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The research on cold-formed steel (CFS) built-up columns, which has grown over the past decade, has been instrumental in developing new CFS built-up columns with transversely spaced chords, demonstrating better axial performance than conventional I-type built-up columns. However, previous research findings on CFS laced columns have been limited, with no data available on stub columns. This paper presents the first test program for cold-formed steel laced stub columns using plain channels. The program involved fabricating 12 specimens with a single lacing configuration, connecting lacing elements and end plates to the chords using self-drilling screws, and evaluating the impact of critical parameters on column performance under concentric axial loading. Important variables such as lacing slenderness, end plate length, and transverse chord spacing were examined, with the built-up section's aspect ratio varying from 0.75 to 1.25. The failure modes, peak strengths, and load-displacement curves of the stub column specimens were used to evaluate their performance. In addition, the study compared strength predictions from the current American Iron and Steel Institute (AISI S100-16) and Eurocode (EN1993-1-3) standards against the test strengths. Unlike slender column axial strength, these current standards predicted the axial strengths of the stub columns better, with an overprediction of less than 5%. It was verified that lacing slenderness and end plate length variation does not change the failure mode in CFS laced stub columns. Further, earlier recommendations on end plate length for CFS laced columns cannot be extended to CFS laced stub columns. [ABSTRACT FROM AUTHOR]

In this study, we introduce two spatial approaches to enhance semantic segmentation accuracy in remote sensing imagery in resource-constrained computational environments, with a focus on edge regions. The first approach, Contextual Bands Addition, integrates overview, incorporating essential contextual information. The second approach, multi-look inferencing, utilises multiple spatial perspectives to refine segmentation. Our results show significant improvements: Contextual Band Addition with tile overlaps increases IoU scores by 4–5%. Multi-look inferencing enhances IoU scores by 2.5% post-training. Combined, these strategies yield a 6–7% overall performance boost, valuable for semantic segmentation on limited training samples from satellite imagery datasets. [ABSTRACT FROM AUTHOR]

Cold-formed steel (CFS) sections have become popular in construction due to several advantages over structural steel. However, research on the performance of galvanized iron (GI)-based CFS under high temperatures, especially regarding its flexural behavior, has been limited. This study extensively investigates how GI-based CFS beams with varying spans behave under elevated temperatures and subsequent cooling using air and water. This study examines the impact of temperature loading and compares the effectiveness of air- and water-cooling methods. Experimental results are validated and analyzed alongside findings from finite element modeling (FEM) using ABAQUS (2019_09_13-23.19.31) and the Direct Strength Method (DSM). Additionally, this study conducts a parametric investigation to assess how beam span influences flexural capacity. Among beams heated to the same temperature, those cooled with water show slightly lower load capacities compared to those cooled with air. The highest load capacity observed is 64.3 kN for the reference specimen, while the lowest is 26.2 kN for the specimen heated for 90 min and cooled with water, a 59.27% difference between them. Stiffness decreases as heating duration increases, with the reference section exhibiting significantly higher stiffness compared to the section heated for 90 min and cooled with water, with a 92.76% difference in stiffness. As heating duration increases, ductility also increases. Various failure modes are observed based on different heating and cooling conditions across different beam spans. This study provides insights into how GI-based CFS beams perform under temperature stress and different cooling scenarios, contributing valuable data for structural design and safety considerations in construction. [ABSTRACT FROM AUTHOR]

This study estimates the spatial changes in Minna's built-up areas. For change detection and urban growth analysis, the topographical map of Minna in 1972, the township map for 1979, and the satellite imageries covering 1986, 1996, 2006, and 2015 were all employed. These maps were georeferenced using ArcGIS 10.3. The study reveals as follows: 1972 (468.3 hectares); 1979 (893.7 hectares); 1986 (4,579.8 hectares); 1996 (5,205.4.5 hectares); 2006 (8,505.1 hectares); and 2015 (19,777.2 hectares). The land consumption rates were estimated as 0.0084, 0.0117, 0.0356, 0.0215, 0.0204, and 0.0273, respectively.We conclude that strategies birthed by systematic planning conclusions must guide cities. [ABSTRACT FROM AUTHOR]

Wildfires present a significant risk to societies globally due to population growth, concentrated activities, climate change, and extreme environmental conditions. To establish effective fire suppression and management policies, it is crucial to determine whether the distance between ignition points and urban areas is increasing or decreasing. This study analyzes 101,597 fires in Spain and California between 2007 and 2015, where ignition points and all built-up areas were precisely geolocated in 2014. The study employs the Mann–Kendall test to determine trends and analyze the relative distance of wildfires to human buildings over time. The results indicate that wildfires are becoming statistically significantly closer in several areas. It is also observed that the majority of wildfires are moving away from buildings, although this is not a significant finding. These results suggest the possibility of further research into the reasons behind these observations and possible future developments and their consequences. [ABSTRACT FROM AUTHOR]

Anthropogenic activities have significantly changed global land use land cover (LULC), especially in areas with extreme population expansion and climate change. Remote sensing and the geographic information system are popular methods for keeping track of LULC changes. This research analyzed historical changes and predicted future patterns of LULC in Chittagong Metropolitan City, Bangladesh. LULC maps were created using the semi-automated classification plug-in in QGIS, which was used to classify the satellite images from 1990 to 2020. Eight distinct LULC groups, including (i) agricultural land, (ii) fallow land, (iii) trees outside of forest, (iv) hill vegetation, (v) mangrove, (vi) built-up, (vii) pond/lake, and (viii) river, were used to classify the images. The generated LULC maps showed the changes in the area from 1990 to 2020 in several classifications, showing increases in built-up, pond/lake, and river waterbodies of 278.5, 407.69, and 10.07%, respectively. However, a significant decline was observed in agricultural (61.64%), hill vegetation (43.26%), mangrove forest (30.7%), fallow (22.02%), and Tree Outside of Forest (TOF) land (8.81%). The LULC changes between 2020 and 2035 were predicted using the cellular automata-artificial neural network (CA-ANN) model. The prediction maps from 2020–2035 illustrated increasing trends of built-up land (+ 15.65%) and decreasing trends of all other LULC types, predominantly, agricultural (−3.53%), fallow (−3.13%), trees outside of forest (−6.53%), and pond/lake (−1.44%). The findings of this research may be helpful to design future strategies for sustainable landscape management and help decision-makers in government make better choices for the environment and the ecosystem. [ABSTRACT FROM AUTHOR]

Monitoring land use, buildings, and vegetation index of ecotourism areas in North Halmahera can support planning space utilization in urban areas for tourist areas as the concept of land use management and urban planning. This study offers ideas for analyzing the distribution of buildings, vegetation index, and land use in the mangrove ecotourism area of North Halmahera Regency using the spatio-temporal analysis method. The spatio-temporal analysis method comprises several stages: data selection, preprocessing, data integration, spatial analysis, temporal analysis, spatio-temporal analysis, data visualization, interpretation and understanding, and data visualization. The results of this study show that changes in the livelihood strategy of local people, from farmers and fishermen to traders, also affect land use patterns, from agricultural activities to economic activities, which triggers an increase in the number of buildings for production activities to product distribution. The implications of these findings on ecotourism development programs and policies and infrastructure development in the North Halmahera Regency are to consider community livelihoods and space or land use behavior in ecotourism areas based on vegetation, soil, and building index values. Thus, the intensification of building distribution and changes in vegetation index values from 2013-2023 reflect changes in people's livelihood strategies from agrarian activities to trade and from fishermen's activities to tourism transportation service providers. [ABSTRACT FROM AUTHOR]

New Yogyakarta International Airport (NYIA) in Kulon Progo Regency was developed with the primary objective of fostering economic growth. The initiation of operations at NYIA in March 2020 triggered substantial urban development in the surrounding area. This research aims to monitor the changes in land cover and predict development of urban areas. The research methodology comprised the use of Random Forest, Classification, and Regression Tree machine learning algorithms to create land cover maps. It also incorporated Cellular Automata (CA), which was used to make prediction related to land development. The results showed that the land cover map had an overall accuracy level of above 0.80. Furthermore, it was observed from the results of the time series land cover analysis that there was a rapid growth in built-up lands. Between 2013 and 2017 these lands expanded by 572.38 hectares and further increased by 268.97 hectares from 2017 to 2023, leading to the conversion of 571.64 hectares of agricultural lands. Based on these findings, it was projected that by 2033, there would be an expansion of 386.08 hectares in built-up lands, with approximately 356.82 hectares converted from agricultural areas. The accuracy assessment of the 2023 land cover prediction map showed a high level of correctness, with a 97% accuracy rate. Based on these results, it was concluded that land conversion is essential to prevent environmental degradation, and further research can be carried out with the aim of assessing environmental quality indices.

This study presents an automated methodology to generate training data to map up-to-date artificial impervious surface (AIS) extent maps using two dates (winter and nonwinter) of a Sentinel-2 granule across six international sites (Egypt, India, Qatar, U.K., Eastern USA, and Western USA). It uses a series of spectral, textural, and distance decision functions combined with an outdated AIS layer to create nontarget and target binary masks from which to generate a balanced set of training data applied to a random forest classifier. Two outdated global AIS layers (GMIS-2010 and GISA-2016) were evaluated within the framework to create AIS maps from more recent years (e.g., 2020). For the decision functions, stepwise threshold adjustments applied to normalized difference vegetation index (NDVI) and Euclidean distance layers were evaluated on the binary masks (low-density AIS, high-density AIS, and nontarget land covers) with 729 permutations and 115 permutations for global impervious surface area (GISA) and global manmade impervious surface (GMIS), respectively. The optimal thresholds were determined globally (all six scenes), individually (scene) and grouped by climate for adaptive thresholds. The accuracy assessment found both GMIS-output and GISA-output with global thresholds can accurately map current AIS with 86.9% (±1.7%) (GISA) and 82.7% (±2.3%) (GMIS) accuracy. Adaptive climate thresholds yielded slightly higher accuracies for temperate, tropics, and arid scenes. A novel beach bare ground sampling mask and annual NDVI standard deviation were also evaluated for performance and improved the accuracy in 5/6 sites. Lastly, the global GISA output was compared with a manually labeled deep learning model (Esri) with slightly lower overall accuracy (86.9% vs 88.6%).

New Yogyakarta International Airport (NYIA) in Kulon Progo Regency was developed with the primary objective of fostering economic growth. The initiation of operations at NYIA in March 2020 triggered substantial urban development in the surrounding area. This research aimed to monitor the changes in land cover and predict the development of urban areas. The research methodology comprised the use of Random Forest, Classification, and Regression Tree machine learning algorithms to create land cover maps. It also incorporated Cellular Automata (CA), which was used to make prediction related to land development. The results showed that the land cover map had an overall accuracy level of above 0.80. Furthermore, it was observed from the results of the time series land cover analysis that there was a rapid growth in built-up lands. Between 2013 and 2017, these lands expanded by 572.38 hectares and further increased by 268.97 hectares from 2017 to 2023, leading to the conversion of 571.64 hectares of agricultural lands. On the basis of these findings, it was projected that by 2033, there would be an expansion of 386.08 hectares in built-up lands, with approximately 356.82 hectares converted from agricultural areas. The accuracy assessment of the 2023 land cover prediction map showed a high level of correctness, with a 97% accuracy rate. On the basis of these results, it was concluded that land conversion is essential to prevent environmental degradation, and further research can be carried out with the aim of assessing environmental quality indices. [ABSTRACT FROM AUTHOR]

The validated influence of urban biophysical structure on environmental processes within urban areas has heightened the emphasis on studies examining morphological patterns to determine precise locations and underlying causes of urban climate conditions. The present study aims to characterise morphological patterns describing the distribution of Land Surface Temperature (LST) based on a prior classification of biophysical variables, including urban density (building intensity and average height), surface characteristics, shortwave solar radiation (broadband albedo), and seasonal variations in vegetation cover (high, medium, and low levels), retrieved from multisource datasets. To describe the distribution of LST, the variables were calculated, classified, and subsequently, analysed individually and collectively concerning winter and summer LST values applied in an urban neighbourhood in Madrid, Spain. The results from the analytical approaches (observation, correlations, and multiple regressions) were compared to define the morphological patterns. The selection of areas resulting from the morphological patterns with the most unfavourable LST values showed agreement of up to 89% in summer and up to 70% for winter, demonstrating the feasibility of the methods applied to identify priority areas for intervention by season. Notably, low and high vegetation levels emerged as pivotal biophysical characteristics influencing LST distribution compared to the other characteristics, emphasising the significance of integrating detailed seasonal vegetation variations in urban analyses. [ABSTRACT FROM AUTHOR]

Monitoring land use, buildings, and vegetation index of ecotourism areas in North Halmahera can support planning space utilization in urban areas for tourist areas as the concept of land use management and urban planning. This study offers ideas for analyzing the distribution of buildings, vegetation index, and land use in the mangrove ecotourism area of North Halmahera Regency using the spatio-temporal analysis method. The spatio-temporal analysis method comprises several stages: data selection, preprocessing, data integration, spatial analysis, temporal analysis, spatio-temporal analysis, data visualization, interpretation and understanding, and data visualization. The results of this study show that changes in the livelihood strategy of local people, from farmers and fishermen to traders, also affect land use patterns, from agricultural activities to economic activities, which triggers an increase in the number of buildings for production activities to product distribution. The implications of these findings on ecotourism development programs and policies and infrastructure development in the North Halmahera Regency are to consider community livelihoods and space or land use behavior in ecotourism areas based on vegetation, soil, and building index values. Thus, the intensification of building distribution and changes in vegetation index values from 2013-2023 reflect changes in people's livelihood strategies from agrarian activities to trade and from fishermen's activities to tourism transportation service providers.

Cold-formed steel (CFS) sections have become popular in construction due to several advantages over structural steel. However, research on the performance of galvanized iron (GI)-based CFS under high temperatures, especially regarding its flexural behavior, has been limited. This study extensively investigates how GI-based CFS beams with varying spans behave under elevated temperatures and subsequent cooling using air and water. This study examines the impact of temperature loading and compares the effectiveness of air- and water-cooling methods. Experimental results are validated and analyzed alongside findings from finite element modeling (FEM) using ABAQUS (2019_09_13-23.19.31) and the Direct Strength Method (DSM). Additionally, this study conducts a parametric investigation to assess how beam span influences flexural capacity. Among beams heated to the same temperature, those cooled with water show slightly lower load capacities compared to those cooled with air. The highest load capacity observed is 64.3 kN for the reference specimen, while the lowest is 26.2 kN for the specimen heated for 90 min and cooled with water, a 59.27% difference between them. Stiffness decreases as heating duration increases, with the reference section exhibiting significantly higher stiffness compared to the section heated for 90 min and cooled with water, with a 92.76% difference in stiffness. As heating duration increases, ductility also increases. Various failure modes are observed based on different heating and cooling conditions across different beam spans. This study provides insights into how GI-based CFS beams perform under temperature stress and different cooling scenarios, contributing valuable data for structural design and safety considerations in construction.

Monitoring the spatiotemporal dynamics of building footprints (BF) is necessary for understanding urbanization growth. It is a difficult task to extract residential sites, mainly BF, because of the complexity of their makeup and spectral variety. Additionally, conventional methods for building mapping typically rely on abundant training data and expertise from human operates. This study presents a new unsupervised Feature-Based Building Footprint Extraction (F2BFE) strategy using Sentinel-1&2 satellite images and the SRTM Digital Elevation Model (DEM). The newly developed radar index (NRI) from Sentinel-1 images was utilized to extract the Primary Building Footprints (PBF) through histogram analysis and thresholding techniques, based on the mean of annual Sentinel-1 VV and VH Backscatter channels in the Ascending orbit. In this research, the integration of the Otsu and Unimodal thresholding technique was developed as an optimal thresholding method for feature extraction. Furthermore, Sentinel-2 images were applied to extract spectral indices related to vegetation (NDVI, GNDVI, RDVI indices), water (NDWI index), and residential/built-up (NDBI, BuEI). The qualitative and quantitative validation results indicate that the NRI-based BF map achieved higher Overall Accuracy (OA) values of 98.14%, 90%, and 91% in Region of Interest-1 (ROI-1), ROI-2, and ROI-3, respectively. Additionally, the Kappa Coefficients (KC) for these regions were 0.96, 0.97, and 0.85, respectively. The NRI index provides an excellent OA result when vegetation, water, and slope features are carefully eliminated. Finally, it can be inferred that the simultaneous use of the sentinel-1&2 and slope data in feature space leads to increased BF accuracy. [ABSTRACT FROM AUTHOR]

This paper investigates the lateral‐torsional buckling of built‐up cold‐formed steel beams featuring two or three component C‐ or sigma‐sections arranged to have a closed loop. Several thicknesses of each cross‐section with nominal yield stress values of 450 MPa and 550 MPa were tested to obtain lateral buckling strength data for a range of cross‐section slenderness values. Complementary reference tests were conducted on the same built‐up sections braced laterally to obtain the in‐plane section capacities, precluding the effect of lateral‐torsional buckling. Coupon tests were also conducted to determine the mechanical properties of the steel material. The test rig featured a dual‐actuator set‐up, with one actuator (applying vertical load) mounted on a trolley that was moved horizontally by the second actuator in response to the signal from a transducer measuring the lateral buckling displacement at the mid‐length of the beam, thus ensuring vertical loading throughout the experiments. The rig also featured specialized end bearings allowing free flexural rotations and warping, while restraining lateral displacements and twist rotations. The paper describes the test rig and the results of the in‐plane and lateral‐torsional buckling experiments. Particular attention is paid to the use of closed parts to enhance the torsional rigidity of the built‐up sections and thereby their lateral‐torsional buckling capacity. [ABSTRACT FROM AUTHOR]

Cold‐formed steel (CFS) structural profiles are extremely versatile enabling the combination of multiple individual cross‐section shapes to fabricate a built‐up member presenting enhanced structural performance (higher load‐bearing capacity and torsional stiffness). Built‐up members have the potential to contribute to further expanding the current use of CFS products in the construction industry. However, the existing design codes, such as the EN 1993‐1‐3 and AISI S100, do not present specific design methodologies for the design of such members, mainly due to a limited understanding of the complex behaviour of built‐up CFS members combining multiple components. The behaviour of built‐up CFS columns comprising 4 individual shapes was assessed through experimental tests and numerical modelling. The interaction between the different components and the influence of spacing between connectors was investigated using the finite element method, providing recommendations concerning the effective use of fasteners to attain composite action between the individual shapes. The suitability of the design codes, namely, Eurocode and North American design predictions, following to Effective Width Method (EWM) and Direct Strength Method (DSM), respectively, were assessed for the built‐up members. [ABSTRACT FROM AUTHOR]

Built‐up cold‐formed steel (CFS) columns are extensively used when single cold‐formed steel elements are not able to fulfill the established requirements in terms of load‐bearing capacity. For hot‐rolled steel laced and battened columns, the EN 1993‐1‐1 presents specific design provisions. However, no specific design guidelines are provided for CFS laced and battened columns. The investigation on this type of built‐up elements is scarce, requiring extensive research to assess if the hot‐rolled design methodologies are also suitable for cold‐formed steel elements. In this investigation, experimental and numerical results are presented for CFS battened columns comprising C and Σ channels. Assessing the composite action between the individual shapes connected by the batten plates was one of the objectives of this investigation. The predominant buckling modes were analyzed considering the influence of batten plate spacing and the number of fasteners per plate. Based on the obtained experimental results finite element models were developed to further assess the influence of key governing parameters. The observed axial strengths are compared with design strengths determined according to the Eurocode assessing the suitability of the design methodologies. [ABSTRACT FROM AUTHOR]

The dynamics of built-up height are a crucial aspect of urban form, enabling the characterization of urban growth patterns and the attainment of sustainable development goals. While past studies have focused on urban extent mapping, little has been done to reveal changes in vertical structures in built-up areas. In this study, we reconstructed annual urban form dynamics in Beijing, China, from 1990 to 2020, utilizing Landsat time-series data. First, we identified urban growth and renewal years using a temporal segmentation approach. Then, we reconstructed the annual dynamics of built-up heights through logical reasoning, using the reference height in 2020 and the identified changing years. We evaluated the derived dataset and analyzed the urban growth patterns (i.e., upward and outward) over the past three decades. The detected change years are reliable, with an overall accuracy of 88% (± 1 year). Meanwhile, the reconstructed built-up height data showed good agreement with surveyed results (R2: 0.92), with a root mean square error of 2.87 m and a mean absolute error of 2.07 m. Most expanded built-up areas during 1990–2020 were located at the fringe of the central city, and about 16% experiencing multiple changes. Overall, outward growth was prominent in Beijing during the first decade, while upward growth became dominant in most districts thereafter. The proposed framework provides a new way to reveal annual urban form dynamics through time series analysis, with great potential to support relevant studies such as urban climate modeling and carbon emissions studies. [ABSTRACT FROM AUTHOR]

Wildfires present a significant risk to societies globally due to population growth, concentrated activities, climate change, and extreme environmental conditions. To establish effective fire suppression and management policies, it is crucial to determine whether the distance between ignition points and urban areas is increasing or decreasing. This study analyzes 101,597 fires in Spain and California between 2007 and 2015, where ignition points and all built-up areas were precisely geolocated in 2014. The study employs the Mann–Kendall test to determine trends and analyze the relative distance of wildfires to human buildings over time. The results indicate that wildfires are becoming statistically significantly closer in several areas. It is also observed that the majority of wildfires are moving away from buildings, although this is not a significant finding. These results suggest the possibility of further research into the reasons behind these observations and possible future developments and their consequences.

Increased visitor arrivals and improved work opportunities in the discussed destinations resulted in infrastructural development and settlement movements, culminating in the urbanisation of the locations. As a result of increased tourist flows and growing economic dependency on the tourism sector, the accommodation and other tourist infrastructure have contributed to a change in built-up areas considerably in tourist areas. Most green spaces in environmentally vulnerable locations are being filled with concrete due to a lack of appropriate spatial development guidelines, while urban areas are losing their authentic aspects. The paper attempts to understand spatial sustainability through the measures of land consumption rate and land-use efficiency in various types of tourist places. As a result, the study concludes that there is a strong link between growing urbanisation and changing visitor arrivals, as well as population change, and tourism has a substantial influence on spatial sustainability.

A new built-up closed-rib section is proposed that may improve the installation, performance, and durability of orthotropic steel bridge decks. The rib is composed of two partial or whole standard hot-rolled steel sections which are connected by a steel plate. The concept is used to design a built-up closed-rib replacement for the Benjamin Franklin Bridge deck. In addition, section performance was compared with the actual bulb section as well as a typical trapezoidal section through finite element simulations. The analyses indicate that the built-up section has smaller stress concentration values as compared with the other sections, and hence, improved fatigue resistance is expected. Finally, it is concluded that the built-up rib has potential to be considered in future orthotropic steel deck designs.

Land use change occurs by altering natural landscape to manmade built environment. Rapid urban growth is the main factor for land use change at global level. Addis Ababa is one of the recent rapidly growing urban areas in Africa. Since 1983, the population has increased by nearly three times. However, the spatial expansion of the urban area has been much greater with urban sprawl, informal settlement, industry, condominium housing, and real estate development. The demand for urban land has been increasing at alarming rate both by city government, investors, and its residents. The city is primate and the population nine times the second largest city in the country. This study focused on quantifying and analyzing impact assessment of urban growth on land use change from 1986 to 2019. The study assessed the major change in extent and determinants of land use change through 33 years (1986–2019) and future growth scenario the next 30 years from 2019 to 2049. This study used Landsat image, base map of 1986, 1998, 2008, and 2019, to analyze built-up growth and land use change. Observation and interview have also taken to explore more on major urban growth and land use change driving factor from concerned bodies. The last, land use efficiency method was applied to measure land consumption rate and population growth rate. The result showed that in 1986, 1998, 2008, and 2019, built-up covered 21.83%, 42.31%, 59.42%, and 81.20% respectively. This shows that the agriculture and open space were rapidly changed to built-up by 32,486.67 hectares for housing, manufacturing, and infrastructure development. The result from concerned bodies has portrayed that the key determinants for urban land use change in the city were population growth at 4.2% per annum. Government led condominium housing, real estate development, and industrial development expansion including informal settlement has been rapidly reducing agriculture and open space through time. Therefore, unconventional planning approach could be exercised based on community interest for affordable high-rise building. Moreover, disseminate or decentralize industries beyond capital city in regional capital to reduce migration rate and rapid change of urban land use by creating employment opportunity and urban-urban linkage in the reginal capital rather than the capital city. [ABSTRACT FROM AUTHOR]

Environmental sustainability ensures that minerals are responsibly exploited to meet the present needs without depriving the future generations the ability to meet their needs. Unfortunately, environmental sustainability and artisanal mining seem unattainable in recent years with aggressive mining operations. It is on this premise that geospatial techniques with proven role in environmental studies were employed to assess the environmental sustainability due to artisanal mining in Jos area, Plateau State, Nigeria. Land surface temperature (LST) and seven geospatial indices used for land use land cover (LULC) estimation were generated. The mean LST values showed a steady increasing pattern from 23.98 to 25.88 °C and 29.46 °C in 1984, 2002, and 2020 respectively, as a result of exposed outcrops occasioned by mining and the expansion of mining communities. The mean value of the Normalized Difference Vegetation Index (NDVI) depicts a considerable increase from 0.179 in 1984 to 0.458 in 2002 and a slight decline to 0.438 in 2020. This is congruent with the mean Optimized Soil-Adjusted Vegetation Index (OSAVI) values, thus revealed that the Jos area is not densely vegetated implying that the course to revegetate the region has not been achieved to the tune of woodland populated vegetation. The resulting maps from Modified Normalized Difference Water Index (MNDWI) revealed a consistent decline in the mean values − 0.349, − 0.391, and − 0.411 in 1984, 2002, and 2020 respectively. Mineral recovery, mineral processing, and seasonal variations could be some of the reasons waterbodies are one of the most stressed natural resources in the study area. The mean values of Enhanced Built-up and Bareness Index (EBBI) decreased from 0.282 in 1984 to 0.202 in 2002, but increased from 0.202 in 2002 to 0.230 in 2020, which corroborated with the findings of NDBI. It was deduced that built-up areas in the study area are very low. This may be attributed to urban migration and the migration of artisanal miners to new mining sites across the state or country. The values of bare land mapped using Dry Bare Soil Index (DBSI) corresponds with that of Normalized Difference Bareness Index (NDBaI) and showed that bare land has reduced on the Jos Plateau due to improved vegetation growth. This study provided essential input and referential information for proper decision making on environmental sustenance, environmental management, and mineral resource conservation. [ABSTRACT FROM AUTHOR]

The simply supported beams are commonly used in practice. They present many advantages in design as well as in fabrication and erection. Because the moment of the beam is not constant along its length, the section needs to vary to use the least amount of raw material. Various optimization methods have been proposed, including web trimming, reducing the width of flanges, or changing the flange thickness. In terms of fabrication and installation, it is preferable to keep the beam height and the flange thickness unchanged, making the second solution the most popular. Previous studies have only discussed the flange-stepped solution. Thus, this article will focus on tapering the beam flange by investigating the optimal parameters in terms of the beam weight. The new formulas to determine these optimal parameters will be proposed. The formulas are then used to calculate the material saved by the method. The outcomes are next compared to those of other optimization methods. The result shows that flange-tapered is the most efficient solution.

The validated influence of urban biophysical structure on environmental processes within urban areas has heightened the emphasis on studies examining morphological patterns to determine precise locations and underlying causes of urban climate conditions. The present study aims to characterise morphological patterns describing the distribution of Land Surface Temperature (LST) based on a prior classification of biophysical variables, including urban density (building intensity and average height), surface characteristics, shortwave solar radiation (broadband albedo), and seasonal variations in vegetation cover (high, medium, and low levels), retrieved from multisource datasets. To describe the distribution of LST, the variables were calculated, classified, and subsequently, analysed individually and collectively concerning winter and summer LST values applied in an urban neighbourhood in Madrid, Spain. The results from the analytical approaches (observation, correlations, and multiple regressions) were compared to define the morphological patterns. The selection of areas resulting from the morphological patterns with the most unfavourable LST values showed agreement of up to 89% in summer and up to 70% for winter, demonstrating the feasibility of the methods applied to identify priority areas for intervention by season. Notably, low and high vegetation levels emerged as pivotal biophysical characteristics influencing LST distribution compared to the other characteristics, emphasising the significance of integrating detailed seasonal vegetation variations in urban analyses.

A new built-up closed-rib section is proposed that may improve the installation, performance, and durability of orthotropic steel bridge decks. The rib is composed of two partial or whole standard hot-rolled steel sections which are connected by a steel plate. The concept is used to design a built-up closed-rib replacement for the Benjamin Franklin Bridge deck. In addition, section performance was compared with the actual bulb section as well as a typical trapezoidal section through finite element simulations. The analyses indicate that the built-up section has smaller stress concentration values as compared with the other sections, and hence, improved fatigue resistance is expected. Finally, it is concluded that the built-up rib has potential to be considered in future orthotropic steel deck designs. [ABSTRACT FROM AUTHOR]

The insensitive manner in which man is utilizing land in the modern era has necessitated a continuous examination of the changing land use pattern all over the world. This study uses geospatial technology to analyse the changing land use land cover pattern of Keecheri-Puzhakkal river basin in Thrissur district, Kerala from 1995 to 2020. The results of analysis revealed that from 1995 to 2020 built up land increased by 86.91 km², whereas the area under forests, paddy wetlands and water bodies declined by 9.32 km², 46.70 km² and 3.31 km² respectively. Area under mixed crops initially increased by 30.40 km² from 1995 to 2008 and then reduced by 52.72 km² from 2008 to 2020. NDVI analysis showed that from 1995 to 2020 land with dense vegetation declined from 36.11% to 14.10% of the total geographical area of the river basin and land without vegetation increased from 32.14% to 46.36% of the total geographical area of Keecheri-Puzhakkal river basin. [ABSTRACT FROM AUTHOR]

This study investigates the effects of perforations on the buckling behavior and load-bearing capacity of advanced high-strength steel I-shaped built-up compression members. The built-up section was fabricated by connecting two identical lipped channel sections made of complex phrase steel HC700CP980 using pull rivets. The perforations were classified into two groups: holes in web and holes in both web and flanges. A comprehensive parametric study, combining both experimental results and finite element analysis, demonstrated the decrease in load-bearing capacity caused by the presence of perforations, particularly noticeable in specimens featuring holes in both web and flanges. The extend of the reduction is closely linked to the quantity and dimensions of the holes, with a higher hole-element width ratio resulting in a more substantial loss of load-bearing capacity. Additionally, the obtained test and FE results were used to evaluate the accuracy of direct strength method (DSM) for the examined advanced high-strength steel I-shaped built-up compression members. The evaluation findings highlight the limitations of the DSM in the design predictions for built-up columns featuring multiple web holes and holes on both web and flanges. Therefore, a modified calculation method was proposed, which integrated strength reduction factors to consider the influence of the position of holes relative to the flexural buckling axis of built-up sections. The modified method has shown notably improved design accuracy and consistency for the perforated advanced high-strength steel I-shaped built-up sections. • Tests and numerical analysis conducted on advanced high-strength steel I-shaped built-up columns with perforations. • Influence of perforations on the buckling instability and capacities of columns examined. • Applicability of the Direct Strength Method (DSM) assessed. • Modified DSM methods proposed for improved design accuracy and consistency. [ABSTRACT FROM AUTHOR]

Built-up area change detection (CD) plays an important role in city management, which always uses very high spatial resolution (VHR) remote sensing data to extract refined spatial information. Recently, many CD models based on deep learning with VHR data have been proposed. However, due to the complex background information and natural landscape changes, VHR with optical RGB features is hard to extract changes exactly. To this end, we tend to explore the abundant channel information of multispectral and SAR data as a supplement to the refined spatial features of VHR images. We propose a new deep learning framework called multisource CD UNet++ (MSCDUNet), integrating multispectral, SAR, and VHR data for built-up area CD. First, we label and reform two new built-up area CD datasets containing multispectral, SAR, and VHR data: multisource built-up change (MSBC) and multisource OSCD (MSOSCD) datasets. Second, a feature selection method based on random forest is introduced to choose effective features from multispectral and SAR images. Finally, a multilevel heterogeneous feature fusion module is embedded in MSCDUNet to combine multifeatures for CD. Experiments are conducted on both the MSOSCD and the MSBC datasets. Compared to other CD methods based on VHR images, our proposal achieves the highest accuracy on both datasets and proves the effectiveness of multispectral, SAR, and VHR data fusion for CD. The dataset in the article will be available for download from the following link.1

The bio-geophysical effects of land cover classes are considered to be an important factor in land surface temperature variations between urban and suburban areas. This means that major cities are significantly warmer than surrounding suburban or rural areas, which is known as the Urban Heat Island (UHI) effect. The aim of this study was to assess and analyze the spatiotemporal variation, correlation and impact of UHIs on Mekelle city (1990–2020) using remote sensing techniques. The study's primary objective was accomplished using the a number of techniques, including the extraction of LULC classes, estimation of the seasonal LSTs, assessment of UHI and UTFVI, and showing the relationship between LULC and LST as well as the interactions between UHI, UTFVI, and urban LULC classes. By analyzing TIRs/OLI thermal band data after calibrating uncertainty in the images and validating it using the concept of theoretical relationships and least squares fitting method, estimates of local LST, UHI (both in Mekelle and periphery rural areas), and UTFVI were obtained. The result of standard multiple regression models showed that impervious urban land surface, built-up areas, and dry bare soil highly contribute and influence variation at LST intensity caused for the formation of UHI in the study area. The result showed that the maximum UHI value in Mekelle city was 2.73 °C during the dry season in 1990. It decreased slightly to 2.53 °C in 2000 and then increased regularly to 2.83 °C and 2.98 °C in 2010 and 2020, respectively. To determine the city's UHI status in comparison to eight selected peripheral suburban areas, a trend analysis has been done. The UHI intensity of Mekelle city was higher relatively to that of most of the periphery suburban districts, particularly in 2020 (both dry and rainy seasons); this could be due to the city's explosive growth. It's worth noting that the research area affected by the urban heat island effect has grown over time, and as a result, the study area also has severe microclimate conditions that primarily damage the quality of urban life and create the worst conditions for thermal discomfort. The results of this study provide major conceptual understandings of how improper distribution and use of urban land affects the urban environment and fuels the creation of the UHI and thermal discomfort phenomena. Hence policy makers and urban planners should consider the effects of LST and UHI and integrate UHI comprehensive mitigation strategies with urban development patterns, and current and projected local climate changes in order to create sustainable urban environments, cities, and communities. In conclusion, compared to the conventional method, satellite remote sensing provides a faster and more efficient method for researching LST and UHI.

The present study attempts to simulate land surface temperature (LST) as a function of built-up density using an artificial neural network (ANN) algorithm. The LST was retrieved from Landsat thermal datasets for years 2000, 2010, and 2019 using a single channel algorithm. The retrieved LST was validated using downscaled MODIS LST products of corresponding dates and an average root-mean-square error (RMSE) of 1.3 °C and 1.9 °C was obtained on winter and summer datasets, respectively. The ANN was trained using corresponding built-up density and LST values for the year 2000, 2010, and 2019. The mean absolute error (MAE) of 1.1 °C and 0.7 °C was achieved on summer and winter training datasets, respectively, while on summer and winter testing datasets MAE of 1.5 °C and 0.9 was obtained. Various urban growth scenarios in the year 2029 were simulated using sim weight which is a nonparametric instance-based machine learning algorithm, based on K nearest neighbour procedure. The simulated built-up densities for the year 2029 were input into the trained ANN and LST patterns for the year 2029 were predicted. Analysis of the results showed that for Dehradun city which is located in a humid subtropical climate zone in India, compact urban growth led to lesser areas having LST greater than 42 °C in summers, as compared to other urban growth patterns. [ABSTRACT FROM AUTHOR]

Urban encroachment due to urban sprawl and unchecked expansion in built-up areas is one of the top challenges developing countries such as Pakistan face. The fertile agricultural land is continuously converting into built-up areas reducing the capacity of food production and bringing down the livelihood opportunities associated with agricultural land. Pakistan is an agricultural country with extensive fertile areas. The GDP share of agriculture is more than 20%, and it engages more than half of the country's total labor force, producing a handsome foreign exchange. However, this fertile and productive land is now altering due to urbanization encroachment. The primary purpose of this study was to assess the level of urbanization encroachment and its temporal dynamics in the lowlands of Khyber Pakhtunkhwa. The sample area of District Peshawar was selected for this purpose. First, the study's objective was to detect the district's temporal dynamics in the land-use pattern. Secondly, the quantification of agricultural land converted to built-up in District Peshawar was also considered. The study of urbanization encroachment in temporal dynamics focused on the conversion of agricultural land-use change using high-resolution satellite images (Arc GIS 10.5), a detailed questionnaire survey, and interviews, and focus group discussions were conducted to obtain more profound insight into the study area. SPSS (Statistical Package for Social Sciences), ANOVA, and regression models were applied where needed. For the agricultural land investigation, data from the landowners were also incorporated to learn the size of the lands they currently hold. To claw out the fragmentation of the land, the previous status of the land, its selling, purchasing, and the causes thereof, have also been probed. The results show that 46.35 sq. km of the land area has been built-up since the first census in 1981. In 2019, it increased by 173.3049 sq. km in District Peshawar against the total area of 1257 sq. km. In the sample area, the fertile agricultural land shows a change five times greater than the population increase. The land is continuously reduced and utilized for different purposes. The land values also appeal to the land owners for handsome returns, which is another crucial factor of urban encroachment over the fertile agricultural area. A proper and active regularity authority is recommended, and policies for land transformation from agriculture to built-up coverings should be formed. Decentralization of facilities, subsidies, and incentives to the farmers are recommended to slow down the speed of land conversion. [ABSTRACT FROM AUTHOR]

Un-coordinated urban development, poses many challenges one of which is the encroachment of development into wetland ecosystem. The study examined urban growth dynamics and wetland loss in Yenegoa, Bayelsa state. The research approach was quantitative employing the longitudinal survey design. Both primary and secondary source of data were used. Time series Landsat Imageries of Bayelsa state were downloaded from the website repository of the United Geological Survey for the years 1996, 2004, 2012 and 2021. The Images were clipped in the ArcGIS environment using the clipping tool under the Data management tools in ArcGIS toolbox. Findings showed that there is wetland loss in all the years investigated attributed to urban growth. A total of 2179, hectares of wetland was lost between 1996 and 2004, from a wetland coverage of 31556 hectares in 1996 to 29377 hectares in 2004 with percentage decrease of -6.91. There was however 27% gain in builtup areas to the tune of 4037 hectares from an area of 15194 hectares in 1996 to 19231 hectares in 2004 with a percentage increase of 26.56. The situation in 2012 was however not different as there was further wetland loss of 4423 hectares from a wetland coverage of 29377 hectares in 2004 to 24954 hectares in 2012 while built-up gained a land area of 4019 hectares. (32%) within the same period with a percentage increase of 20.90. The 2021 analysis revealed further depletion of wetland in the area with a wetland loss of 2085 hectares from an area of 24954 hectares in 2012, to 22869 hectares in 2021 with a percentage decrease of -8.36, while built-up gained 2814 hectares increasing from 23250 hectares in 2012 to 26064 hectares (32%) in 2021(36%) with a percentage increase of 12.10. Strict implementation of extant laws on wetland conservation is a desideratum for ensuring the protection of wetland resources in Yenegoa Planning Area. [ABSTRACT FROM AUTHOR]

The use of vegetation is one of the effective methods to combat the increasing Urban Heat Island (UHI). However, vegetation is steadily decreasing due to urban pressure and increased water stress. This study used air temperature measurements, humidity and an innovative advanced earth system analysis to investigate, at daytime, the relationship between green surfaces, built-up areas and the surface urban heat island (SUHI) in Marrakesh, Morocco, which is one of the busiest cities in Africa and serves as a major economic centre and tourist destination. While it is accepted that UHI variation is generally mitigated by the spatial distribution of green spaces and built-up areas, this study shows that bare areas also play a key role in this relationship. The results show a maximum mean land surface temperature difference of 3.98 °C across the different city neighbourhoods, and bare ground had the highest correlation with temperature (r = 0.86). The correlation between the vegetation index and SUHI is decreasing over time, mainly because of the significant changes in the region's urban planning policy and urban growth. The study represents a relevant overview of the factors impacting SUHI, and it brings a new perspective to what is known so far in the literature, especially in arid climate areas, which have the specificity of large bare areas playing a major role in SUHI mitigation. This research highlights this complex relationship for future sustainable development, especially with the challenges of global warming becoming increasingly critical. [ABSTRACT FROM AUTHOR]

Convolutional neural network (CNN)-based very high-resolution (VHR) image segmentation has become a common way of extracting building footprints. Despite publicly available building datasets and pre-trained CNN models, it is still necessary to prepare sufficient labeled image tiles to train CNN models from scratch or update the parameters of pre-trained CNN models to extract buildings accurately in real-world applications, especially the large-scale building extraction, due to differences in landscapes and data sources. Deep active learning is an effective technique for resolving this issue. This study proposes a framework integrating two state-of-the-art (SOTA) models, U-Net and DeeplabV3+, three commonly used active learning strategies, (i.e., margin sampling, entropy, and vote entropy), and landscape characterization to illustrate the performance of active learning in reducing the effort of data annotation, and then understand what kind of image tiles are more advantageous for CNN-based building extraction. The framework enables iteratively selecting the most informative image tiles from the unlabeled dataset for data annotation, training the CNN models, and analyzing the changes in model performance. It also helps us to understand the landscape features of iteratively selected image tiles via active learning by considering building as the focal class and computing the percent, the number of patches, edge density, and landscape shape index of buildings based on labeled tiles in each selection. The proposed method was evaluated on two benchmark building datasets, WHU satellite dataset II and WHU aerial dataset. Models in each iteration were trained from scratch on all labeled tiles. Experimental results based on the two datasets indicate that, for both U-Net and DeeplabV3+, the three active learning strategies can reduce the number of image tiles to be annotated and achieve good model performance with fewer labeled image tiles. Moreover, image tiles with more building patches, larger areas of buildings, longer edges of buildings, and more dispersed building distribution patterns were more effective for model training. The study not only provides a framework to reduce the data annotation efforts in CNN-based building extraction but also summarizes the preliminary suggestions for data annotation, which could facilitate and guide data annotators in real-world applications. [ABSTRACT FROM AUTHOR]

Increased visitor arrivals and improved work opportunities in the discussed destinations resulted in infrastructural development and settlement movements, culminating in the urbanisation of the locations. As a result of increased tourist flows and growing economic dependency on the tourism sector, the accommodation and other tourist infrastructure have contributed to a change in built-up areas considerably in tourist areas. Most green spaces in environmentally vulnerable locations are being filled with concrete due to a lack of appropriate spatial development guidelines, while urban areas are losing their authentic aspects. The paper attempts to understand spatial sustainability through the measures of land consumption rate and land-use efficiency in various types of tourist places. As a result, the study concludes that there is a strong link between growing urbanisation and changing visitor arrivals, as well as population change, and tourism has a substantial influence on spatial sustainability. [ABSTRACT FROM AUTHOR]

Jakarta and Bandung metropolitan areas in Indonesia are experiencing urban expansion, which makes these two metropolitan areas increasingly connected by corridors to become one mega-urban. Karawang and Purwakarta Regencies are part of the Jakarta-Bandung corridor area which then triggers the urban physical development. This study aims to 1) Determine the level of service facilities in Karawang and Purwakarta Regencies; 2) Identify the changes in built-up and paddy fields Land Use/Land Cover (LULC) of Karawang and Purwakarta Regency based on existing and future conditions, and 3) Propose recommendations to control the urban physical development in Karawang and Purwakarta Regency. Analysis of level service facilities was carried out by using the scalogram method. Changes of built-up and paddy fields LULC in the existing and future conditions (projected using the CA-Markov method) are based on LULC of 2005, 2010 and 2018. Recommendations are given based on the grouping of villages with the same characteristics using the quantitative zoning method. Results showed the village development index in 2018 as the level of service facilities indicators, has a high or more developed value in the area around the connecting accessibility route between Jabodetabek and Greater Bandung metropolitan area. Changes in built-up and paddy fields LULC also the same trend as the village development index that is characterized by a fairly large increase in the area of built-up LULC in Karawang and Purwakarta Regencies. Recommendations are given to address specific problems that exist in each village group formed based on the spatial clustering method result. [ABSTRACT FROM AUTHOR]

A test program on cold-formed steel (CFS) laced columns fabricated using plain channels has been presented in this study. Twelve specimens with single and N-type lacing configurations were fabricated. The lacing plates and the end-plates were connected to the chords by using self-drilling screws. The effect of critical parameters, like lacing slenderness and transverse chord spacing, on the performance of laced columns under concentric axial loading was investigated. The aspect ratio of the built-up section of the specimens varied from 0.75 to 1.25. The relative slenderness of the unsupported chord (with respect to the global slenderness of the column) ranged from 0.31 to 0.87 in single-laced columns and 0.15–0.44 in N-type laced columns. The performance of the specimens was assessed in terms of their failure modes, peak strengths, and load-displacement trends. Lastly, the strength estimations from both the current American (AISI S100-16) and European (EN1993-1-3) standards were evaluated by comparison against the test strengths. It was noted that both these codes overpredicted the strength of the laced column specimens by up to about 25%. The modified design rules catering to both American (AISI S100-16) and European (EN1993-1-3) standards, previously proposed by the authors for CFS battened columns, were assessed, and their strength predictions were found satisfactory for both types of lacing configurations. The reliability index determined using the modified design rules was approximately equal to three, indicating high reliability. [ABSTRACT FROM AUTHOR]

Continuous urban expansion transforms the natural land cover into impervious surfaces across the world. It increases the city's thermal intensity that impacts the local climate, thus, warming the urban environment. Surface urban heat island (SUHI) is an indicator of quantifying such local urban warming. In this study, we quantified SUHI for the two most populated cities in Alberta, Canada, i.e., the city of Calgary and the city of Edmonton. We used the moderate resolution imaging spectroradiometer (MODIS) acquired land surface temperature (LST) to estimate the day and nighttime SUHI and its trends during 2001–2020. We also performed a correlation analysis between SUHI and selected seven influencing factors, such as urban expansion, population, precipitation, and four large-scale atmospheric oscillations, i.e., Sea Surface Temperature (SST), Pacific North America (PNA), Pacific Decadal Oscillation (PDO), and Arctic Oscillation (AO). Our results indicated a continuous increase in the annual day and nighttime SUHI values from 2001 to 2020 in both cities, with a higher magnitude found for Calgary. Moreover, the highest value of daytime SUHI was observed in July for both cities. While significant warming trends of SUHI were noticed in the annual daytime for the cities, only Calgary showed it in the annual nighttime. The monthly significant warming trends of SUHI showed an increasing pattern during daytime in June, July, August, and September in Calgary, and March and September in Edmonton. Here, only Calgary showed the nighttime significant warming trends in March, May, and August. Further, our correlation analysis indicated that population and built-up expansion were the main factors that influenced the SUHI in the cities during the study period. Moreover, SST indicated an acceptable relationship with SUHI in Edmonton only, while PDO, PNA, and AO did not show any relation in either of the two cities. We conclude that population, built-up size, and landscape pattern could better explain the variations of the SUHI intensity and trends. These findings may help to develop the adaptation and mitigating strategies in fighting the impact of SUHI and ensure a sustainable city environment. [ABSTRACT FROM AUTHOR]

Some of the past studies on cold-formed steel (CFS) battened built-up columns have resulted in the development of new design rules for predicting their axial strengths. However, the main drawbacks of such studies are that they are purely numerical and the numerical models developed for such parametric studies were validated using the test results on similar built-up column configurations, but not the exact ones. Therefore, experimental studies on CFS battened columns comprising of lipped channels are needed for verifying the accuracy of the proposed design rules for CFS battened columns. This paper reports an experimental study performed on CFS built-up battened columns under axial compression. Adequately spaced identical lipped channels in the back-to-back arrangement were used as chords and were connected by batten plates laterally with self-driving screws to form the built-up members. The dimensions of chords were fixed as per the geometric limits given out in the North American Specifications (NAS) for the design of CFS structural members. The sectional compactness of the chords and the overall slenderness of the built-up columns were varied by altering the thickness of the channels and height of the built-up columns, respectively. A total of 20 built-up sections were tested under uniform compression to investigate the behavioural changes in the built-up columns due to these variations. The behaviour assessment was made in terms of peak strengths, load–displacement response and failure modes of the test specimens. The current design standards on CFS structures were used to determine the design strengths and were compared against the test strengths for assessing their adequacy. Furthermore, as discussed in the beginning, the test strengths were used to verify the accuracy of the different relevant proposed design rules in the literature. [ABSTRACT FROM AUTHOR]

The use of vegetation is one of the effective methods to combat the increasing Urban Heat Island (UHI). However, vegetation is steadily decreasing due to urban pressure and increased water stress. This study used air temperature measurements, humidity and an innovative advanced earth system analysis to investigate, at daytime, the relationship between green surfaces, built-up areas and the surface urban heat island (SUHI) in Marrakesh, Morocco, which is one of the busiest cities in Africa and serves as a major economic centre and tourist destination. While it is accepted that UHI variation is generally mitigated by the spatial distribution of green spaces and built-up areas, this study shows that bare areas also play a key role in this relationship. The results show a maximum mean land surface temperature difference of 3.98 °C across the different city neighbourhoods, and bare ground had the highest correlation with temperature (r = 0.86). The correlation between the vegetation index and SUHI is decreasing over time, mainly because of the significant changes in the region’s urban planning policy and urban growth. The study represents a relevant overview of the factors impacting SUHI, and it brings a new perspective to what is known so far in the literature, especially in arid climate areas, which have the specificity of large bare areas playing a major role in SUHI mitigation. This research highlights this complex relationship for future sustainable development, especially with the challenges of global warming becoming increasingly critical.