Increase In Built-up Area Research Articles

Changes in the Patterns of Population Distribution and Built-Up Areas of the Rural–Urban Fringe in Post-Socialist Context—A Central European Case Study

The rapid and significant expansion of urban areas is observed worldwide; however, considerable differences are detected within the characteristics of the process. The rural–urban fringe is changing most dynamically from the aspect of land use and this tends to be relevant in the case of post-socialist cities in Central Europe even with a stagnating or decreasing population. Debrecen (Hungary) and its hinterland adequately represent the migration trends of Hungarian cities and the great administrative area provided wide intra-urban suburbanization processes. The current study put the emphasis on the analysis of the spatial pattern of built-up areas and the distribution of residents. In order to discover the processes of the post-socialist transition period, detailed point layers were created to illustrate every built-up parcel in the rural–urban fringe of Debrecen (for the years 1980, 2000, and 2020). The most important characteristics were discovered with the help of GIS methods—Kernel-density, grid pattern analysis of the object density, and analysis of land cover/land use changes using Corine Land Cover Change (CLCC) databases. The dynamic and extended expansion of built-up areas was seen until 2000, in which the outskirts (including hobby gardens) densified spectacularly. The urban sprawl has been less intensive since the millennium and the increase in built-up areas has become more concentrated. As a consequence of the transition period, extended territories—primarily the least dense parts of the rural–urban fringe—are faced with the disappearance of buildings due to agricultural cultivation reasons.

The extent, perceived causes and impacts of land use and land cover change in Tyhume Valley, South Africa

There is limited knowledge on how people living in communal areas perceive land use and land cover (LULC) change and the impacts it has on sustainable access to essential ecosystem goods and services. This study used seven wet season Landsat images covering 1989 to 2019 and the Extreme Gradient Boosting algorithm to map LULC in Tyhume Valley, South Africa. Analyses of trends in LULC and long-term changes in rainfall over the same period were based on the Mann Kendall (MK) statistical technique. Perceptions on the causes and impacts of the observed trends were solicited from 102 respondents and summarized through frequency analysis. Major trends that emerged from image-based analysis include the expansion of Vachellia karroo by 25% (τ = 0.98; p = 0.004), decrease in pastureland by 18% (τ = –0.90, p = 0.007), decrease in cropland by 9.6% (τ = –0.90, p = 0.007), decrease in surface water by 1.1% (-0.90, p = 0.007), and increase in built-up area by 2.5% (τ = 1.00, p = 0.003). Perceived causes of these trends include the eradication of land access control systems, poor management of surface water, lack of farmer support programs, and 14 years of negative rainfall anomalies. The impacts of these changes include long-distance trekking of animals to pastures and watering points, increased livestock malnutrition and mortality, decline of medicinal and culturally significant trees, increased purchasing of stock feed, increased unemployment, and consumption of unhealthy food. The study concludes by highlighting the need to accommodate local perceptions in the formulation of policies and practices for sustainable use of ecosystem services.

Simulation-Based Optimization of the Urban Thermal Environment through Local Climate Zones Reorganization in Changsha City, China with the FLUS Model

Urbanization leads to changes in surface landscapes, such as the increase in built-up areas and the decrease in natural elements, resulting in local changes in land surface temperature, which often create unusually hot weather and affect livability, especially for mid- and low-latitude cities. Therefore, optimizing urban landscapes and adjusting the thermal environment is especially important to improve comfort and to achieve sustainable urban development. Existing studies on optimizing landscapes have considered mainly horizontal land uses/land covers but ignored their elevation. This study considered local climate zones as basic units to describe three-dimensional landscapes; we measured the relationship between local climate zones and land surface temperature, based on which the research further used a genetic algorithm and future land-use simulation models to optimize the spatial layouts of local climate zones in Changsha, China, considering multiple objectives including adjusting land surface temperature without affecting population carrying capacity, economic development, watershed protection, and forest and grass protection. According to the optimization results, the area of open low-rise buildings increased by 5.98% after optimization, and dense trees decreased by 7.64%; open low-rise buildings were suggested to be newly built in the city center and sparsely buildings should be developed in the surrounding administrative district far away from the city center. The optimization results contributed to a −5.2 °C reduction of average land surface temperature, which could significantly improve the thermal environment under the premise of ensuring the population and economic development levels and thus serves as a novel solution for improving urban landscapes to implement sustainable city development.

Future prediction of scenario based land use land cover (LU&LC) using DynaCLUE model for a river basin

Human activities that cause changes to the surface of the Earth lead to alterations in Land Use and Land Cover (LU&LC) which have an impact on biodiversity, ecosystem functioning, and the well-being of humans. In order to comprehend and manage the effects of human activities on the environment, prediction of scenario-based LU&LC in future periods are crucial. Scenario-based predictions of LU&LC provide valuable insights for decision-makers in the sustainable governance of land and water resources. In the present study, the Dynamic Conversion of Land Use and its Effects (DynaCLUE) modelling platform was used to predict future LU&LC for Munneru river basin, India. Using six different user defined scenarios LU&LC change patterns were analyzed in 2030, 2050 and 2080 so as to understand the pressure on the natural resources and to plan sustainable Land Use Planning by preserving the important land use classes. The connection between LU&LC classes and input driving factors was quantified using Binary Logistic Regression (BLR) analysis. The β-coefficient was estimated using LU&LC type as a dependent variable and driving factors as independent variables. The demands of each LU&LC type, spatial policies and constraints, characteristics of each location and land use conversions are used as inputs for prediction of future LU&LC maps. Major conversions in LU&LC observed in this basin from last two decades are the rapid increase in built-up area due to urbanization in the outskirts of cities and towns. The major LU&LC changes projected for the period of 2019–2080 are expansion of built-up area ranging from 42.5% to 88.5%, and a reduction in barren land ranging from 57.3% to 74.5% across all six scenarios in the entire basin. The projected LU&LC maps under different scenarios provide valuable insights that could aid local communities, government agencies, and stakeholders in systematically allocating resources at the local level and in preparing the policies for long-term benefits.

Spatiotemporal Analysis of Land Use Land Cover Mapping and Change Detection in Dambatta Local Government Area

This research studied the spatiotemporal changes in land use (LU)/land cover (LC) in Dambatta local government area, with a view to identifying the effect arising from the observable changes in land use patterns. The imageries used in the study were obtained from the National Space Research and Development Agency (NARSDA), Abuja. Spatial analytical techniques and descriptive statistical techniques were employed to analyze the data. The results showed 66.8% reduction in agricultural lands, 45.5% reduction in vegetation cover, 223.2% increase in built-up areas, 269.1% increase in bare lands and 70% increase in water bodies within the 20 years. Spatio-temporal analysis of the three imageries revealed that agricultural lands were largely been taken over by urbanization while vegetation had rapidly given way to bare lands within the 20 years. It was observed that these changes resulted from anthropogenic activities, environmental factors and climate change. These result in the loss of farmlands, inadequate food supply, unemployment, inadequate industrial raw materials, reduction in revenue generated, forest depletion, desertification, wildlife extinction and temperature increase. While it is recommended that reforestation, land reclamation and irrigation agriculture should be promoted in the area, it is also suggested that further research should focus on the impact of climate change on land cover change in the area.

Morphometric analysis and land use-occupation in the Campestre creek watershed in the city of Lins, São Paulo State, Brazil.

The increased demand for natural resources, economic growth and graph growth can influence the reduction of individual land use coverage, which makes water infiltration difficult. The objective was to evaluate, through the morphometric parameters and land-use occupation, the flooding susceptibility in the Campestre creek watershed. An analysis of the morphometric indexes was performed with the help of the tools presented in the SPRING 5.4.3 software. The characteristics of land use and occupation were identified by the of classification by regions, using images from three different periods: 1990, 2005 and 2021. The satellite images used were LANDSAT 5, TM sensor and LANDSAT 8, OLI sensor, and finally, as an auxiliary project to the study, Numerical Terrain Modeling data from the SRTM Project was used, with a spatial resolution of 30 meters. The morphometric results show that the Campestre creek watershed has a circular shape and straight channels, which contributes to the classification of medium-high susceptibility to floods and inundations. There was a 13% increase in built-up areas in regions that were previously water and vegetation, from 4.2 km² to 4.87 km² in 2021. The reduction of permeable areas makes it difficult for water to infiltrate, contributing to the occurrence of floods and inundations.

The Impact of the Trans-Java Toll Road Development on Spatial Planning in the Northern Region of Java Island: A Study Utilizing NDBI and Google Earth Images

The primary objective of toll roads is to stimulate economic growth. As the pivotal road network on Java Island, the Trans-Java Toll Road has a significant impact on regional development and spatial planning. However, there has been a lack of research focusing on the specific influence of this toll road on spatial planning. Therefore, this study aims to comprehensively examine the spatial and temporal implications of the Trans-Java Toll Road. To achieve this goal, the Normalized Difference Built-Up Index (NDBI) method is employed using satellite imagery. This method is widely recognized for its effectiveness in detecting changes in built-up areas through remote sensing techniques. The calculated NDBI values reveal substantial expansion of built-up areas in the cities and regencies traversed by the Trans-Java Toll Road. Notably, two specific areas with the highest rates of change are investigated: Gresik Regency and Bekasi Regency, where the built-up areas have experienced remarkable growth of over 186.9% and 61.8% respectively over a five-year period. To validate these findings, Google Earth imagery is utilized for two different years, namely 2016 and 2021. The observed changes in these regions are predominantly attributed to the economic growth facilitated by the establishment of industrial areas. Consequently, the expansion of industrial zones and settlements has resulted in a notable reduction in wetland areas and a simultaneous increase in built-up areas.

Spatiotemporal Land Use Changes in Remote Rural Regions of India Between 2000 and 2020

This study tracks the spatiotemporal changes in high-population growth and high-density rural regions of India, also called ‘urural’. The urural areas are remote, high-density rural areas far from zones of urban influence. Deriving the land use and land cover changes from the Global Land Cover and Land Use Change dataset and analysing them in the most populated and dense districts, the study confirms the hypothesis that land uses are continuously changing and have accelerated in high population growth and density in rural districts in India. The findings demonstrate significant changes in land use patterns in the last two decades, that is, 2000–2020, particularly in the last decade. Almost all physical changes, such as an increase in built-up areas, a reduction in agricultural lands, and depletion in vegetative cover and water bodies, were significant. This means that high population density, combined with population pressure in remote rural regions, is a leading contributing factor to considerable land use transformations, essentially turning them into areas with urban characteristics, that is, making them urural.

Land Surface Temperature in an Arid City: Assessing Spatio-temporal Changes

The sprawl of urban areas and its consequent alteration of the Earth’s surface lead to problems with rising temperatures. This research aims to assess the urban cold/heat island phenomenon and driving factors that currently affect the Land Surface Temperature (LST) pattern of a city in a desert environment (Tulum Valley, Argentina). We selected 50 points for the urban class and 49 points for the rural class. The LST data was obtained for cold and warm periods of the years 1988, 2000, 2010, and 2021. For each study year, the median (annual), minimum (of cold period), and maximum (of warm period) LST values were calculated in 90 × 90 m moving windows (3 × 3 pixels). As driving factors, we assessed vegetation areas, built-up, and bare soil areas, taking into account their spatial abundance (median values), and heterogeneity (standard deviation) in the same moving windows. The Tulum Valley behaved like an UCI in almost every year studied. In the urban class, the LST was positively affected by vegetation during the cold period, whereas in the rural class, it was explained by a negative relationship with vegetation and a positive one with built-up areas. In the urban class during the warm periods, LST had a negative relationship with heterogeneous areas of bare soil and vegetation. Conversely, an increase in built-up areas caused a rise in LST, both in urban and rural classes. Different drivers affected the LST pattern in the Tulum Valley; moreover, these drivers explained more variability in the rural than the urban class.

Changes in landscape structure and ecosystem services since 1850 analyzed using landscape metrics in two German municipalities

Land use has fundamentally altered landscape structure and ecosystem service provision over the last century in central Europe and worldwide. In this study, we analyzed long-term changes in landscape structures and ecosystem services in two case study areas in Germany in 1850 and 2018. First, we reconstructed land use changes using historical and current serial cadastral maps, historical documents, and digital aerial photographs. Second, we analyzed landscape structure by calculating select landscape metrics for several land-use types in both case study areas and time steps. Land use analysis for the first case study in the intensively used agricultural area of Jesewitz (Saxony) showed a significantly decreased percentage of grassland from 9.2% (in 1850) to 3.9% (in 2018) and an increase in built-up areas from 1.2% to 3.8%. For the second study area, located in the mountainous region of Ilsenburg, Harz (Saxony-Anhalt), the analysis revealed a stable forest area of 78% at both time steps. Grasslands dominated the non-forest areas and showed a significant decrease in area from 53.2% (in 1850) to 19.6% (in 2018). The settlement area increased markedly from 1.8% to 16.4%. Business and industrial areas also increased significantly from 0.9% to 10.0%. The present study shows that the risk of soil degradation caused by erosion has increased significantly since 1850. Furthermore, the risk of biodiversity loss has increased significantly owing to habitat degradation and devastation of vegetation structures. Moreover, the results showed that changes in landscape structure adversely affected the availability and quality of ecosystem services.

Assessing landscape fragmentation due to urbanization in English Bazar Municipality, Malda, India, using landscape metrics

Urbanization in India is having a significant impact on the environment and human health, as built-up areas are expanding while vegetation and water bodies are declining. To mitigate the negative effects of urbanization, there is an urgent need to monitor and manage the growth of cities through the creation of smart cities. Accurately identifying and mapping urban expansion patterns is crucial to achieving this goal, but this is currently lacking in India. To address this gap, this study takes a comprehensive approach to examining the processes of urban expansion in English Bazar Municipality, Malda, India. The study employs the random forest (RF) method for land use and land cover (LULC) mapping for the years 2001, 2011, and 2021 and then uses the frequency approach, landscape homogeneity, and fragmentation to model urban expansion over the same time period. The study also employs several landscape matrices to quantify urban expansion. The results of the study reveal a substantial increase in built-up areas from 601.26 hectares in 2001 to 859.13 hectares in 2021, accompanied by a corresponding decline in vegetation, cropland, and open land. This land use transition process has also led to increased fragmentation of the landscape. The spatiotemporal landscape homogeneity analysis identifies two transition zones (zone 2 and zone 1) surrounding the stable zone, which capture the new, small, isolated built-up areas and show a progression of urban expansion from 2001 to 2021. Overall, the study provides valuable insights into the changes in urban expansion and fragmentation in English Bazar Municipality. To promote sustainable urban development and enhance the quality of life for residents, it is important for stakeholders and the government to prioritize the conservation and creation of green and blue spaces. This can be accomplished through the incorporation of green infrastructure, smart city principles, community engagement and education, and partnerships with local businesses.

Assessment of Ecosystem Service Value in Response to LULC Changes Using Geospatial Techniques: A Case Study in the Merbil Wetland of the Brahmaputra Valley, Assam, India

The alteration of land use and land cover caused by human activities on a global scale has had a notable impact on ecosystem services at regional and global levels, which are crucial for the survival and welfare of human beings. Merbil, a small freshwater wetland located in the Brahmaputra basin in Assam, India, is not exempt from this phenomenon. In the present study, we have estimated and shown a spatio-temporal variation of ecosystem service values in response to land use and land cover alteration for the years 1990, 2000, 2010, and 2021, and predicted the same for 2030 and 2040. Supervised classification and the CA-Markov model were used in this study for land-use and land-cover classification and future projection, respectively. The result showed a significant increase in built-up areas, agricultural land, and aquatic plants and a decrease in open water and vegetation during 1990–2040. The study area experienced a substantial rise in ecosystem service values during the observed period (1990–2021) due to the rapid expansion of built-up areas and agricultural and aquatic land. Although the rise of built-up and agricultural land is economically profitable and has increased the study site’s overall ecosystem service values, decreasing the area under open water and vegetation cover may have led to an ecological imbalance in the study site. Hence, we suggest that protecting the natural ecosystem should be a priority in future land-use planning. The study will aid in developing natural resource sustainability management plans and provide useful guidelines for preserving the local ecological balance in small wetlands over the short to medium term.

Analyzing the Spatio-temporal Changes in the Hasdeo Subbasin in Chhattisgarh Using Sentinel-2 Imagery

Understanding the dynamics of the world's landscapes is made possible by the multi-temporal change detection analysis made possible by Remote Sensing (RS) and GIS technologies. The current study provides an illustration of the spatiotemporal changes in land use land cover (LULC) of the Hasdeo subwatershed, Chhattisgarh, India, between 2016 and 2019 using Sentinel-2 imagery. To quantify the changes in the LULC area from 2016 to 2019, Sentinel-2 images from 2016 and 2019 were obtained. With the ERDAS Imagine software, the supervised classification method has been used. Eight different LULC classes, including forest, cultivated land, fallow land, water body, barren land, built-up land, mining and sand, were created using the image data of the research area. The outcome shows that between 2016 and 2019, there was an increase in built-up area and water body, while there was a decline in cultivated land, forest, and barren land. Kappa Coefficient accuracy is 88.00% and overall accuracy is 92.1% according to the LULC accuracy assessment for the data analysis. The paper's data base emphasises the significance of change detection approaches for spotting significant changes in land cover and for tracking the effects of human-induced change on the hydrological environment, behaviour, and setting of the Hasdeo sub watershed.

Impacts of land use change on landscape structure and eco- system services at local scale: A case study in central Portugal

This study aims to evaluate land use and land cover (LULC) changes and associated impacts in the landscape structure and ecosystem services (ES) value in Lousã municipality, in Central Portugal. The results show that signif- icant changes in LULC were recorded over the study period (1974–2018). Agricultural abandonment, expansion of woodland due to the promotion of the eucalyptus (EU) monoculture (chiefly Eucalyptus globulus), the invasion of exotic species (mainly Acacia dealbata) and the increase of built-up areas are the most significant changes that have shaped the landscapes of the study area. The analysis also revealed that the mean patch size has decreased whereas the number of patches increased. The results showed that although the EU and deciduous forest (DF) increased the ES value, the overall total ES value fell around 10% between 1974 and 2018, mainly due to the decrease in the supply of agricultural goods. Studies of this kind on local rural landscapes are vital when it comes to devising appropriate land management policies for the landscape level by considering the interaction between each element for sustainable development.

Analysis of land cover land use change in the greater Gaborone area of South Eastern Botswana

Changes in land cover land use (LCLU) have long been considered to be among the many factors responsible for global environmental challenges. This study focused on assessing LCLU changes in the Greater Gaborone area of South Eastern Botswana between 1988 and 2022. The study employed remote sensing (RS) and geographic information systems (GIS) tools for analyzing LCLU changes in the study area during the study period. Landsat images of 1988 and 2002 and Sentinel-2A images of 2022 were used to detect LCLU changes. Image classification was done using a Supervised classification approach based on a Maximum Likelihood Classifier. Six LCLU types such as water body, trees dominated, cropland, shrubland, bare land, and built-up, were identified in the area. Post Classification Comparison (PCC) approach was used to detect LCLU change during the study period. Shrubland class was found to be the dominant LCLU type in the study area. A significant gain was observed in the built-up class (75.12 km2), while significant losses were observed in shrubland (24.16 km2) and trees dominated (33.32 km2) classes in the entire study period. Given the rapid increase in built-up areas, this recommends that land managers and policymakers should invest in implementing sustainable land management interventions to prevent undesirable LCLU changes.

Temporal changes in Land Use and Land Cover (LULC) and local climate in the Krueng Peusangan Watershed (KPW) area, Aceh, Indonesia

Watersheds are important sources of various ecosystem services. The Krueng Peusangan Watershed (KPW), one of the watersheds in Aceh Province, is expected to become the "lungs" of the ecology of the north-central part of Aceh. Currently, the KPW is one of the watersheds that suffers from severe or critical damage, especially that caused by changes in forest cover. Spatiotemporal monitoring of changes in landscape patterns (composition and configuration) is needed to inform policy and support planning for sustainable watershed management. This study aims to: 1) determine the pattern of changes in LULC in KPW in two decades (1999–2009 and 2009–2019, and 2) determine the impact of changes in the LULC pattern on the local climate. Landsat Satellite Imagery for three years (1999, 2009, and 2019) is used to classify LULC. Geographic Information System (GIS) technology and remote sensing are used to analyze it. Each satellite image is classified into six categories: built-up area, forest, agriculture, bare land, wetland, and water body. This classification resulted in LULC maps for 1999, 2009, and 2019 with kappa coefficients of 0.84, 0.88, and 0.84. It is found that between 1999–2009 and 2009–2019, there has been a consistent decrease in forest cover area and an increase in built-up area. Local climate change is also occurring in this KPW. Continuous monitoring of LULC changes in KPW is also necessary to keep management planning up to date.

A Spatio-Temporal Analysis of Heat Island Intensity Influenced by the Substantial Urban Growth between 1990 and 2020: A Case Study of Al-Ahsa Oasis, Eastern Saudi Arabia

Rapid urbanization has recently led to a significant propagation of heat islands. This study aimed to analyze the spatio-temporal variation in urban heat islands (UHIs) at Al-Ahsa Oasis in Saudi Arabia, in addition to exploring the urbanization influence on UHI distribution over the last 30 years. The spatial variability in UHIs was assessed, the key determinant elements were identified, and the forms of distribution were delineated. Change detection, hot spots, and spatial autocorrelation were employed to study UHI distribution and intensity and to identify the clustering and correspondence between heat and urbanization. The results revealed a considerable increase in built-up areas from 17.15% to 45.8% of total land use/cover (LULC) from 1990 to 2020. No significant variations in UHI intensity were observed (10.4 °C in 1990 and 8.7 °C for 2020). However, a remarkable link was found between urbanization and heat, confirmed by hot spot clustering over intense urban complexes, while cold spot clustering was observed over date and palm tree areas, with 99% confidence for both. Lastly, the link between temperature and urbanization was also confirmed through spatial autocorrelation, producing Moran’s indices of 0.41 and 0.45 for 1990 and 2020, respectively, with an overall significance (p-value) of 0.001. The mechanisms applied have proven their robustness in assessing the effect of urbanization on heat island distribution and quantification.

The factors driving land cover transitions and land degradation and the potential impacts of the proposed developments in the Isiolo dam watershed, LAPSSET corridor, Kenya

Isiolo dam is planned to be constructed along the Ewaso Nyiro River to provide water to the planned Isiolo resort city, one of the Lamu Port and Southern Ethiopia Transport (LAPSSET) corridor projects. This paper evaluates the factors driving land cover transitions and their effects, as a consequence of the proposed infrastructure developments with a view to providing evidence-based information for formulating policies and approaches for sustainable land management and development. Landsat images were used to assess Land Use and Land Cover (LULC) change, while land degradation was evaluated based on the United Nations Convention to Combat Desertification guidelines (2000–2020). Spatial overlays of land degradation, LULC change, population, and land tenure were performed to establish their interrelations. The results revealed that water, bareland, built-up, and forest increased by 2043%, 83%, 35%, and 17%, respectively, while shrubland and cropland decreased by 26% and 6%, respectively. Further, 61% of the watershed remained stable, 31% experienced degradation and 8% improved. The main drivers of LULC transitions, and land degradation are population pressure, land tenure, climate change and economic growth. With the development of the LAPSSET projects, it is projected that built-up areas, cropland, and bareland will increase mainly due to population increase, while the forest and shrubland will reduce mainly as a consequence of an increase in built-up areas and potentially poor land management. To achieve sustainable development with net zero loss of natural resources, proper planning for economic investments as well as inclusive land-use planning should be enhanced in drylands such as the Isiolo watershed and similar landscapes.

Forecasting land use and land cover dynamics using combined remote sensing, machine learning algorithm and local perception in the Agoènyivé Plateau, Togo

Knowledge of land use and land cover (LULC) dynamics helps policymakers set sustainable land management plans. Population growth, migration, and rural exodus have led to spatial expansion in many cities worldwide, especially in coastal urban settings. This research aims at assessing and predicting LULC over the Agoènyivé plateau (AP) in Togo, using remote sensing and Markov Chain along with local perceptions on LULC change, thus considering four scenarios (i.e., Business-as Usual, afforestation, wetland policy, and building policy). LULC was classified based on the maximum likelihood algorithm using Landsat images. The future scenarios maps were produced using the Multilayer Perceptron (MLP) neural networks-Markov chain modelling approach by considering five driver variables considered to affect future development. The historical change analysis was performed for the periods of 1986–2001, 2001–2011, and 2011–2020, while 1986–2020 was used for model validation and change prediction. Image accuracy assessment was performed using the error or confusion matrices, kappa coefficients (Kscores), Relative Operating Characteristics (ROC), and accuracy scores, with an overall accuracy (Kappa coefficient) of 87% (0.81), 88% (0.81), 90% (0.82), and 92% (0.84) for the years 1986, 2001, 2011, and 2020, respectively. The results showed an increase in built-up areas (38.71% land gain), while a decrease was observed in mixed vegetation/savannah (22.69% land loss), croplands/bare surfaces (22.89%), and wetlands (3.36% land loss) over the period of 1986–2020. An increase in built-up areas (7.79% and 19.79% land gain by 2030 and 2050, respectively) and a decrease in mixed vegetation (1.13% and 2.54% land loss by 2030 and 2050, respectively), croplands and bare surfaces (6.58% and 16.98% loss by 2030 and 2050, respectively), and wetlands (0.13% and 0.31% loss by 2030 and 2050, respectively), are expected under the BAU scenario. Contrary to the wetland policy, which induces change only in the wetlands (0.02% and 0.047% land loss by 2030 and 2050, respectively), the afforestation scenario results in a gain in forest/savannah (0.11% and 0.73% land gain by 2030 and 2050 compared to the BAU scenario), but also a decrease in croplands/bare surfaces (0.64% by 2050 compared to the BAU scenario), whereas the building policy scenario results in a long-term increase in croplands/bare surfaces (2.88% by 2050, compared to the BAU), and wetlands (0.027 and 2.88% by 2050) in addition to the mixed vegetation/savannah. LULC dynamics (including future urbanization trends) for the AP under various scenarios is a step ahead of time, highlighting the importance of the implementation of existing laws and policies, but also providing information to deal with the observed inharmonious spatial development of urban centres, and serving as a dataset source for LULC change impact assessments on related resources.

Interrogating the Impact of Land Use/Land Cover Dynamics in Mbarara City in Southwestern Uganda

The urbanization in Mbarara City Southwestern Uganda has increased the number of built-up and small-scale agricultural areas thus escalating pressure on the grassland and woodlot areas hence influencing land fragmentation and slum development. In this study, we focused on land use/land cover dynamics. This helped us to identify land uses that reduce grassland areas, which increases land fragmentation, and slum development. Presumably, the land uses in the area included built-up areas, grassland, small-scale agriculture, and woodlots. Built-up, grassland, and small-scale agriculture were vital for our analysis. We employed remote sensing techniques (Supervised-Maximum Likelihood Classifier) with two cloud-free high-resolution images of 2010 and 2022 in mapping spatial-temporal patterns in built-up, grassland, and small-scale agriculture. Our results evidenced that built-up area increased by (5.14%), grassland declined by (7.1%), small-scale agriculture increased by (2.62%), and woodlots reduced by (0.73%) between 2010 to 2022 and the accuracy assessment for the image classification was (83%). Our study found that an increase in built-up areas and small-scale agriculture led to the decline of the grassland and woodlot areas between 2010 to 2022 with a statistically significant difference (p = 0.03). There was also a strong positive correlation (r = 0.97) between land use/land cover types in 2010 and 2022. Our study recommends that Mbarara City Authority should put strict laws and regulations governing the minimum size of land required during sub-division to avoid land fragmentation which results in increased slum development. Increased land fragmentation may have an intense impact on important ecosystems such as grasslands.