Geographic Information System Tools Research Articles

The Multi–Disaster risk assessment: A-GIS based approach for Izmir City

Urban settlements currently face many disasters that are increasing in number and frequency every day such as floods, landslides, sea level rise, storms, drought, forest fires, etc. due to the negative consequences of global climate change caused by significantly exceeding the carrying capacity of nature. Cities are currently becoming less resistant to disaster risks because of the unhealthy settlements. These settlements are becoming widespread in terms of physical, economic and social conditions as a natural result of the urbanization in which planning processes are carried out in an uncontrolled and unsupervised manner. This situation makes it a necessity to develop strategies and policies aimed at reducing and/or eliminating possible disaster damages which are defined as high risk. From this viewpoint, the study aims to reveal the current disaster risks in urban areas with a dense population and building stock. Izmir city is determined as the study area. Spatial analyses are performed for disaster risk by using Geographical Information Systems (GIS) tools and Weighted Overlap method considering the natural and built environment elements that significantly affect the disaster risk. The findings obtained from the study and the determinations made within the scope of the Izmir Provincial Disaster Risk Reduction Plan (IRAP) prepared by the Disaster and Emergency Management Presidency (AFAD) are evaluated comparatively. As a result, it has been seen that the determinations put forward for disaster risks have shown consistency throughout Izmir city and the studies carried out at the local level have been prioritized in such a way as to be aimed at risk management and prevention planning by the time.

Spatio-temporal investigation of urbanization and its impact on habitat fragmentation in natural ecosystems of Istanbul using Shannon’s entropy and landscape metrics in GIS

This study aims to investigate the impact of spatio-temporal dynamics of urban sprawl on habitats in Istanbul, using the CORINE 1990 and 2018 land cover datasets. In this context, by means of geographic information system (GIS) tools and techniques, land cover maps are created for land cover change analysis and visualization, the Shannon’s entropy method is performed for measuring urban growth and sprawl, and the landscape metrics method is applied for assessing habitat loss and fragmentation. Results indicate that the rate of urban sprawl in the area increased by 0.1230 as per the Shannon’s entropy index over the 28-year period. Similarly, the Shannon Diversity Index and the Shannon Evenness Index rose from 1.74 to 1.85 and from 0.68 to 0.70, respectively, indicating an increase in urbanization within the area. Moreover, an analysis of patch numbers reveals that habitat fragmentation increased in shrub and/or herbaceous vegetation associations (72.55%), heterogeneous agricultural areas (45.11%), arable lands (42.5%), forests (36.13%) and pastures (15.05%), due to urbanization. Habitat fragmentation has had a detrimental effect on the local biodiversity. While 15 flora species were identified as vulnerable, 13 as endangered and 9 as critically endangered, 19 fauna species were identified as vulnerable and 5 as endangered. This study highlights that the natural habitats and biodiversity of Istanbul will suffer further decline due to urbanization unless sustainable urban planning and management policies are put into practice. It is essential to have controlled urban development to preserve the ecosystem’s carrying capacity, and urbanization decisions must consider this requirement.

Mapping of soil suitability for medicinal plants using machine learning methods

Inadequate conservation of medicinal plants can affect their productivity. Traditional assessments and strategies are often time-consuming and linked with errors. Utilizing herbs has been an integral part of the traditional system of medicine for centuries. However, its sustainability and conservation are critical due to climate change, over-harvesting and habitat loss. The study reveals how machine learning algorithms, geographic information systems (GIS) being a powerful tool for mapping and spatial analysis, and soil information can contribute to a swift decision-making approach for actual forethought and intensify the productivity of vulnerable curative plants of specific regions to promote drug discovery. The data analysis based on machine learning and data mining techniques over the soil, medicinal plants and GIS information can predict quick and effective results on a map to nurture the growth of the herbs. The work incorporates the construction of a novel dataset by using the quantum geographic information system tool and recommends the vulnerable herbs by implementing different supervised algorithms such as extra tree classifier (EXTC), random forest, bagging classifier, extreme gradient boosting and k nearest neighbor. Two unique approaches suggested for the user by using EXTC, firstly, for a given subregion type, its suitable soil classes and secondly, for soil type from the user, its respective subregion labels are revealed, finally, potential medicinal herbs and their conservation status are visualised using the choropleth map for classified soil/subregion. The research concludes on EXTC as it showcases outstanding performance for both soil and subregion classifications compared to other models, with an accuracy rate of 99.01% and 98.76%, respectively. The approach focuses on serving as a comprehensive and swift reference for the general public, bioscience researchers, and conservationists interested in conserving medicinal herbs based on soil availability or specific regions through maps.

Characterization of spatio-temporal dynamics of the constrained network of the filamentous fungus Podospora anserina using a geomatics-based approach.

In their natural environment, fungi are subjected to a wide variety of environmental stresses which they must cope with by constantly adapting the architecture of their growing network. In this work, our objective was to finely characterize the thallus development of the filamentous fungus Podospora anserina subjected to different constraints that are simple to implement in vitro and that can be considered as relevant environmental stresses, such as a nutrient-poor environment or non-optimal temperatures. At the Petri dish scale, the observations showed that the fungal thallus is differentially affected (thallus diameter, mycelium aspect) according to the stresses but these observations remain qualitative. At the hyphal scale, we showed that the extraction of the usual quantities (i.e. apex, node, length) does not allow to distinguish the different thallus under stress, these quantities being globally affected by the application of a stress in comparison with a thallus having grown under optimal conditions. Thanks to an original geomatics-based approach based on the use of automatized Geographic Information System (GIS) tools, we were able to produce maps and metrics characterizing the growth dynamics of the networks and then to highlight some very different dynamics of network densification according to the applied stresses. The fungal thallus is then considered as a map and we are no longer interested in the quantity of material (hyphae) produced but in the empty spaces between the hyphae, the intra-thallus surfaces. This study contributes to a better understanding of how filamentous fungi adapt the growth and densification of their network to potentially adverse environmental changes.

EventGeoScout: Fostering Citizen Empowerment and Augmenting Data Quality through Collaborative Geographic Information Governance and Optimization

In this manuscript, we present EventGeoScout, an innovative framework for collaborative geographic information management, tailored to meet the needs of the dynamically changing landscape of geographic data integration and quality enhancement. EventGeoScout enables the seamless fusion of open data from different sources and provides users with the tools to refine and improve data quality. A distinctive feature of our framework is its commitment to platform-agnostic data management, ensuring that processed datasets are accessible via standard Geographic Information System (GIS) tools, reducing the maintenance burden on organizations while ensuring the continued relevance of the data. Our approach goes beyond the boundaries of traditional data integration, enabling users to fully harness the power of geospatial information by simplifying the data creation process and providing a versatile solution to the complex challenges posed by layered geospatial data. To demonstrate the versatility and robustness of EventGeoScout as an optimization tool, we present a case study centered on the Uncapacitated Facility Location Problem (UFLP), where a genetic algorithm was used to achieve outstanding performance on both traditional computing platforms and smartphone devices. As a concrete case study, we applied our solution in the context of the Málaga City Marathon, using the latest data from the last edition of the marathon.

Investigating Noise Mapping in Cities to Associate Noise Levels with Sources of Noise Using Crowdsourcing Applications

Environmental noise is a major environmental concern in metropolitan cities. The rapid social and economic growth in the 20th century is not always accompanied by adequate land planning and environmental management measures. As a consequence of rapid urbanization processes, cities are facing an increase in noise pollution. Noise is being recognized as a serious environmental problem and one which must be accounted for in a sustained development policy designed to improve the quality of life for citizens. Therefore, the monitoring of noise is a crucial aspect of urban planning to allow urban planners to create harmonious and livable environments for communities worldwide. This research aims at assessing the noise levels and associated sources of noise in downtown areas through the involvement of crowdsourcing techniques. The incorporation of noise mapping and increased public awareness are achieved by a framework that enables a comparative scheme between two cities: Alexandria, Egypt and Zagreb, Croatia. The methodology depends on combining crowdsourcing techniques using mobile applications and geographic information system (GIS) tools to detect and analyze noise. Finally, this research provides a comparison between the two cities using the adopted methodology and introduces recommendations to enhance urban planning decisions.

Historical and current distribution ranges of the Asiatic black bear (Ursus thibetanus)

The current distribution of Asiatic black bear (Ursus thibetanus) is available on the IUCN Red List of Threatened species website; however, nothing is known about the historical extent and occurrence of this species. Therefore, we aimed to understand the historical distribution of the Asiatic black bear, and map and estimate its total size, to compare it with that of species current distribution. In addition, we analyzed a network of protected areas in the past and current ranges of the species. We employed geographic information system (GIS) software to reconstruct and measure the historical range of the Asiatic black bear, comparing past and current ranges to analyze its expected range contraction. The main focus of the study was to enhance our understanding of the species' historical distribution, contributing to better conservation strategies for the present and future perspectives. The utilization of GIS tools facilitates a comprehensive exploration of the factors influencing the species' decline, ultimately aiding in more effective management and conservation efforts. We used published records of black bear’s occurrence in anywhere in history to reconstruct its historical distribution range. Results revealed that the Asiatic black bear was more widely distributed in historical times and its range spanned across approximately 15.86 million km2 while its current range is limited to approximately 7.85 million km2, showing a range contraction of approximately 49.5% (8.02 million km2 reduced). The total protected areas in the historical range of the species were found to be N = 9933, with total size of 0.946 million km2, against N = 6580 (0.667 million km2) that are present in the current range. Approximately 27.5% of the protected areas have lost the Asiatic black bear since historical times.

Managing Landscape Urbanization and Assessing Biodiversity of Wildlife Habitats: A Study of Bobcats in San Jose, California

In the rapid process of urbanization, crucial habitats for mid-sized felids such as bobcats are increasingly compromised. This study employs Geographic Information System (GIS) tools and Machine Learning to investigate the subtle impacts of urbanization on bobcat habitats. Focused on the San Jose area, our extensive geospatial analysis has developed a complex ecological model for bobcat habitats. Our findings emphasize the significant influence of factors like vegetation cover, water body distribution, road traffic volume, and intersection density on the suitability of habitats for bobcats. Specifically, we discovered that while vegetation cover typically supports habitat suitability, its proximity to busy roads significantly undermines this advantage, indicating a need for strategic urban planning that incorporates wildlife mobility. By synthesizing natural and urban elements, we offer fresh insights into urban ecosystem management and propose specific conservation tactics: identifying optimal wildlife crossings, integrating corridors with urban infrastructure, and placing fencing and signage strategically to facilitate wildlife movement safely. These measures aim to reduce road-related threats and enhance the integrity of natural habitats, strengthening bobcat conservation efforts. More than its direct implications for bobcat conservation, this study offers actionable insights for urban wildlife conservation and introduces innovative methods for assessing and mitigating the broader ecological impacts of urbanization.

Study on shoreline migration and island dynamics over the last five decades in the Muriganga River using multi-temporal satellite images.

The Muriganga River, also known as channel creek, underwent morphological changes often since it is an alluvial as well as a tidal river. The present study analyses the morphological changes in the Muriganga River and its islands with the help of the Remote Sensing and Geographical Information System (GIS) and digital shoreline analysis tool (DSAS 5.0). Moreover, the computation of morphological changes was also performed on two islands, i.e. Sagar and Ghoramara, which are situated just outside the river reach. Eight cloud-free satellite images of Landsat MSS (1972-1980), Landsat TM (1988-2011) and Landsat OLI (2017-2021) have been used to investigate the river shoreline shifting and island dynamics of the Muriganga River resulted from the erosion-accretion process during the last 49 years. For the short-term study, the erosion-accretion rates are derived from one Landsat image to the next, whereas for long-term analysis, the erosion-accretion rates are estimated based on the difference between 1972 as the reference image and the succeeding images. Short-term and long-term analysis shows that the average rate of erosion is more than that of accretion in Muriganga River. It is also found that the areas of Sagar, Ghoramara, Mousuni and Pushpa islands are shrinking continuously, whereas the Niogi and Basit islands are expanding enormously. These may indicate that the shoreline erosion results in widening the river and the eroded materials are accumulated in Niogi and Basit islands. The results suggest that there is an urge for a better coastal management strategy for the erosion control scheme. This study also helps in gaining knowledge of maintaining the navigability in the Muriganga River.

Analysing Decadal Land Use Land Cover Dynamics in the Sub-Upper Krishna Basin of Maharashtra, India Using Remote Sensing and GIS

Aims: This study was conducted to examine Land Use Land Cover (LULC) dynamics in Maharashtra’s sub-upper Krishna basin from 2009 to 2019 using remote sensing and geographical information system (GIS), focusing on water bodies, vegetation, soil, settlements, and their changes.
 Study Design: Employing remote sensing and GIS for LULC mapping (2009-2019) the study used a maximum likelihood classifier in supervised classification, identifying six land use categories: water bodies, open shrubs, forests, agricultural land, settlements, and fallow land.
 Place and Duration of Study: It was conducted in the sub-upper Krishna basin, Maharashtra, over ten years’ data (2009-2019).
 Methodology: The study utilised satellite remote sensing and GIS tools for LULC mapping. A supervised classification was applied with a maximum likelihood classifier to categorize land. The changes in water bodies, open shrubs, forests, agricultural land, settlements, and fallow land were analysed using GIS approach.
 Results: It was seen that, over the decade, fallow land decreased by 3.03%, while agricultural land and settlements grew by 7.32% and 4.3%, respectively. Tree cover increased by 9.85%, water bodies by 0.93%, and open scrubland decreased by 1.77%. Institutional factors, easier water access, and technological and economic factors drove these changes.
 Conclusion: The study advocates the effective use of satellite remote sensing to monitor LULC changes, identifying key drivers, including institutional and technological factors, contributes to sustainable development planning. The findings aid predictions for future land use changes, supporting effective land management and conservation strategies in the region.

Novel approach for the LULC change detection using GIS & Google Earth Engine through spatiotemporal analysis to evaluate the urbanization growth of Ahmedabad city

Changes in Land Use and Land Cover (LULC) have a significant impact on both urban and environmental planning, especially in the context of rapidly urbanising areas. The largest city in the state of Gujarat, Ahmedabad, has experienced substantial growth. Utilising the powerful tools of Geographic Information System (GIS) and Google Earth Engine (GEE), this study uses a thorough methodology to track and examine changes in LULC over the last ten years. Modifications in LULC have a significant impact on both urban and environmental planning, especially in light of the fast urbanisation cycle. This study uses a comprehensive approach to monitor and analyze Landsat imagery changes in LULC over the past ten years, leveraging the powerful capabilities of Google Earth Engine and GIS. Important insights into LULC patterns are revealed by analysing Landsat imagery from Ahmedabad from 2013 to 2023. Pre-processing with GIS and GEE, accuracy evaluation, and classification of satellite images are all included in the methodology. With a notable 0.85 Kappa and 89 % accuracy in LULC classification, the resulting LULC classifications cover settlements, vegetation, water bodies, arid land, and other relevant features. Results show that over the previous ten years, Ahmedabad has seen a noteworthy decrease in agricultural lands of 13.74 % and a reduction in barren areas of 4.78 %. Meanwhile, the total LULC patterns have shown a significant expansion of 23.56 %. This study is significant because it highlights how urbanisation reduces vegetation cover. The results will helpful for urban planning strategies that take changing environmental dynamics into account.

Erosion susceptibility mapping of a loess-covered region using Analytic Hierarchy Process – A case study: Kalat-e-Naderi, northeast Iran

In this study, the Analytic Hierarchy Process (AHP) is applied to generate erosion susceptibility maps in four basins of Kalat-e-Naderi county, namely Archangan, Kalat, Qaratigan, and Chahchaheh basins, situated in northeast Iran. The Kalat-e-Naderi region is characterized by a partial coverage of loess. Given the agricultural significance of loess and its susceptibility to erosion, this research focuses specifically on regions covered by loess. Geographic Information System (GIS) tools, including ArcMap and Quantum Geographic Information System (QGIS), were utilized to facilitate the creation of erosion susceptibility maps. Seven factors, including slope, aspect, elevation, drainage density, lithology, the Normalized Difference Vegetation Index (NDVI), and precipitation were selected for consideration. Recognizing the variability of precipitation and vegetation cover across different seasons, seasonal data for the specified factors were employed. Consequently, erosion susceptibility maps were generated on a seasonal basis. Pairwise comparison tables revealed that precipitation, lithology, and slope emerged as the dominant factors contributing to erosion susceptibility in this region. The resultant maps distinctly delineate basins with higher precipitation values, unresistant lithology (such as loess, characterized by high porosity and permeability), and steeper slopes, exhibiting heightened susceptibility to erosion (Archangan and Kalat basins). The credibility of the research findings was examined through on-site observations. The outcomes of this study may provide pertinent insights for decision-makers and planners. This information can be effectively employed in formulating strategies aimed at conserving soil quality in areas vulnerable to erosion hazards.

Research on optimization strategies for urban park green space planning in Nanjing based on GIS from the perspectives of network analysis and Thiessen polygon theory

Urban Park green space is an essential carrier and form of urban recreation space, playing an important role in improving the ecological environment and enhancing the image of the city. With the process of urbanization and the continuous improvement of residents’ living standards, urban park construction has become increasingly important to meet people’s growing needs for a better life. However, the evaluation indicators for urban park green space in China mostly consider macroscopic levels, such as the area, number and per capita green area of parks. This cannot fully reflect the level of park green space services. Accessibility can reflect the convenience of residents to reach the park, provide guidance for the reasonable layout of parks and have various evaluation methods relying on geographic information technology. Therefore, it is necessary to quantitatively study the layout and accessibility of park green space. Taking the central urban area of Nanjing as the research object, this paper summarizes existing research and focuses on evaluating the accessibility of park green space while analyzing the layout of parks from multiple perspectives, combined with the existing pressure appraisal of park green space services. Relevant data on Nanjing, including overall planning and statistical yearbooks, were collected and analyzed using geographic information system (GIS) tools, network analysis and Thiessen polygon theory to analyze the service pressure, demand and accessibility of park green space in the central urban area under different transportation methods. Based on the results, targeted optimization strategies are proposed.

Analysis of Dieback in a Coastal Pinewood in Campania, Southern Italy, through High-Resolution Remote Sensing.

For some years, the stone pine (Pinus pinea L.) forests of the Domitian coast in Campania, Southern Italy, have been at risk of conservation due to biological adversities. Among these, the pine tortoise scale Toumeyella parvicornis (Cockerell) has assumed a primary role since its spread in Campania began. Observation of pine forests using remote sensing techniques was useful for acquiring information on the health state of the vegetation. In this way, it was possible to monitor the functioning of the forest ecosystem and identify the existence of critical states. To study the variation in spectral behavior and identify conditions of plant stress due to the action of pests, the analysis of the multispectral data of the Copernicus Sentinel-2 satellite, acquired over seven years between 2016 and 2022, was conducted on the Domitian pine forest. This method was used to plot the values of individual pixels over time by processing spectral indices using Geographic Information System (GIS) tools. The use of vegetation indices has made it possible to highlight the degradation suffered by the vegetation due to infestation by T. parvicornis. The results showed the utility of monitoring the state of the vegetation through high-resolution remote sensing to protect and preserve the pine forest ecosystem peculiar to the Domitian coast.

Defining priority areas for conservation based on multispecies functional connectivity

Habitat fragmentation poses a significant challenge to biodiversity conservation. Well-designed ecological corridors can effectively enhance connectivity between habitat areas, particularly within Protected Areas (PAs), thereby mitigating biodiversity loss. Herein, we proposed a methodological approach for identifying Priority Areas for Conservation (PACs) of biodiversity based on functional connectivity for different species of birds and terrestrial mammals. We applied the proposed methodology in a biodiverse region in Brazil that harbors a mosaic of PAs and remaining areas of natural vegetation under anthropogenic pressure, primarily from mineral extraction activities. We used ecological corridor simulations as input data and a set of geographic information systems tools to delineate the priority areas. In total, we identified 24 priority areas for the conservation of 10 bird and 5 mammal species under different extinction threat levels and preferential habitat types, which varied among seasonal semideciduous forests, savannas, and rupestrian grasslands. The sizes of the priority areas identified ranged from 834.42 to 7954.36 ha. The proposed methodology can be applied to define priority areas for biodiversity conservation at a regional scale for different species or groups of species worldwide.

Morphometric Indicators for the Definition of New Territorial Units in the Periurban Space: Application to the Metropolitan Area of Valencia (Spain)

New territorial units resulting from urban sprawl processes constitute a major challenge for territorial planning. The aim of this paper is to analyze periurban spaces, focusing on the delimitation and characterization of the urban units arising from urban sprawl processes. The delimitation derives from fractal analysis, where urbanized space is used to detect the limits of the units. The characterization starts with the calculation of eight different indicators, using Geographic Information Systems tools. PCA is used to obtain different dimensions of the urban sprawl phenomenon. Finally, a cluster analysis has been applied to establish a typology of territorial units and facilitate the comparative analysis. The methodology is applied to a case study, the metropolitan area of Valencia. Results show six groups of urbanized spaces, which present different types of urban sprawl structures with different necessities. This applied research can be useful for the spatial planning of the periurban spaces, insofar as it allows the identification of supra-municipal or infra-municipal areas, where it will be possible to improve infrastructures, facilities, or green infrastructure, to empower secondary urban nuclei and to create new inter-municipal cooperation and governance formulas. In addition, the results can constitute a non-administrative territorial basis for the calculation of land occupation indicators that are often used as thresholds for the creation of new residential spaces in regulatory planning documents.

Proximity Analysis using Weighted Product Method: Case Study for Fast-Food Restaurants

This study aims to analyze the proximity between fast-food restaurant locations and several factors to consider in opening outlets, including public facilities, roads, transportation facilities, community mobility, and distance to industrial areas. The method used in this study is the Weighted Product Method. The Geographic Information System tools are used to obtain location data and perform spatial data settings based on the reference system, as well as calculate the distance matrix between locations. The Weighted Product method is used to provide an assessment analysis regarding the factors to be considered in opening an outlet at a location.

Development of a multicriteria matrix for decision making in the management of flexible pavements in an urban road network. Case study the city of Itagüí – Colombia

Decision-making for interventions in urban road networks is often carried out reactively, addressing roads in the worst condition first, which reduces the length of intervention in the entire urban road network under an assigned budget. The objective of this work was to establish a methodology to prioritize the intervention of asphalt pavements on urban roads through a multi-criteria matrix that allows optimizing the management of pavements in the network. The criteria were previously adjusted and validated by road infrastructure experts using the Likert scale. Subsequently a large group of experts completed the multi-criteria matrix to qualify and weigh each of the criteria and intervention alternatives considered to address each of the established problems; the goal is to preserve the urban road network in good condition. With the support of Geographic Information Systems (GIS) tools, each criterion was represented by a vector shapefile format, each of them was transformed into raster format and reclassified to assign a specific score. The attributes of the raster format used information from the road network of the city of Itagüí (Colombia). The final result was the weighted overlay of maps that allowed establishing the prioritization of the roads to intervene according to the score obtained in each road segment, which allows the administrator to make efficient decisions in an urban network.

Assessing forest changes in Yok Don National Park and surrounding areas, Dak Lak province, Vietnam

Forests serve as vital ecosystems, playing a pivotal role in preserving biodiversity, maintaining air and water quality, and regulating the climate, all while delivering many benefits to humanity and serving as a critical resource for diverse industries. This study investigated changes in forest cover within Yok Don National Park and surrounding areas in Dak Lak province, Vietnam, over the period from 2001 to 2021. The primary objective was to identify decadal shifts in forest cover through the utilization of freely accessible satellite remote sensing data and geographic information systems (GIS) tools. The maximum likelihood classification technique was employed to categorize Landsat images captured in 2001, 2011, and 2021. Furthermore, we evaluated the efficacy of the Normalized Difference Vegetation Index (NDVI) and the Soil-Adjusted Vegetation Index (SAVI) based classifications in detecting forest cover changes when compared to supervised classification. Initial estimates placed forest cover at 2796.91 km2, constituting 88.44% of the total land area in 2001, which subsequently declined to 2609.97 km2 (82.53%) in 2011, and further reduced to 1843.57 km2 (58.29%) in 2021. Severely reduced forest cover is often associated with the expansion of agriculture on the forest edge; other contributing factors include logging and illegal production land. Notably, the NDVI outperformed the SAVI in detecting forest cover changes. The findings of this research are anticipated to contribute to ongoing studies and enhance the effective monitoring of this protected forest area, thus providing invaluable insights for decision-makers.

Diachronic Study of Coastal Vegetation Cover in Al Hoceima (Morocco): A Geospatial Analysis Using Remote Sensing and GIS

Coastal ecosystems are vital land-sea interfaces that are necessary to sustain environmental stability and biodiversity. In many places, the complex network of vegetation cover serves as an essential buffer, preventing erosion, sustaining a variety of habitats, and enhancing ecological resilience overall The study utilizes advanced technologies like GIS, remote sensing, and Landsat images to analyze vegetation changes in Sfiha and Swani's coastal regions over the past 18 years, aiming to understand the impact of land use, climate fluctuations, and human activities on the landscape, Sophisticated remote sensing technology, Landsat satellite images, and Geographic Information System (GIS) tools are among the materials employed. During the designated period, the proportions of changes in the plant cover in the research area are determined and interpreted with the help of these resources. The study reveals significant changes in vegetation cover in Sfiha and Swani, revealing patterns of 21% (2003), 25% (2010), 33% (2015), and 15% (2021), providing insight into the temporal evolution of the coastal ecosystem and influencing conservation strategies and sustainable management practices. This study underscores the broader relevance of employing advanced spatial technologies for the monitoring and management of coastal ecosystems.Introduction