-dimensional reconstructions of historical and archaeological landscapes;
  4. Semi-automatic or unsupervised classification of landforms/landscapes;
  5. Application of quantitative methods and models to estimate landscape modification and their impact on urban systems;
  6. Analysis of geomorphic processes and rates by the multitemporal acquisition of high-resolution topographic data and spatial statistics;
  7. GIS tools and spatial statistics for the analysis of natural hazards and human impact on the landscape.

Review articles about the limitations, recent developments and new approaches of this research field are also welcomed.

Dr. Dario Gioia
Dr. Maria Danese
Guest Editors

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Keywords

spatial analysis; high-resolution DEMs; landscape archaeology; landscape evolution model (LEM); past landscape reconstruction; soil consumption; geomorphological processes; natural hazard

Published Papers (7 papers)

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Editorial

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2 pages, 164 KiB  
Editorial
Spatial Analysis for Landscape Changes
by Dario Gioia and Maria Danese
Appl. Sci. 2021, 11(24), 11924; https://doi.org/10.3390/app112411924 - 15 Dec 2021
Viewed by 876
Abstract
Landscape is the backcloth over which environmental and anthropic events occur, and recent increasing trends of natural and anthropic processes, such as urbanization, land-use changes, and extreme climate events, have a strong impact on landscape modification [...] Full article
(This article belongs to the Special Issue Spatial Analysis for Landscape Changes)

Research

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21 pages, 8800 KiB  
Article
Superpixel-Based Singular Spectrum Analysis for Effective Spatial-Spectral Feature Extraction
by Subhashree Subudhi, Ramnarayan Patro , Pradyut Kumar Biswal and Fabio Dell’Acqua
Appl. Sci. 2021, 11(22), 10876; https://doi.org/10.3390/app112210876 - 17 Nov 2021
Cited by 4 | Viewed by 1276
Abstract
In the processing of remotely sensed data, classification may be preceded by feature extraction, which helps in making the most informative parts of the data emerge. Effective feature extraction may boost the efficiency and accuracy of the following classification, and hence various methods [...] Read more.
In the processing of remotely sensed data, classification may be preceded by feature extraction, which helps in making the most informative parts of the data emerge. Effective feature extraction may boost the efficiency and accuracy of the following classification, and hence various methods have been proposed to perform it. Recently, Singular Spectrum Analysis (SSA) and its 2-D variation (2D-SSA) have emerged as popular, cutting-edge technologies for effective feature extraction in Hyperspectral Images (HSI). Using 2D-SSA, each band image of an HSI is initially decomposed into various components, and then the image is reconstructed using the most significant eigen-tuples relative to their eigen-values, which represent strong spatial features for the classification task. However, instead of performing reconstruction on the whole image, it may be more effective to apply reconstruction to object-specific spatial regions, which is the proposed objective of this research. As an HSI may cover a large area, multiple objects are generally present within a single scene. Hence, spatial information can be highlighted accurately by specializing the reconstruction based on the local context. The local context may be defined by the so-called superpixels, i.e., finite sets of pixels that constitute a homogeneous set. Each superpixel may undergo tailored reconstruction, with a process expected to perform better than non-spatially-adaptive approaches. In this paper, a Superpixel-based SSA (SP-SSA) method is proposed where the image is first segmented into multiple regions using a superpixel segmentation approach. Next, each segment is individually reconstructed using 2D-SSA. In doing so, the spatial contextual information is preserved, leading to better classifier performance. The performance of the reconstructed features is evaluated using an SVM classifier. Experiments on four popular benchmark datasets reveal that, in terms of the classification accuracy, the proposed approach overperforms the standard SSA technique and various common spatio-spectral classification methods. Full article
(This article belongs to the Special Issue Spatial Analysis for Landscape Changes)
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19 pages, 7809 KiB  
Article
Comparison of Satellite and Drone-Based Images at Two Spatial Scales to Evaluate Vegetation Regeneration after Post-Fire Treatments in a Mediterranean Forest
by Jose Luis Martinez, Manuel Esteban Lucas-Borja, Pedro Antonio Plaza-Alvarez, Pietro Denisi, Miguel Angel Moreno, David Hernández, Javier González-Romero and Demetrio Antonio Zema
Appl. Sci. 2021, 11(12), 5423; https://doi.org/10.3390/app11125423 - 10 Jun 2021
Cited by 14 | Viewed by 2582
Abstract
The evaluation of vegetation cover after post-fire treatments of burned lands is important for forest managers to restore soil quality and plant biodiversity in burned ecosystems. Unfortunately, this evaluation may be time consuming and expensive, requiring much fieldwork for surveys. The use of [...] Read more.
The evaluation of vegetation cover after post-fire treatments of burned lands is important for forest managers to restore soil quality and plant biodiversity in burned ecosystems. Unfortunately, this evaluation may be time consuming and expensive, requiring much fieldwork for surveys. The use of remote sensing, which makes these evaluation activities quicker and easier, have rarely been carried out in the Mediterranean forests, subjected to wildfire and post-fire stabilization techniques. To fill this gap, this study evaluates the feasibility of satellite (using LANDSAT8 images) and drone surveys to evaluate changes in vegetation cover and composition after wildfire and two hillslope stabilization treatments (log erosion barriers, LEBs, and contour-felled log debris, CFDs) in a forest of Central Eastern Spain. Surveys by drone were able to detect the variability of vegetation cover among burned and unburned areas through the Visible Atmospherically Resistant Index (VARI), but gave unrealistic results when the effectiveness of a post-fire treatment must be evaluated. LANDSAT8 images may be instead misleading to evaluate the changes in land cover after wildfire and post-fire treatments, due to the lack of correlation between VARI and vegetation cover. The spatial analysis has shown that: (i) the post-fire restoration strategy of landscape managers that have prioritized steeper slopes for treatments was successful; (ii) vegetation growth, at least in the experimental conditions, played a limited influence on soil surface conditions, since no significant increases in terrain roughness were detected in treated areas. Full article
(This article belongs to the Special Issue Spatial Analysis for Landscape Changes)
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19 pages, 5196 KiB  
Article
Modeling Short-Term Landscape Modification and Sedimentary Budget Induced by Dam Removal: Insights from LEM Application
by Dario Gioia and Marcello Schiattarella
Appl. Sci. 2020, 10(21), 7697; https://doi.org/10.3390/app10217697 - 30 Oct 2020
Cited by 9 | Viewed by 1853
Abstract
Simulation scenarios of sediment flux variation and topographic changes due to dam removal have been investigated in a reservoir catchment of the axial zone of southern Italy through the application of a landscape evolution model (i.e.,: the Caesar–Lisflood landscape evolution models, LEM). LEM [...] Read more.
Simulation scenarios of sediment flux variation and topographic changes due to dam removal have been investigated in a reservoir catchment of the axial zone of southern Italy through the application of a landscape evolution model (i.e.,: the Caesar–Lisflood landscape evolution models, LEM). LEM simulation highlights that the abrupt change in base level due to dam removal induces a significant increase in erosion ability of main channels and a strong incision of the reservoir infill. Analysis of the sediment dynamics resulting from the dam removal highlights a significant increase of the total eroded volumes in the post dam scenario of a factor higher than 4. Model results also predict a strong modification of the longitudinal profile of main channels, which promoted fluvial incision upstream and downstream of the former reservoir area. Such a geomorphic response is in agreement with previous analysis of the fluvial system short-term response induced by base-level lowering, thus demonstrating the reliability of LEM-based analysis for solving open problems in applied geomorphology such as perturbations and short-term landscape modification natural processes or human impact. Full article
(This article belongs to the Special Issue Spatial Analysis for Landscape Changes)
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16 pages, 9999 KiB  
Article
Analysis of the Use of Geomorphic Elements Mapping to Characterize Subaqueous Bedforms Using Multibeam Bathymetric Data in River System
by Ge Yan, Heqin Cheng, Lizhi Teng, Wei Xu, Yuehua Jiang, Guoqiang Yang and Quanping Zhou
Appl. Sci. 2020, 10(21), 7692; https://doi.org/10.3390/app10217692 - 30 Oct 2020
Cited by 5 | Viewed by 1843
Abstract
Riverbed micro-topographical features, such as crest and trough, flat bed, and scour pit, indicate the evolution of fluvial geomorphology, and have an influence on the stability of underwater structures and overall scour pits. Previous studies on bedform feature extraction have focused mainly on [...] Read more.
Riverbed micro-topographical features, such as crest and trough, flat bed, and scour pit, indicate the evolution of fluvial geomorphology, and have an influence on the stability of underwater structures and overall scour pits. Previous studies on bedform feature extraction have focused mainly on the rhythmic bed surface morphology and have extracted crest and trough, while flat bed and scour pit have been ignored. In this study, to extend the feature description of riverbeds, geomorphic elements mapping was used by employing three geomorphic element classification methods: Wood’s criteria, a self-organization map (SOM) technique, and geomorphons. The results showed that geomorphic element mapping can be controlled by adjusting the slope tolerance and curvature tolerance of Wood’s criteria, using the map unit number and combination of the SOM technique and the flatness of geomorphons. Relatively flat bed can be presented using “plane”, “flat planar”, and “flat” elements, while scour pit can be presented using a “pit” element. A comparison of the difference between parameter settings for landforms and bedforms showed that SOM using 8 or 10 map units is applicable for land and underwater surface and is thus preferentially recommended for use. Furthermore, the use of geomorphons is recommended as the optimal method for characterizing bedform features because it provides a simple element map in the absence of area loss. Full article
(This article belongs to the Special Issue Spatial Analysis for Landscape Changes)
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17 pages, 6906 KiB  
Article
Characterization of Evolution Stages, Groundwater and Soil Features of the Mud Forest Landscape at Qian-an (China)
by XiangJian Rui, Lei Nie, Yan Xu, Chao Du, FanSheng Kong, Tao Zhang, YuanYuan He and YuZheng Wang
Appl. Sci. 2020, 10(21), 7427; https://doi.org/10.3390/app10217427 - 22 Oct 2020
Cited by 1 | Viewed by 1752
Abstract
The research on geological landscape has received more and more attention worldwide. The National Geological Park of Qian-an mud forest, located in Qian-an Country, Songyuan City (Jilin Province, China) is a rare natural geological landscape formed by erosion. Mud forest landscape has undergone [...] Read more.
The research on geological landscape has received more and more attention worldwide. The National Geological Park of Qian-an mud forest, located in Qian-an Country, Songyuan City (Jilin Province, China) is a rare natural geological landscape formed by erosion. Mud forest landscape has undergone long-term geological processes, and it is still in continuous evolution due to subsurface erosion. In the process of the mud forest landscape formation and evolution, distinct stages have been recognized. The subsurface erosion factors of the mud forest area were identified by groundwater and soil samples characterization, and the mechanism of the formation of the mud forest is studied. Results show that the occurrence of subsurface erosion is controlled by four factors: (1) The head difference of terrace increases due to geological structure, (2) The dry and cold paleoclimate increases the accumulation of soluble salts. Concentrated precipitation in the short term also promotes subsurface erosion. (3) The high content of sodium ions in groundwater promotes the dispersion of soil, and (4) Loess-like soil is characterized by high porosity, low plasticity, and dispersibility. Full article
(This article belongs to the Special Issue Spatial Analysis for Landscape Changes)
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Review

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13 pages, 3749 KiB  
Review
Spatial Analysis for Landscape Changes: A Bibliometric Review
by Maria Danese and Dario Gioia
Appl. Sci. 2021, 11(21), 10078; https://doi.org/10.3390/app112110078 - 27 Oct 2021
Cited by 2 | Viewed by 1701
Abstract
The main aim of this study is to analyze from a bibliometric point of view the research trend in spatial analysis for landscape changes using the records published in the Web of Science database in the last twenty years. Several parameters such as [...] Read more.
The main aim of this study is to analyze from a bibliometric point of view the research trend in spatial analysis for landscape changes using the records published in the Web of Science database in the last twenty years. Several parameters such as documents published per year, sources of documents, number of citations as well as VOSviewer software and GIS are used for the analysis of different metrics such as the number of citations, co-authorship network, and keyword occurrences. Analysis of the number of papers, their keywords, and authorships countries shows the research trend in the specific topics of the spatial analysis for landscape changes and consequently can constitute a benchmark for researchers who approach this research topic. Full article
(This article belongs to the Special Issue Spatial Analysis for Landscape Changes)
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