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 2023 | Viewed by 8355

Special Issue Editor

Dr. Karel Charvat
E-Mail Website
Guest Editor
Czech Centre for Science and Society, WirelessInfo, 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
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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 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 2000 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 (4 papers)

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Research

Article
Are Wildfires in the Wildland-Urban Interface Increasing Temperatures? A Land Surface Temperature Assessment in a Semi-Arid Mexican City
Land 2022, 11(12), 2105; https://doi.org/10.3390/land11122105 - 22 Nov 2022
Viewed by 394
Abstract
High rates of land conversion due to urbanization are causing fragmented and dispersed spatial patterns in the wildland-urban interface (WUI) worldwide. The occurrence of anthropogenic fires in the WUI represents an important environmental and social issue, threatening not only vegetated areas but also [...] Read more.
High rates of land conversion due to urbanization are causing fragmented and dispersed spatial patterns in the wildland-urban interface (WUI) worldwide. The occurrence of anthropogenic fires in the WUI represents an important environmental and social issue, threatening not only vegetated areas but also periurban inhabitants, as is the case in many Latin American cities. However, research has not focused on the dynamics of the local climate in the WUI. This study analyzes whether wildfires contribute to the increase in land surface temperature (LST) in the WUI of the metropolitan area of the city of Guanajuato (MACG), a semi-arid Mexican city. We estimated the pre- and post-fire LST for 2018–2021. Spatial clusters of high LST were detected using hot spot analysis and examined using ANOVA and Tukey’s post-hoc statistical tests to assess whether LST is related to the spatial distribution of wildfires during our study period. Our results indicate that the areas where the wildfires occurred, and their surroundings, show higher LST. This has negative implications for the local ecosystem and human population, which lacks adequate infrastructure and services to cope with the effects of rising temperatures. This is the first study assessing the increase in LST caused by wildfires in a WUI zone in Mexico. Full article
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Article
An Advanced Open Land Use Database as a Resource to Address Destination Earth Challenges
Land 2022, 11(9), 1552; https://doi.org/10.3390/land11091552 - 13 Sep 2022
Viewed by 822
Abstract
Land-use and land-cover (LULC) themes are important for many domains, especially when they process environmental and socio-economic phenomena. The evolution of a land-use database called Open Land Use (OLU) started in 2013 and was continued by adapting many user requirements. The goal of [...] Read more.
Land-use and land-cover (LULC) themes are important for many domains, especially when they process environmental and socio-economic phenomena. The evolution of a land-use database called Open Land Use (OLU) started in 2013 and was continued by adapting many user requirements. The goal of this study was to design a new version of the OLU database that would better fit the gathered user requirements collected by projects using LULC data. A formal definition of the developed data model through Unified Modeling Language (UML) class diagrams, a feature catalogue based on ISO 19110 and SQL scripts for setting up the OLU database, are the key achievements of the presented paper. The presented research provides a multi-scale open database of LULC information supporting the DestinE initiative to develop a very-high-precision digital model of the earth. The novel spatio-temporal thematic approach also lies in modular views of the OLU database. Full article
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Article
Spatiotemporal Change Analysis and Prediction of Future Land Use and Land Cover Changes Using QGIS MOLUSCE Plugin and Remote Sensing Big Data: A Case Study of Linyi, China
Land 2022, 11(3), 419; https://doi.org/10.3390/land11030419 - 14 Mar 2022
Cited by 3 | Viewed by 3895
Abstract
Land use and land cover (LULC) change analysis is a systematic technique that aids in the comprehension of physical and non-physical interaction with the natural habitat and the pursuit of environmental sustainability. Research regarding LULC’s spatiotemporal changing patterns and the simulation of future [...] Read more.
Land use and land cover (LULC) change analysis is a systematic technique that aids in the comprehension of physical and non-physical interaction with the natural habitat and the pursuit of environmental sustainability. Research regarding LULC’s spatiotemporal changing patterns and the simulation of future scenarios offers a complete view of present and future development possibilities. To simulate the spatiotemporal change transition potential and future LULC simulation, we utilized multi-temporal remotely sensed big data from 1990 to 2020 with a 10-year interval. Independent variables (DEM, slope, and distance from roads) and an integrated CA-ANN methodology within the MOLUSCE plugin of QGIS were utilized. The findings reveal that physical and socioeconomic driving variables have a substantial effect on the patterns of the terrain. In the last three decades, the study area had a significant rise in impervious surface from 10.48% to 26.91%, as well as a minor increase in water from 1.30% to 1.67%. As a result, forest cover decreased from 12.60% to 8.74%, green space decreased from 26.34% to 16.57%, and barren land decreased from 49.28% to 46.11%. Additionally, the predictions (2030–2050) support the increasing trend towards impervious surface at the expense of significant quantities of forest and green space. Full article
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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 18 | Viewed by 1958
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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