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Integration of Remote Sensing and GIS for Land Use Change...
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Integration of Remote Sensing and GIS for Land Use Change Assessment (Second Edition)

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land Innovations – Data and Machine Learning".

Deadline for manuscript submissions: 30 November 2026 | Viewed by 2741

Special Issue Editor

Prof. Dr. Martin Boltiziar

E-Mail Website
Guest Editor
Institute of Landscape Ecology SAS Bratislava, Branch Nitra, 94901 Nitra, Slovakia
Interests: geography; landscape ecology; remote sensing; geoinformatics; geomorphology; land use change; landscape pattern physical geography; geostatistical analysis; natural hazards
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Land-use change has become a global environmental concern with significant consequences for ecosystem services, biodiversity protection, and climate change due to the increase in global population and economic activity. Remote sensing technologies and geographic information systems (GISs) provide a scientific foundation for understanding and managing land-use change, serving as crucial tools for monitoring and assessing change over time.

The goal of this Special Issue is to collect papers (original research articles and review papers) to provide insights into the most recent findings in the field of land-use change assessment using GISs and remote sensing technologies. Through interdisciplinary collaboration, we seek to advance the use of remote sensing and GIS technologies in the assessment of land-use change, as well as the sustainable management and preservation of natural resources.

This Special Issue will welcome manuscripts that link the following themes:

  • Application of remote sensing technology in land-use change monitoring;
  • The role of GISs in land-use change analysis;
  • Drivers and influencing factors of land-use change;
  • Models and methods for land-use change assessment;
  • Land-use change and ecosystem services;
  • Land-use change and climate change;
  • Socioeconomic impacts of land-use change.

We look forward to receiving your original research articles and reviews.

Prof. Dr. Martin Boltiziar
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 250 words) can be sent to the Editorial Office for assessment.

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

  • remote sensing
  • GIS
  • land-use change
  • land cover
  • ecosystem services
  • environmental impact assessment

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Related Special Issue

Published Papers (3 papers)

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Research

31 pages, 11082 KB  
Article
An Analysis of the Impact of High-Quality Urban Development on Non-Point Source Pollution in the Chenghai Lake Drainage Basin Based on Multi-Source Big Data
by Mingbiao Chen and Xiong He
Land 2026, 15(4), 660; https://doi.org/10.3390/land15040660 - 16 Apr 2026
Viewed by 260
Abstract
With urbanization transforming from scale expansion to high-quality development and the increasing prominence of the ecological environment constraints of drainage basins, systematically identifying the mechanism of action of non-point source pollution from a high-quality development perspective is significant for coordinating urban development and [...] Read more.
With urbanization transforming from scale expansion to high-quality development and the increasing prominence of the ecological environment constraints of drainage basins, systematically identifying the mechanism of action of non-point source pollution from a high-quality development perspective is significant for coordinating urban development and environmental protection. Based on remote sensing data on atmospheric pollution and multi-source spatial big data such as nighttime light (NTL), LandScan population, point of interest (POI), and land use data from 2013 to 2025, this study applies methods including deposition flux analysis, deep learning fusion, bivariate spatial autocorrelation, and geographically weighted regression (GWR) to empirically analyze the spatiotemporal evolution characteristics, spatial correlation, and local impacts of high-quality urban development on non-point source pollution in the Chenghai drainage basin. We find that, firstly, non-point source pollution and high-quality urban development in the Chenghai drainage basin both present significant stage-specific and spatial heterogeneity. In other words, the two are not mutually independent spatial elements in space; instead, they are closely and significantly correlated, with their correlation types showing obvious spatial agglomeration characteristics. Secondly, the impact of high-quality urban development on non-point source pollution evolves in stages. It gradually shifts from a whole-region, homogeneous, strongly positive driving force to spatial differentiation. Specifically, from 2013 to 2017, the whole-region regression coefficients are generally greater than 0.5, meaning that urban development represents a strong, whole-region driving force promoting pollution. However, after 2017, this impact evolves into a stable spatial differentiation pattern. It mainly shows that the northern urban core area, where coefficients are greater than 0.5, maintains a continuous strong positive driving force. Meanwhile, the peripheral area, where coefficients are generally lower than 0, creates a negative inhibition effect. Based on the above rules, further analysis shows that the impact of high-quality urban development on non-point source pollution is absolutely not a simple linear relationship. Instead, it is a result of the coupling effect of multiple factors, including development stage, spatial location, and governance level. Therefore, to positively affect the ecological environment through high-quality development, model transformation and precise governance are essential. The findings of this study deepen our understanding of the transformation of urban development models and the response mechanism of non-point source pollution. They also provide a scientific basis and decision support for promoting the coordinated governance of high-quality urban development and non-point source pollution by region and stage in plateau lake drainage basins, as well as for improving the sustainable development of drainage basins. Full article
(This article belongs to the Special Issue Integration of Remote Sensing and GIS for Land Use Change Assessment (Second Edition))
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25 pages, 34337 KB  
Article
Spatiotemporal Modeling and Future Trends of Land Surface Temperature Using Remote Sensing and CA-ANN in Industrial Narayanganj, Bangladesh
by Sayed Abu Johany, Sajid Ibne Jamalfaisal, Md Sabit Mia, Sujit Kumar Roy, Md. Tahsinur Rahman, Md. Mahmudul Hasan, Wafa Saleh Alkhuraiji, Martin Boltižiar and Mohamed Zhran
Land 2026, 15(3), 423; https://doi.org/10.3390/land15030423 - 5 Mar 2026
Viewed by 1287
Abstract
The thermal consequences of industrial land transformation remain underexplored in rapidly urbanizing regions of Bangladesh. This study presents a novel approach of how extensive industrial expansion in Narayanganj, a major manufacturing hub dominated by textile, knitwear and dyeing industries, has altered land surface [...] Read more.
The thermal consequences of industrial land transformation remain underexplored in rapidly urbanizing regions of Bangladesh. This study presents a novel approach of how extensive industrial expansion in Narayanganj, a major manufacturing hub dominated by textile, knitwear and dyeing industries, has altered land surface temperature (LST) dynamics over the past three decades, including its variation across classes, relationships with biophysical indices and future patterns. Landsat 5 TM and Landsat 8 OLI imagery from 1991, 2007, and 2023 were utilized to map LULC using winter-season images through supervised classification, while multi-seasonal thermal bands were used to derive LST. LST variations were further evaluated using cross-sectional profiles across different land cover types, and correlations were examined with indices including the greenness index (NDVI), moisture index (NDMI), built-up index (NDBI), and barrenness index (NDBAI). Additionally, a future LST map for 2039 was generated using the cellular automata–artificial neural network (CA-ANN) model. Results show that between 1991 and 2023, built-up area and bare land expanded by 16.72% and 14.15%, while vegetation area and water bodies decreased by 26.62% and 4.25%. Average LST increased from 25.94 °C in 1991 to 28.68 °C in 2023, with projections indicating an additional 2 °C rise by 2039. Cross-sectional analysis found that built-up areas consistently showed the maximum surface temperatures, followed by bare land, vegetation and water bodies. In addition, correlation analysis revealed that LST showed an inverse relation with NDVI and NDMI, while showing a positive relationship with NDBI and NDBAI. These findings show the necessity of sustainable urban planning and green infrastructure to reduce surface heating in rapidly urbanizing areas. Full article
(This article belongs to the Special Issue Integration of Remote Sensing and GIS for Land Use Change Assessment (Second Edition))
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30 pages, 14744 KB  
Article
Geospatial and Sentinel-2 Analysis of Mediterranean Wildfire Severity and Land-Cover Patterns in Greece During the 2024 Fire Season
by Ignacio Castro-Melgar, Eleftheria Basiou, Ioannis Athinelis, Efstratios-Aimilios Katris, Maria Zacharopoulou, Ioanna-Efstathia Kalavrezou, Artemis Tsagkou and Issaak Parcharidis
Land 2026, 15(2), 333; https://doi.org/10.3390/land15020333 - 15 Feb 2026
Viewed by 683
Abstract
Wildfires pose increasing challenges for Mediterranean landscapes, making rapid and reliable mapping of burn severity essential for management and recovery planning. This study applies an integrated geospatial workflow to wildfires that occurred in Greece during the 2024 summer season. Sentinel-2-derived dNBR and RBR [...] Read more.
Wildfires pose increasing challenges for Mediterranean landscapes, making rapid and reliable mapping of burn severity essential for management and recovery planning. This study applies an integrated geospatial workflow to wildfires that occurred in Greece during the 2024 summer season. Sentinel-2-derived dNBR and RBR indices were used to map burn severity, while CORINE Land Cover and Tree Cover Density datasets provided complementary context for interpreting how severity varied across different vegetation types and canopy-density conditions. A one-way ANOVA was used to summarize differences in burned area among severity classes. The results show that low and moderate-low severity levels dominated most fire perimeters, whereas high-severity patches were spatially limited and typically coincided with densely forested areas. Validation against Copernicus Emergency Management Service data yielded an overall agreement of approximately 94%, indicating that the applied multispectral workflow produced severity extents broadly consistent with independent operational products. By applying a consistent methodology across multiple fire events, this study demonstrates the value of combining spectral indices with land-cover information for interpreting severity patterns and supporting post-fire management. The findings highlight the usefulness of freely accessible remote sensing data for timely fire assessment in Mediterranean environments and provide a basis for future multi-regional and multi-year comparisons. Full article
(This article belongs to the Special Issue Integration of Remote Sensing and GIS for Land Use Change Assessment (Second Edition))
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