Special Issue "Land Use Mapping as the Base for Modeling and Earth Oriented Digital Twins"

A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: 22 February 2022.

Special Issue Editor

Dr. Karel Charvat
E-Mail Website
Guest Editor
Plan4all z.s., K Rybníčku 557, 33012 Horní Bříza, Czech Republic
Interests: remote sensing; ICT; IoT; open data; big data; agriculture; rural development; semantic data; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Geospatial data on land use and land cover (LULC) contains information about the bio-physical cover of the Earth's surface and the purposes for which humans exploit it. LULC data are important for many geo-related disciplines, as well as f various specific tasks. Such use involves both physical-geographical (environmental) and socio-economic phenomena. LULC is used for the modeling of human population, urban growth and/or transformation, agriculture, socio-economic activities, or transportation. LULC also affects several environmental characteristics such as hydrological ones, when LULC has an impact on the surface runoff, water quality, soil moisture, and even groundwater accumulation. Another area where LULC data is used is climate modeling at various scales, from urban to regional analysis.

The biggest area is the modeling, analysis, and research, in general, of the LULC itself and its changes over time, which are closely related to the development of the landscape. Sustainable Development Goals on a global scale and the Green Deal Strategy in Europe will require the development of a very high precision digital model of the Earth to monitor and simulate natural and human activity and to develop and test scenarios that would enable more sustainable development and support environmental policies. For this purpose, we will need a digital replica of a living or non-living physical entity—a digital twin—that will give expert and non-expert users high-quality information, services, models, scenarios, forecasts, and visualizations. Detail LULC will be an important part of these models. It will include not only current status but also changes in time and relation to other aspects, for example, climatic change. This Special Issue will collect papers related to existing LULC models. But it will also be focused on modeling and AI tools dealing with LULC. We are interested in papers focused on the use of remote sensing for detection changes, usage of HPC and cloud computing for modeling and analysis of land-use changes, and on paper demonstrations of the use of LULC in different domains.

Dr. Karel Charvat
Guest Editor

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 papers will be 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 1800 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 use
  • Land cover
  • Digital twins
  • Sustainable development goals
  • Modeling
  • Artificial intelligence

Published Papers (1 paper)

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Research

Article
Mapping of Sicilian Pocket Beaches Land Use/Land Cover with Sentinel-2 Imagery: A Case Study of Messina Province
Land 2021, 10(7), 678; https://doi.org/10.3390/land10070678 - 27 Jun 2021
Cited by 6 | Viewed by 897
Abstract
Pocket beaches (PBs) are among the most attractive tourist sites and economic development contributors in coastal areas; however, they are negatively impacted by the combined effects of climate change and anthropogenic activities. Generally, research on PBs is conducted from the beach towards offshore. [...] Read more.
Pocket beaches (PBs) are among the most attractive tourist sites and economic development contributors in coastal areas; however, they are negatively impacted by the combined effects of climate change and anthropogenic activities. Generally, research on PBs is conducted from the beach towards offshore. Studies on the land use/land cover (LULC) of PBs are limited and currently lacking. Such studies deserve more investigation due to the importance of LULC in PBs’ functioning. In this study, supervised classification methods were investigated for LULC mapping of the PBs located in the province of Messina. Sentinel-2B satellite images were analyzed using maximum likelihood (MaL), minimum distance (MiD), mahalanobis distance (MaD) and spectral angle mapper (SAM) classification methods. The study was conducted mainly in order to determine which classification method would be adequate for small scale Sentinel-2 imagery analysis and provide accurate results for the LULC mapping of PBs. In addition, an occurrence-based filter algorithm in conjunction with OpenStreetMap data and Google Earth imagery was used to extract linear features within 500 m of the inland buffer zone of the PBs. The results demonstrate that information on the biophysical parameters, namely surface cover fractions, of the coastal area can be obtained by conducting LULC mapping on Sentinel-2 images. Full article
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