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Geostatistics Applications in Resources and Environment

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainability in Geographic Science".

Deadline for manuscript submissions: closed (25 June 2023) | Viewed by 1577

Special Issue Editors


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Guest Editor
College of Resources & Environment, Huazhong Agricultural University, Wuhan 430070, China
Interests: geostatiscs method and its applications

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Guest Editor
College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China
Interests: geostatiscs theory and method of spatial analysis and application in soil environment

Special Issue Information

Dear Colleagues,

Under global environmental change and sustainable development background, research has been highly concerned with resource and environmental issues. Geostatistics provides essential theories and methods to analyze the spatial distribution of geographical data. It has been extensively applied in resources and the environment because of its higher applicability and effectiveness.

In terms of its application in resources and the environment, geostatistics is mainly used to reveal some natural phenomena or spatial/spatiotemporal processes of environment properties (soil properties, air pollutants, meteorological properties, water pollutants, etc). In addition, geostatistics methods can also be combined with geographic information system (GIS) analysis and remote sensing (RS) data to explore other resource and environment problems, such as driving mechanisms of air/soil/water attributes, spatial cluster analysis of pollutants, and spatial/spatiotemporal simulation with higher accuracy.

This Special Issue will focus on geostatistics methods and their applications in resources and the environment. This Special Issue calls for research articles, reviews, and case studies at the regional and global scales, and submissions may cover but are not limited to, the following topics:

  • Innovative or improved geostatistics methods;
  • Spatial/spatiotemporal modeling of environment properties;
  • Uncertainty assessment;
  • Spatial/spatiotemporal mapping and pattern analysis;
  • Air/soil/water environment quality assessment.

This Special Issue aims to publish new ideas and improved geostatistics methods or frameworks and applications, and to expand the application of geostatistics in resources and the environment.

Prof. Dr. Yong Yang
Dr. Chutian Zhang
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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • geostatistics methods
  • geostatistics applications
  • spatial/spatiotemporal modeling
  • uncertainty assessment
  • resource and environment
  • spatial/spatiotemporal pattern analysis
  • environment assessment

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Published Papers (1 paper)

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Research

27 pages, 6885 KiB  
Article
Assessing Endokarst Potential in the Northern Sector of Santo António Plateau (Estremadura Limestone Massif, Central Portugal)
by Luís Reis, Luca Antonio Dimuccio and Lúcio Cunha
Sustainability 2023, 15(21), 15599; https://doi.org/10.3390/su152115599 - 3 Nov 2023
Cited by 1 | Viewed by 1238
Abstract
Karst is a peculiar natural landscape arising from high rock solubility and well-developed underground solutional channel porosity. It is unique for its surface relief (exokarst) and subsurface drainage, including cave systems (endokarst). In Portugal, karst areas mainly consist of marginal or low-density territories [...] Read more.
Karst is a peculiar natural landscape arising from high rock solubility and well-developed underground solutional channel porosity. It is unique for its surface relief (exokarst) and subsurface drainage, including cave systems (endokarst). In Portugal, karst areas mainly consist of marginal or low-density territories with great fragility and vulnerability and great geo-environmental richness that merits better policies and practices regarding their geo-conservation. Endokarst potential assessments can provide decision-makers and local authorities insight into present and future territorial management and planning. In this context, the main objective of this study was to produce a cartographic model to identify areas with a greater probability of containing karstic caves—i.e., a greater endokarst potential—in the northern sector of the Santo António Plateau (Estremadura Limestone Massif, Central Portugal). Geological, topographic, hydrogeological, and land cover data were collected, processed, and integrated into a spatial database using a Geographic Information System. The locations of known cave entrances in the study area were also identified from local public institutions and speleological team records. Subsequently, four conditioning factors were extracted from the data: lithostratigraphic units, fracture density, relief energy, and land cover. Using a multi-criteria decision-making analysis, each previously chosen conditioning factor and its respective classes were weighted using an analytic hierarchy process. The locations of known cave entrances served to evaluate the cartographic model built, with results showing an agreement of 81.9%. This prototype of the endokarst potential map for the study area may be used for strategic and operational environmental planning (at least on a local scale) to assist decision-makers, competent authorities, and local speleological teams. Its application may promote a more accurate and thoughtful definition of areas to be investigated, substantially reducing the time and costs associated with field prospecting. Full article
(This article belongs to the Special Issue Geostatistics Applications in Resources and Environment)
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