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Land
Special Issues
Geospatial Data in Land Suitability Assessment: 2nd Edition
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Geospatial Data in Land Suitability Assessment: 2nd Edition

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land Systems and Global Change".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 1902

Special Issue Editors

Dr. Ivan Plaščak

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Guest Editor
Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia
Interests: GIS; precision agriculture; variable rate technology; multicriteria decision making; farming and cropping systems; agricultural land management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Mladen Jurišić

E-Mail Website
Guest Editor
Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia
Interests: crop production; GIS; multicriteria decision making; inventarization of natural resources; agroecosystems and the environment; farming and cropping systems
Special Issues, Collections and Topics in MDPI journals
Dr. Dorijan Radočaj

E-Mail Website
Guest Editor
Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia
Interests: cropland suitability; land suitability; remote sensing; GIS; predictive mapping; digital soil mapping; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce a Special Issue of Land, entitled “Geospatial Data in Land Suitability Assessment: 2nd Edition”.

The need for improved spatial approaches and models has increased along with the need for effective and ecologically responsible land-use management. Even if multicriteria analysis techniques lead to excellent management and marketing outcomes, the integration of geographic information systems (GISs) with already used techniques greatly expands the potential applications of multicriteria analysis. Using GIS-based multicriteria analysis, it is possible to determine a land’s ideal suitability based on a variety of natural factors (such as topography, soil, and climate), as well as numerous socioeconomic and economic factors. Due to this combination, GIS-based multicriteria analysis for suitability studies in land management, environmental sciences and protection, landscape design, agriculture, urban planning, and many other crucial areas of land use may be carried out with great efficiency and flexibility. The best land-use alternatives are chosen using these suitability results, and the usage of costly and potentially harmful environmental inputs is minimized. This allows for efficient decision making in land use management.

It gives us great pleasure to extend this invitation to you for the Special Issue on “Geospatial Data in Land Suitability Assessment”, which aims to bring together various interdisciplinary fields with the cutting-edge, effective, and adaptable techniques found in GIS-based multicriteria analysis to identify the best possible land suitability.

This Special Issue seeks to further current understanding of the assessment of land suitability using GIS-based multicriteria analysis in a number of areas that are crucial for effective land use management. Submissions should include a wide variety of subjects that are envisioned as the foundation for effective land use management, with GIS-based multicriteria analysis as the main tool. Urban planning, agriculture, environmental sciences, and other multidisciplinary fields with a direct connection to land use management are a few examples of potential themes. Case studies are also encouraged for submission due to the versatility of GIS-based multicriteria analysis, which is useful for professionals from all over the world to assess their own technique and criteria evaluation in their chosen disciplines.

We look forward to receiving your contributions.

Dr. Ivan Plaščak
Prof. Dr. Mladen Jurišić
Dr. Dorijan Radočaj
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

  • land management
  • environmental modeling
  • geographic information system (gis)
  • remote sensing
  • satellite missions
  • multicriteria decision making

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Related Special Issue

Published Papers (1 paper)

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Research

30 pages, 18624 KiB  
Article
Harnessing Machine Learning Algorithms to Model the Association between Land Use/Land Cover Change and Heatwave Dynamics for Enhanced Environmental Management
by Kumar Ashwini, Briti Sundar Sil, Abdulla Al Kafy, Hamad Ahmed Altuwaijri, Hrithik Nath and Zullyadini A. Rahaman
Land 2024, 13(8), 1273; https://doi.org/10.3390/land13081273 - 12 Aug 2024
Viewed by 1576
Abstract
As we navigate the fast-paced era of urban expansion, the integration of machine learning (ML) and remote sensing (RS) has become a cornerstone in environmental management. This research, focusing on Silchar City, a non-attainment city under the National Clean Air Program (NCAP), leverages [...] Read more.
As we navigate the fast-paced era of urban expansion, the integration of machine learning (ML) and remote sensing (RS) has become a cornerstone in environmental management. This research, focusing on Silchar City, a non-attainment city under the National Clean Air Program (NCAP), leverages these advanced technologies to understand the urban microclimate and its implications on the health, resilience, and sustainability of the built environment. The rise in land surface temperature (LST) and changes in land use and land cover (LULC) have been identified as key contributors to thermal dynamics, particularly focusing on the development of urban heat islands (UHIs). The Urban Thermal Field Variance Index (UTFVI) can assess the influence of UHIs, which is considered a parameter for ecological quality assessment. This research examines the interlinkages among urban expansion, LST, and thermal dynamics in Silchar City due to a substantial rise in air temperature, poor air quality, and particulate matter PM2.5. Using Landsat satellite imagery, LULC maps were derived for 2000, 2010, and 2020 by applying a supervised classification approach. LST was calculated by converting thermal band spectral radiance into brightness temperature. We utilized Cellular Automata (CA) and Artificial Neural Networks (ANNs) to project potential scenarios up to the year 2040. Over the two-decade period from 2000 to 2020, we observed a 21% expansion in built-up areas, primarily at the expense of vegetation and agricultural lands. This land transformation contributed to increased LST, with over 10% of the area exceeding 25 °C in 2020 compared with just 1% in 2000. The CA model predicts built-up areas will grow by an additional 26% by 2040, causing LST to rise by 4 °C. The UTFVI analysis reveals declining thermal comfort, with the worst affected zone projected to expand by 7 km2. The increase in PM2.5 and aerosol optical depth over the past two decades further indicates deteriorating air quality. This study underscores the potential of ML and RS in environmental management, providing valuable insights into urban expansion, thermal dynamics, and air quality that can guide policy formulation for sustainable urban planning. Full article
(This article belongs to the Special Issue Geospatial Data in Land Suitability Assessment: 2nd Edition)
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