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• Climatic conditions effect was evaluated on urban photovoltaic system development. • SMCDA was used to assess the spatial potential of UPVS development. • PVOUT and population density are key factors in UPVS development. • Dry climate cities have higher UPVS development potential than humid ones. Identifying suitable locations for urban photovoltaic systems (UPVS) is crucial for achieving sustainable energy objectives and designing smart, eco-friendly cities. This study assesses the potential for UPVS expansion in eight cities across different climatic zones in Iran using a spatial multi-criteria decision-making method. Two scenarios were analyzed: the first compared spatial potential within each city, and the second compared potential between cities. The findings indicate that rooftops of the tallest buildings in densely populated areas, especially those with high solar energy output and sky view factor, hold the greatest potential for UPVS development. These locations are often near parks, commercial centers, and road networks. In the first scenario, Ardabil (5.70%), Gorgan (4.65%), Mashhad (5.46%), Tehran (8.10%), Kermanshah (5.76%), Shahrekord (3.41%), Kerman (8.67%), and Zahedan (8.56%) show significant potential for photovoltaic development. In the second scenario, cities in hot, dry climates like Zahedan and Kerman exhibit greater potential compared to cities in moderate, humid climates like Ardabil and Gorgan. Based on the analysis of this scenario, Ardabil (0.04%), Gorgan (1.49%), Mashhad (5.58%), Tehran (5.06%), Kermanshah (0.00%), Shaherkord (0.03%), Kerman (21.70%) and Zahedan (39.11%) showed a very high potential for UPVS development. The results of this study offer valuable insights for urban solar energy planning. [Display omitted] [ABSTRACT FROM AUTHOR]

Anthropogenic activities play a crucial role in the formation and intensification of Urban Surface Ecological Poorness Zones (USEPZ). This study introduces a methodology for assessing the spatiotemporal fluctuations of Anthropogenic USEPZ (AUSEPZ), using Lisbon city and the Setúbal district as a case study to demonstrate its effectiveness. By integrating data from various surface characteristics through the Comprehensive Ecological Evaluation Index (CEEI), Surface Ecological Condition (SEC) maps were developed, and their spatial and temporal variations were analyzed. Additionally, a feature space was established between the Impervious Surface Percentage (ISP) and CEEI to calculate AUSEPZ intensity across different years. The findings revealed that the mean CEEI of Lisbon increased by 0.41 between 1986 and 2023. During this period, the proportions of SEC classified as Excellent, Very Good, Good, Fair, and Poor changed by −52 %, −13 %, +107 %, +444 %, and + 1134 %, respectively. The AUSEPZ intensity values for Lisbon were 0.32, 0.39, 0.46, 0.52, 0.57, and 0.63 for the years 1986, 1994, 2001, 2008, 2015, and 2023, respectively. The intensification of human activities, driven by urban expansion and population growth, has significantly contributed to the deterioration of SEC in Lisbon over recent years. These findings provide valuable insights for urban planners, policymakers, and stakeholders, enabling the design of targeted strategies to mitigate the impacts of urbanization and enhance ecological conditions in urban areas. [Display omitted] • A CEEI-ISP feature space-based method was proposed for AUSEPZ intensity quantification. • AUSEPZ intensity reflects heightened human activity impact on SEC degradation. • The proposed method effectively captures AUSEPZ intensity changes. • The SEC poorness degree in Lisbon city increased by 186 % from 1986 to 2023. • The AUSEPZ intensity of Lisbon rose from 0.32 (1986) to 0.63 (2023). [ABSTRACT FROM AUTHOR]

Abstract Wind erosion in arid and semi-arid regions is a serious concern because it can cause land degradation and consequently affect the land use pattern. The aim of this study was to assess the variations of aeolian sediments and gypsum sediment surfaces (ASGSS) during 1992–2017 in Sejzy Plain and to analyze the impact of plans against desertification, as well as human and environmental activities on the variations of these surfaces. In the current study, Landsat satellite images were classified using the multiple layer perceptron (MLP) neural network. Finally, the logistic regression model has been used to study the impact and role of plans against desertification, human and environmental activities on the ASGSS variations in the studied area. The ASGSS decreased from 37.9% in 1992 to 24.3% in 2017 in the study area. Investigation of the effect of aeolian desertification in the region showed that planting stabilizing species and preventive measures taken in controlling gypsum-mining activities and grill areas, especially in the northern parts of the region has prevented further variation in the gypsum sediment cover. The results indicate that the planting of stabilizing species in lands outside the ASGSS has a greater effect on reducing ASGSS, in comparison with the planting of stabilizing species in the interior lands of the and ASGSS. Also, the results show that policies related to plans against desertification have been useful in reducing lands with ASGSS. [ABSTRACT FROM AUTHOR]

This study aimed to explore the effect of the sea on the spatial and temporal changes in surface urban heat island (SUHI) intensity. Therefore, 11 cities located along the Caspian Sea Plain were selected as the case studies. Firstly, the SUHI intensity of both coastal and non-coastal cities was calculated for different seasons and times of day and night. Finally, the effect of distance from the sea on the SUHI intensity was calculated by modeling the relationship between the SUHI intensity and a set of independent parameters such as urban surface biophysical properties, population density, and distance from the coastline. The results showed that by increasing the distance of cities from the sea, the daily SUHI intensity increased, while it reversed during the night. The RMSE values between the actual and simulated SUHI intensities based on population density and surface biophysical properties in spring, summer, autumn, and winter were 0.9, 1.1, 0.5, and 0.3 °C, respectively. By factoring in the distance from the sea in the modeling, the RMSE values for different seasons were obtained at 0.7, 0.8, 0.3, and 0.2 °C, respectively. The results show that distance from the sea has a significant effect on UHI intensity. • The effect of the sea on the spatial and temporal changes in the UHI intensity was assessed. • The research data consisted of a range of remote sensing and ground stations data. • The distance of cities from the coastline is one of the main contributors to the UHI intensity. • The highest effect of the sea on the UHI occurred between 13:00 to 15:00 (20:00 to 22:00) in the warm (cold) seasons. • By increasing the distance of cities from the sea, the daily (nightly) UHI intensity was increased (decreased). [ABSTRACT FROM AUTHOR]

Nowadays, predicting spatial and temporal changes of surface urban heat islands (SUHIs) is both a demanding challenge and a subject of interest for researchers working on urban thermal environments. This study aimed to predict the spatial-temporal changes of SUHI in Tehran city. The research data consisted of Landsat multi-temporal images, MODIS-derived water vapor and land surface temperature (LST) products, as well as climatic data. The cellular automata (CA)-Markov model was used for predicting the spatial and temporal land cover changes. Afterward, based on the statistical and spatial information of the impact of land cover changes on LST changes, maps of the LST and SUHII were procured for future years. The results showed that the area of built-up lands increased by 88% from 1985 to 2019. The built-up lands area is expected to increase to 446.3, 463.9, and 480.1 km2 by 2026, 2032, and 2038, respectively. The mean LST of Tehran city in 1985, 1992, 2000, 2009, and 2019 was 36.45, 41.95, 43.15, 44.95, and 47.25 °C, respectively. By 2026, 2032, and 2038, the mean LST may reach 48.65, 49.95, and 51.15 °C, respectively. Analysis of the SUHI ratio index in Tehran showed an increase from 0.01 in 1985 to 0.34 in 2019, and is expected to reach 0.38, 0.45, and 0.51 by 2026, 2032, and 2038, respectively. • Spatial and temporal changes in the SUHI of Tehran city were evaluated. • A CA-Markov model was employed for LST and SUHI prediction. • The area of built-up lands increased by 88% from 1985 to 2019. • The mean LST of Tehran increased by 11 °C during the period of 1985–2019. • The SUHI intensity in 2026, 2032, and 2038 is expected to increase by 11, 23, and 50%, respectively. [ABSTRACT FROM AUTHOR]

• This study proposes a new categorization of land uses, the eight-type spaces (ETS). • The ETS integrates land functions into urban human-natural systems. • Spatial compositions have a distinct impact on the LST of the ETS. • Human systems and natural systems have a difference in hot spot areas. • To mitigate temperature, human systems need more attention in urban planning. The planning for cooling cities is crucial for sustainable development under the influence of climate change. However, urban warming mitigation across human-natural systems is scarce. This research aims at characterizing land surface temperature with the integration of land uses and land function with the eight-type spaces, including human systems (H1 residential area, H2 commercial area, H3 public service, H4 open space) and natural systems (N5 natural green, N6 farmland, N7 brownfield, N8 water). We seasonally investigated the LST, its correlation with three indices of spatial components. From the results, NDVI had more impact on LST than NDBI in H1, H3, H4, N6, N7, and N8; while NDBI had more influence than NDVI in H2 and N5; The area of Hot and Very hot classes in human systems is higher than in natural systems. It reveals that mitigating temperature across different urban land use types requires different management of green, grey, and blue infrastructures. The eight-type spaces could explain there are different NDVI and NDBI influences on urban temperature. More attention on urban planning is needed on human systems though increasing building height and combining grey infrastructures with green infrastructures and natural systems requiring decreasing impervious spaces for cooling cities. [ABSTRACT FROM AUTHOR]