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Geosciences
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A GIS Spatial Analysis Model for Land Use Change
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A GIS Spatial Analysis Model for Land Use Change

A special issue of Geosciences (ISSN 2076-3263).

Deadline for manuscript submissions: closed (30 March 2021) | Viewed by 23795

Special Issue Editors

Prof. Dr. Elzbieta Bielecka

E-Mail Website
Guest Editor
WAT Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908 Warszawa, Poland
Interests: spatial analysis; mapping; geoinformation; geomatics; geographical analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Małgorzata Luc

E-Mail Website
Co-Guest Editor
Institute of Geography and Spatial Management, Jagiellonian University, 31-007 Kraków, Poland
Interests: geoinformatics; landscape research; land use change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Land use change is one of the most important types of environmental change, and it is occurring rapidly in all regions around the word. Land use is generally driven by such demographic changes as: population growth, migration, as well as economic changes. In general, land use changes include urban sprawl, conversion of agricultural land, land abandonment, deforestation, and reforestation. The reason for changes in LU/LC varies considerably from region to region and covers many environmental, economic, political, and social problems. Documenting land use changes, simulating land use changes, and identifying their impact on the environment are becoming more important because the results can be useful for sustainable land management on a local, regional, national or even global scale. GIS-based spatial analysis and GIS modeling have been widely used to monitor and forecast land use/land cover changes and their impact on the environment and human wellbeing. Geospatial technology also plays a key role in monitoring the achievement of Sustainable Development Goals, in particular Goal 11 and land use efficiency (SDG 11.3.1).

This Special Issue aims to disseminate state-of-the-art research articles as well as review papers on GIS-based spatial analysis and model for land use/land cover change with the use of earth observation data (in situ and remote sensing), topographic maps, and any other sources of information on land cover/land use. Contributions related to geography, geology and geosciences are welcome.

Prof. Dr. Eng. Elzbieta Bielecka
Dr. Małgorzata Luc
Guest Editors

Manuscript Submission Information

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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

  • change detection of land use and land cover
  • urban sprawl modeling
  • deforestation modeling and monitoring
  • multitemporal spatial analysis
  • accuracy assessment
  • spatial relation between land use and population distribution
  • SDG 11.3.1
  • data mining and machine learning

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Published Papers (4 papers)

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Research

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22 pages, 2541 KiB  
Article
Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland
by Barbara Wiatkowska, Janusz Słodczyk and Aleksandra Stokowska
Geosciences 2021, 11(8), 312; https://doi.org/10.3390/geosciences11080312 - 26 Jul 2021
Cited by 35 | Viewed by 7285
Abstract
Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, [...] Read more.
Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment. Full article
(This article belongs to the Special Issue A GIS Spatial Analysis Model for Land Use Change)
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27 pages, 16183 KiB  
Article
Analysis of Built-Up Areas of Small Polish Cities with the Use of Deep Learning and Geographically Weighted Regression
by Maciej Adamiak, Iwona Jażdżewska and Marta Nalej
Geosciences 2021, 11(5), 223; https://doi.org/10.3390/geosciences11050223 - 20 May 2021
Cited by 6 | Viewed by 4085
Abstract
Small cities are an important part of the settlement system, a link between rural areas and large cities. Although they perform important functions, research focuses on large cities and metropolises while marginalizing small cities, the study of which is of great importance to [...] Read more.
Small cities are an important part of the settlement system, a link between rural areas and large cities. Although they perform important functions, research focuses on large cities and metropolises while marginalizing small cities, the study of which is of great importance to progress in social sciences, geography, and urban planning. The main goal of this paper was to verify the impact of selected socio-economic factors on the share of built-up areas in 665 small Polish cities in 2019. Data from the Database of Topographic Objects (BDOT), Sentinel-2 satellite imagery from 2015 and 2019, and Local Data Bank by Statistics Poland form 2019 were used in the research. A machine learning segmentation procedure was used to obtain the data on the occurrence of built-up areas. Hot Spot (Getis-Ord Gi*) analysis and geographically weighted regression (GWR) was applied to explain spatially varying impact of factors related to population, spatial and economic development, and living standards on the share of built-up areas in the area of small cities. Significant association was found between the population density and the share of built-up areas in the area of the cities studied. The influence of the other socio-economic factors examined, related to the spatial and economic development of the cities and the quality of life of the inhabitants, showed great regional variation. The results also indicated that the share of built-up areas in the area of the cities under study is a result of the conditions under which they were established and developed throughout their existence, and not only of the socio-economic factors affecting them at present. Full article
(This article belongs to the Special Issue A GIS Spatial Analysis Model for Land Use Change)
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19 pages, 13976 KiB  
Article
Automated Land Cover Change Detection and Forest Succession Monitoring Using LiDAR Point Clouds and GIS Analyses
by Marta Szostak
Geosciences 2020, 10(8), 321; https://doi.org/10.3390/geosciences10080321 - 17 Aug 2020
Cited by 14 | Viewed by 3368
Abstract
This paper investigates the possibility of applying light detection and ranging (LiDAR) point clouds and geographic information system (GIS) analyses for land use and land cover (LULC) change detection, mainly with a view to monitoring uncontrolled forest succession occurring on postagricultural lands. The [...] Read more.
This paper investigates the possibility of applying light detection and ranging (LiDAR) point clouds and geographic information system (GIS) analyses for land use and land cover (LULC) change detection, mainly with a view to monitoring uncontrolled forest succession occurring on postagricultural lands. The research was conducted in a part of the administrative district of Milicz (in the central-west area of Poland). The areas of interest were parcels in which agricultural use has been abandoned and forest succession processes have progressed. The airborne laser scanning (ALS) data (acquired in 2007, 2012, and 2015) revealed detailed changes in land cover as a result of the progression in the forest succession process. Using the ALS data, the LULC changes and the progress of secondary forest succession are shown, and the vegetation parameters (LiDAR metrics) are presented. Full article
(This article belongs to the Special Issue A GIS Spatial Analysis Model for Land Use Change)
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Review

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21 pages, 2844 KiB  
Review
GIS Spatial Analysis Modeling for Land Use Change. A Bibliometric Analysis of the Intellectual Base and Trends
by Elzbieta Bielecka
Geosciences 2020, 10(11), 421; https://doi.org/10.3390/geosciences10110421 - 25 Oct 2020
Cited by 28 | Viewed by 7525
Abstract
The paper aimed to express the cognitive and intellectual structure of research executed in the field of GIS-based land use change modeling. An exploration of the Web of Science database showed that research in GIS spatial analysis modeling for land use change began [...] Read more.
The paper aimed to express the cognitive and intellectual structure of research executed in the field of GIS-based land use change modeling. An exploration of the Web of Science database showed that research in GIS spatial analysis modeling for land use change began in the early 1990s and has continued since then, with a substantial growth in the 21st century. By science mapping methods, particularly co-coupling, co-citation, and citation, as well as bibliometric measures, like impact indices, this study distinguishes the most eminent authors, institutions, countries, and journals in GIS-based land use change modeling. The results showed that GIS-based analysis of land use change modeling is a multi- and interdisciplinary research topic, as reflected in the diversity of WoS research categories, the most productive journals, and the topics analyzed. The highest impact on the world sciences in the field have can be attributed to European Universities, particularly from The Netherlands, Belgium, Switzerland, and Great Britain. However, China and the United States published the highest number of research papers. Full article
(This article belongs to the Special Issue A GIS Spatial Analysis Model for Land Use Change)
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