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A substantial portion of interventions designed to support autistic children are also designed to be delivered by caregivers (i.e. are ‘caregiver‐mediated’). Brown et al. (Journal of Child Psychology and Psychiatry, 2024) are one of the first groups to critically examine the baseline skills that caregivers bring as they prepare to learn a class of interventions called Naturalistic Developmental Behavioral Interventions (NDBIs), which are designed to support social communication growth in young autistic children. This commentary commends Brown and colleagues for their focus on caregivers, a linchpin within the increasingly prominent caregiver‐mediated process of intervention delivery. However, it is imperative that future research understand the potential adverse effects and supports that are needed to bolster caregivers in this crucial role. We present six recommendations for research on caregiver‐mediated interventions that build on Brown and colleagues' work and address these needs, which involve: caregiver supports, equitable samples, community settings, adaptive designs, general principles, and implications for NDBI dissemination. [ABSTRACT FROM AUTHOR]

Studies have shown that the greenspace ratio has a cooling effect on the land surface temperature (LST) in different regions. Sample plots were obtained from 32 different regions in Istanbul. For 1985, 2000, 2013, and 2021, LSTs were determined using Landsat satellite images, and their relationships with GI, NDVI, and NDBI were examined. In the 1985–2021 period, the rate of greenspace in the sample plots decreased from 23 to 6.9%. The lowest LSTs were obtained in 1985, whereas the highest LSTs were found in 2013. Generally, low LSTs values were obtained in areas with a high greenspace ratio. The GI index decreased from 0.23 to 0.07 from 1985–2021. There was an increase of 10.07°C in average LST values in the 1985–2021 period. Negative correlations were found between NDVI and GI indices and LST, and positive correlations were found between NDBI and LST. In 1985, the lowest LST value was obtained in the 31st region with a greenspace ratio of 54%, while in other periods it was 27th region, some of which was covered with forests and the percentage of greenspace ratio decreased from 21 to 11%. The areas with the highest LST values were generally obtained in areas with dense population and urbanization and with a greenspace rate of 1% or less. The DUNCAN test was used to separate regions in terms of LST values. [ABSTRACT FROM AUTHOR]

Parent‐mediated, naturalistic developmental behavioral interventions (NDBIs) are a promising approach for supporting social communication development in young autistic children. This study examined the effect of telehealth delivery of a parent‐mediated NDBI, Project ImPACT, on children's expressive language ability using a randomized control trial with intent‐to‐treat analysis. Sixty‐four young autistic children and their primary caregiver were matched on age and developmental quotient and randomly assigned to receive 6 months of therapist‐assisted Project ImPACT (i.e., telehealth coaching), self‐directed Project ImPACT, or an active control. Parent–child interactions were recorded at intake and immediately post‐treatment, and the children's expressive language skills were assessed at intake and a 9‐month follow‐up using standardized measures. Although there was no total effect of treatment group assignment on child outcomes, a serial mediation analysis revealed that therapist‐assisted ImPACT had an indirect effect on children's expressive language ability at follow‐up through their parents' use of the intervention strategies and their intentional communication immediately post‐treatment. Findings support Project ImPACT's program theory and highlight the importance of coaching in achieving positive outcomes when delivered via telehealth. Lay Summary: Parent‐delivered, naturalistic developmental behavioral interventions (NDBIs) are a promising approach for supporting social communication development in young autistic children. This study examined the effect of telehealth delivery of a parent‐delivered NDBI, Project ImPACT, on children's expressive language ability. Children and their primary caregiver were randomly assigned to receive 6 months of telehealth coaching from a therapist about Project ImPACT, a self‐directed web‐based Project ImPACT tutorial, or information and resource support. Parents who received telehealth coaching from a therapist improved significantly more in their use of the intervention strategies with their children than parents who received self‐directed Project ImPACT or resource support. For this group, increases in parent use of the intervention strategies led to improvements in children's intentional communication post‐treatment which led to improvements in children's expressive language skills at follow‐up. Findings highlight the importance of therapist coaching in achieving positive outcomes when delivering Project ImPACT via telehealth. [ABSTRACT FROM AUTHOR]

Groundwater depletion and water scarcity are pressing issues in water-limited regions worldwide, including Pakistan, where it ranks as the third-largest user of groundwater. Lahore, Pakistan, grapples with severe groundwater depletion due to factors like population growth and increased agricultural land use. This study aims to address the lack of comprehensive groundwater availability data in Lahore's semi-arid region by employing GIS techniques and remote sensing data. Various parameters, including Land Use and Land Cover (LULC), Rainfall, Drainage Density (DD), Water Depth, Soil Type, Slope, Population Density, Road Density, Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-Up Index (NDBI), Moisture Stress Index (MSI), Water Vegetation Water Index (WVWI), and Land Surface Temperature (LST), are considered. Thematic layers of these parameters are assigned different weights based on previous literature, reclassified, and superimposed in weighted overlay tool to develop a groundwater potential zones index map for Lahore. The groundwater recharge potential zones are categorized into five classes: Extremely Bad, Bad, Mediocre, Good, and Extremely Good. The groundwater potential zone index (GWPZI) map of Lahore reveals that the majority falls within the Bad to Mediocre recharge potential zones, covering 33% and 28% of the total land area in Lahore, respectively. Additionally, 14% of the total area falls under the category of Extremely Bad recharge potential zones, while Good to Extremely Good areas cover 19% and 6%, respectively. By providing policymakers and water supply authorities with valuable insights, this study underscores the significance of GIS techniques in groundwater management. Implementing the findings can aid in addressing Lahore's groundwater challenges and formulating sustainable water management strategies for the city's future. [ABSTRACT FROM AUTHOR]

Background: The rising number of children identified with autism has led to exponential growth in for-profit applied behavior analysis (ABA) agencies and the use of highly structured approaches that may not be developmentally appropriate for young children. Multiple clinical trials support naturalistic developmental behavior interventions (NDBIs) that integrate ABA and developmental science and are considered best practices for young autistic children. The Early Start Denver Model (ESDM) is a comprehensive NDBI shown to improve social communication outcomes for young autistic children in several controlled efficacy studies. However, effectiveness data regarding NDBI use in community-based agencies are limited. Methods: This study uses a community-partnered approach to test the effectiveness of ESDM compared to usual early behavioral intervention (EBI) for improving social communication and language in autistic children served by community agencies. This is a hybrid type 1 cluster-randomized controlled trial with 2 conditions: ESDM and EBI. In the intervention group, supervising providers will receive training in ESDM; in the control group, they will continue EBI as usual. We will enroll and randomize 100 supervisors (50 ESDM, 50 EBI) by region. Each supervisor enrolls 3 families of autistic children under age 5 (n = 300) and accompanying behavior technicians (n = 200). The primary outcome is child language and social communication at 6 and 12 months. Secondary outcomes include child adaptive behavior, caregiver use of ESDM strategies, and provider intervention fidelity. Child social motivation and caregiver fidelity will be tested as mediating variables. ESDM implementation determinants will be explored using mixed methods. Discussion: This study will contribute novel knowledge on ESDM effectiveness, the variables that mediate and moderate child outcomes, and engagement of its mechanisms in community use. We expect results from this trial to increase community availability of this model and access to high-quality intervention for young autistic children, especially those who depend on publicly funded intervention services. Understanding implementation determinants will aid scale-up of effective models within communities. Trail registration: Clinicaltrials.gov identifier number NCT06005285. Registered on August 21, 2023. Protocol version: Issue date 6 August 2024; Protocol amendment number: 02. [ABSTRACT FROM AUTHOR]

Naturalistic Developmental Behavioral Interventions have been described as culturally responsive and family-friendly interventions, with research demonstrating improvements in children's development when receiving these services. Given the child-directed nature of Naturalistic Developmental Behavioral Interventions and the intervention's congruence with families' daily routines, many studies have examined the impact of Naturalistic Developmental Behavioral Interventions on family and family member quality of life. Therefore, we conducted a systematic review and meta-analysis to explore the relationship between Naturalistic Developmental Behavioral Interventions and family quality of life. Results suggest that the receipt of Naturalistic Developmental Behavioral Intervention services neither improved nor worsened family and family member quality of life. For those involved in the provision of Naturalistic Developmental Behavioral Intervention services, there is an immediate need to convey to families that children's improvements will likely not translate into improvements in family quality of life (osf.io/3ua5f). Naturalistic Developmental Behavioral Interventions have been described as culturally responsive and family-friendly interventions, with research demonstrating improvements in children's development following the receipt of these interventions. Given the child-directed nature of Naturalistic Developmental Behavioral Interventions and the intervention's integration within families' daily routines, many studies have examined the impact of Naturalistic Developmental Behavioral Interventions on family and family member quality of life. We conducted a systematic review and meta-analysis to explore the relationship between Naturalistic Developmental Behavioral Interventions and family quality of life. Results suggest that the provision of a Naturalistic Developmental Behavioral Intervention neither improved nor worsened family or family member quality of life. For those involved in delivering Naturalistic Developmental Behavioral Intervention services, there is an immediate need to convey to families that children's improvements will likely not translate into improvements in family quality of life. [ABSTRACT FROM AUTHOR]

Abstract Background The rising number of children identified with autism has led to exponential growth in for-profit applied behavior analysis (ABA) agencies and the use of highly structured approaches that may not be developmentally appropriate for young children. Multiple clinical trials support naturalistic developmental behavior interventions (NDBIs) that integrate ABA and developmental science and are considered best practices for young autistic children. The Early Start Denver Model (ESDM) is a comprehensive NDBI shown to improve social communication outcomes for young autistic children in several controlled efficacy studies. However, effectiveness data regarding NDBI use in community-based agencies are limited. Methods This study uses a community-partnered approach to test the effectiveness of ESDM compared to usual early behavioral intervention (EBI) for improving social communication and language in autistic children served by community agencies. This is a hybrid type 1 cluster-randomized controlled trial with 2 conditions: ESDM and EBI. In the intervention group, supervising providers will receive training in ESDM; in the control group, they will continue EBI as usual. We will enroll and randomize 100 supervisors (50 ESDM, 50 EBI) by region. Each supervisor enrolls 3 families of autistic children under age 5 (n = 300) and accompanying behavior technicians (n = 200). The primary outcome is child language and social communication at 6 and 12 months. Secondary outcomes include child adaptive behavior, caregiver use of ESDM strategies, and provider intervention fidelity. Child social motivation and caregiver fidelity will be tested as mediating variables. ESDM implementation determinants will be explored using mixed methods. Discussion This study will contribute novel knowledge on ESDM effectiveness, the variables that mediate and moderate child outcomes, and engagement of its mechanisms in community use. We expect results from this trial to increase community availability of this model and access to high-quality intervention for young autistic children, especially those who depend on publicly funded intervention services. Understanding implementation determinants will aid scale-up of effective models within communities. Trail registration Clinicaltrials.gov identifier number NCT06005285. Registered on August 21, 2023. Protocol version Issue date 6 August 2024; Protocol amendment number: 02.

The present study focuses on monitoring the spatial distribution of the normalized difference built-up index (NDBI) for Babylon governorate in two different years 2012 and 2022. The paper based on the LANDSAT 7, 8 data, in particular by using two bands (short-wave infrared, and near-infrared) and the Power NASA website. The spatial distribution of the NDBI was presented in two maps. Descriptive statistics of the NDBI were determined for each map (year) to describe and understand the features of the NDBI in the study area. The climate changes such as the air temperature and the land surface temperatures were studied with the change in the distribution of the NDBI in the governorate of Babylon for the period of study. The increase in NDB caused an increase in the temperature of the land surface temperature as well as in the air temperature at an altitude of 2 meters above the Earth's surface by an amount 1.5 C°. [ABSTRACT FROM AUTHOR]

The identification and systematic monitoring of water spread regions using remote sensing techniques necessitates precise temporal resolution datasets. Landsat data are one of the most popular data sources that provides satellite derived images of the Earth's surface for examining the satellite-based indices of a specific region. In the present research study, Normalized Difference Water Index is employed to identify the surface area of 11 system and non-system lakes in a part of Coimbatore region over the time span of 32 years (1990–2022). Based on the analysis, the water spread region in 1990 is seen to be 13.01 ha which gradually increased to 435.17 ha in 2022. This clearly indicates that there is substantial difference in the rainfall statistics over the years. Computations for cross-validation are done using other indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Build-up Index (NDBI). A 500 m buffer is created and calculated for vegetation and built-up indices like Chinna kulam 1 and 2, Kumaraswamy Lake, Valankulam, Singanallur and Sengulam lakes which show the decreasing trend of NDVI. Simultaneously, NDBI increased in 2000, which shows that measures were taken to tackle the encroachment of lakes in the city and the concerted efforts of the Governmental authorities and Non-governmental organizations (NGOs) were fruitful. A decreasing trend is noted in NDBI during 2011 and 2020. The microclimatic conditions and advection current of waterbodies along with boating facilities and parks in some lakes offer city dwellers a tranquil recreational area with respite from vehicular pollution and heat generation from the concrete jungle. This study will be helpful in facilitating policy decisions for future planning and sustainable development of water bodies. It will also be beneficial in devising rehabilitation measures for irrigation tanks and will aid in bringing about agrarian stability of tanks in urban locales. [ABSTRACT FROM AUTHOR]

An urban heat island emerged due to micro urban temperature variations are also referred to as urban heat islands or urban hot spots. The high-rise buildings along the roads form "Urban Canyons" that inhibit reflected radiation from the built-up surface. Urban heat island develops over the cities due to man-made activity and the landscape. An understanding of the urban heat island and its formation is not only helpful in understanding urban thermal characteristics but also helps in understanding human comfort. A geospatial technique has the ability to acquire updated and cost-effective data over large regions. For urban climatology studies, remote sensing and geographic information systems are an important source of information and an effective methodology. Since 1971, the city of Krishnanagar and its vicinity have been witnessing rapid urban growth. Due to its dense population, urban climate and rapid urban expansion, they cause environmental degradation. Appraisal and Impact of urbanization on micro-climate in the Krishnanagar city complex based on satellite derived parameters. For the years 1995, 2007 and 2018, several satellite image analysis approaches such as NDVI, NDWI and NDVI were computed. Significant differences in land surface temperature were observed between 1995 and 2007, as compared to 2007 and 2018. [ABSTRACT FROM AUTHOR]

Introduction: The effectiveness of early interventions in young autistic children is well established, but there is great interindividual variability in treatment response. Predictors of response to naturalistic developmental behavioral interventions (NDBI), like the Early Start Denver Model (ESDM), are needed. Methods: We conducted an exploratory study to prospectively seek predictors of response in 32 young children treated with ESDM after receiving an ASD diagnosis. All children were less than 39 months old (mean age: 29.7 mo), and received individualized ESDM for nine months. Tests were administered at the beginning, after 4 months, and at the end of treatment. Results: Four children (12.5%) were "strong responders", 8 children (25.0%) were "moderate responders", and 20 children (62.5%) were "poor responders". A more favorable response to ESDM was significantly predicted by higher PEP-3 Expressive Language, Receptive Language, Cognitive Verbal/Preverbal, Visuo-Motor Imitation scores, higher GMDS-ER Personal/Social, and VABS-II Communication scores, by lower ADI-R C restricted/stereotypic behaviors, and by joint attention level. Discussion: Most predictors showed a linear association with increasing response to ESDM, but GMDS-ER Personal-Social and joint attention level predicted strong response, while PEP-3 receptive language equally predicted moderate or strong response. Although larger samples will be necessary to reach definitive conclusions, in conjunction with prior reports our findings begin providing information able to assist clinicians in choosing the most appropriate treatment program for young autistic children. [ABSTRACT FROM AUTHOR]

Researchers implemented a short-term cascading coaching model focusing on naturalistic developmental behavioral intervention with three participant triads. Triads consisted of a graduate student clinician, a minimally verbal child with autism spectrum disorder, and the child's parent. Coaching and intervention occurred during an interprofessional summer clinic that included graduate student clinicians from special education and speech and hearing sciences departments. The efficacy of short-term instruction, researcher coaching for student clinicians, and student clinician coaching of parents was evaluated using a multiple baseline across participants' design. The dependent variables were student clinician's and parent's use of elicitation techniques (creating communication temptations, waiting, and prompting) and response techniques (naturally reinforcing children's communication and providing spoken language models). Following coaching, parents and student clinicians from all triads increased their use of elicitation and response techniques, with very large effect sizes across all variables. Visual analysis findings suggest individualized differences and variability across triads. Implications for graduate education and parent coaching programs are discussed. [ABSTRACT FROM AUTHOR]

Younger siblings of autistic children are at a high likelihood (HL) of autism, language, and/or cognitive delays. Vocal complexity, a continuous measure of the developmental maturity of vocal communication, is facilitated by parent-child interaction and predicts language outcomes. This study examined whether parents' intervention fidelity to Project ImPACT, a 12-week, parent-mediated, naturalistic developmental behavioral intervention (NDBI), mediated the effect of Project ImPACT on parents' verbal responsiveness (post-intervention) and children's vocal complexity (3 months post-intervention). Participants were 54 12- to 24-month-old HL child-parent dyads who received 12 weeks of Project ImPACT (n = 28) or business-as-usual (n = 26). Project ImPACT indirectly improved both parents' verbal responsiveness and children's vocal complexity by improving parents' use of the intervention techniques. The efficacy of Project ImPACT in supporting early social communication might be attributed to how Project ImPACT helps parents improve the quality and frequency of their use of the intervention strategies across children's everyday settings. [ABSTRACT FROM AUTHOR]

Over the past decade, a newer class of interventions has emerged specifically designed for young children with or at high likelihood of autism, which are called Naturalistic Developmental Behavioral Interventions (NDBIs). NDBIs are particularly well-suited as a discipline agnostic, primary intervention for young children with autism and other social communication challenges; however, community providers from multiple disciplinary backgrounds who serve these children typically do not develop competencies in areas crucial for effectively implementing NDBI. The goal of this commentary is to: (a) describe the interdisciplinary competencies needed to deliver NDBIs effectively and (b) provide recommendations for moving the field of early intervention for autism and social communication delays forward. Resources for building these competencies for providers at the pre- and in-service level are also provided. [ABSTRACT FROM AUTHOR]

Limited research has examined the active ingredients and mechanisms of change of naturalistic developmental behavioral interventions (NDBIs). The present study used an exploratory sequential mixed-methods design to develop a comprehensive Theory of Change of Project ImPACT, an empirically supported NDBI. We used qualitative data from interviews with intervention experts (n = 10), community providers (n = 22), and caregivers (n = 12) to develop a comprehensive causal model of the intervention process. We then tested select paths of the causal model using path analyses with an archival dataset (n = 92). The causal model described how developmental techniques aimed at supporting children's attention and engagement lay the foundation for more adult-directed learning opportunities and subsequent child skill growth. However, hypothesized causal relationships were not supported by our quantitative analyses. In the future, this research can be used to develop and prioritize nuanced research questions related to the timing, optimization, and mechanistic process underlying NDBIs. [ABSTRACT FROM AUTHOR]

The interactions between the normalised difference vegetation index (NDVI), the normalised difference built-up index (NDBI), and land surface temperature (LST) are complex. The assessment of land use/land cover (LULC) changes in the North-western region of Algeria between 1995 and 2021 confirms the direct influence of these factors on surface thermal processes. The use of new information technologies, particularly remote sensing coupled with GIS, favourably contributes to the processing of a large volume of data and to the use of specific methods aimed at confirming and/or disproving the hypotheses put forward. The application of LULC classification methods clearly highlights the magnitude of transformations, predominantly in favour of intensified urbanisation over the past two decades. Indeed, agricultural lands have experienced a reduction of 17.45%, while urbanised areas have nearly doubled. This phenomenon can, in part, be attributed to the mass migration of populations from inland areas to the coast, not only due to climate change: secondary for political problems between 1990 and 2001. Similarly, barren lands have increased by 10.45%. These changes have real implications for ecosystems (mainly loss of biodiversity) and the climate (pollution, GHG emissions, and rising ambient temperatures). The estimation of average LST from multiple satellite scenes reveals an increasing trend, rising from 36.6 °C in 1995 to 40.35 °C in 2021. The direct relationship between LST and NDVI and between LST and NDBI confirms the close association between land use change and increasing surface temperatures. The Pearson coefficient between LST and NDVI showed a negative correlation, ranging between -0.52 and -0.47, while it was positively correlated between LST and NDBI, with values around 0.66. The emergence of hotspots in the region, confirmed by the results of analysis employing the Getis-Ord G* method, is marked by clearly increasing spatial envelopes. This phenomenon is associated with a distinct reduction in vegetation cover density, coupled with an increased vulnerability to drought conditions. These initial results argue in favour of preserving green and blue networks and, more largely, ecosystems. [ABSTRACT FROM AUTHOR]

The interactions between the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built-Up Index (NDBI), and Land Surface Temperature (LST) are complex. The assessment of Land Use/Land Cover (LULC) changes in the North-western region of Algeria between 1995 and 2021 confirms the direct influence of these factors on surface thermal processes (LST). The use of new information technologies, particularly remote sensing coupled with GIS, favourably contributes to the processing of a large volume of data and to the use of specific methods aimed at confirming and/or disproving the hypotheses put forward. The application of LULC classification methods clearly highlights the magnitude of transformations, predominantly in favor of intensified urbanization over the past two decades. Indeed, agricultural lands have experienced a reduction of 17.45%, while urbanized areas have nearly doubled. This phenomenon can, in part, be attributed to the mass migration of populations from inland areas to the coast due to climate change not only: secondary for political problems between 1990 and 2001. Similarly, barren lands have increased by 10.45%. These changes have real implications for ecosystems (mainly loss of biodiversity) and the climate (pollution, GHG emissions, and rising ambient temperatures), often leading to the creation of in certain places. The estimation of average LST from multiple satellite scenes reveals an increasing trend, rising from 36.61°C in 1995 to 40.35°C in 2021. The direct relationship between LST and NDVI and between LST and NDBI confirms the close association between land use change and increasing surface temperatures. The Pearson coefficient between LST and NDVI showed a negative correlation, ranging between -0.52 and -0.47, while it was positively correlated between LST and NDBI, with values around 0.66. The emergence of hotspots in the region, confirmed by analysis results employing the Getis-Ord G* method, is marked by clearly increasing spatial envelopes. This phenomenon is associated with a distinct reduction in vegetation cover density, coupled with an increased vulnerability to drought conditions. These initial results argue in favor of preserving green and blue networks and, more largely, ecosystems.

Land use and land cover (LULC) analysis gives important information on how the region has evolved over time. Kerala, a land with an extensive and dynamic history of land-use changes, has, until now, lacked comprehensive investigations into this history. So the current study focuses on Kerala, one of the ecologically diverse states in India with complex topography, through Landsat images taken from 1990 to 2020 using two different machine learning classifications, random forest (RF) and classification and regression trees (CART) on Google Earth Engine (GEE) platform. RF and CART are versatile machine learning algorithms frequently employed for classification and regression, offering effective tools for predictive modelling across diverse domains due to their flexibility and data-handling capabilities. Normalised Difference Vegetation Index (NDVI), Normalised Differences Built-up Index (NDBI), Modified Normalised Difference Water Index (MNDWI), and Bare soil index (BSI) are integral indices utilised to enhance the precision of land use and land cover classification in satellite imagery, playing a crucial role by providing valuable insights into specific landscape attributes that may be challenging to identify using individual spectral bands alone. The results showed that the performance of RF is better than that of CART in all the years. Thus, RF algorithm outputs are used to infer the change in the LULC for three decades. The changes in the NDVI values point out the loss of vegetation for the urban area expansion during the study period. The increasing value of NDBI and BSI in the state indicates growth in high-density built-up areas and barren land. The slight reduction in the value of MNDWI indicates the shrinking water bodies in the state. The results of LULC showed the urban expansion (158.2%) and loss of agricultural area (15.52%) in the region during the study period. It was noted the area of the barren class, as well as the water class, decreased steadily from 1990 to 2020. The results of the current study will provide insight into the land-use planners, government, and non-governmental organizations (NGOs) for the necessary sustainable land-use practices. [ABSTRACT FROM AUTHOR]

Remote sensing plays a vital role in analyzing urban changes. In this regard, various datasets collected from satellites today serve as a foundation for decision-makers and urban planners. This study compares the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-up Index (NDBI) as indicators for the creation of surface heat islands. Using Landsat 8 OLI/TIRS C2 L2 images, spatial correlations between land surface temperature (LST) were examined for August 2013, 2019 and 2023. Urban heat islands (UHI) are a contemporary phenomenon and increasingly common in large urban areas compared to surrounding, less populated areas. With the advancement in remote sensing, it is possible to adequately determine the spatial differentiation and prevalence of urban heat islands (UHI). The study is based on Landsat 8 satellite image sets for the Sarajevo basin in August 2013, 2019 and 2023, which were used to analyze LST, NDVI, and NDBI indices. This work indicates a relationship between LST and NDVI but varies depending on the analyzed year. Normalized Difference Built-up Index (NDBI) serves as a suitable indicator for surface UHI effects and can be used as an indicator to assess its spatial distribution within a larger urban environment. [ABSTRACT FROM AUTHOR]

The earth's surface comprises different kinds of land cover, water resources, and soil, which create environmental factors for varied animals, plants, and humans. Knowing the significant effects of land cover is crucial for long-term development, climate change modeling, and preserving ecosystems. In this research, the Google Earth Engine platform and freely available Landsat imagery were used to investigate the impact of the expansion and degradation in urbanized areas, watersheds, and vegetative cover on the land surface temperature in Baghdad from 2004 to 2021. Land cover indices such as the Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index (NDVI, NDWI, and NDBI) were determined to examine the effects of land cover changes. In addition, the land surface temperature was calculated to assess urbanization expansion's impact on Baghdad's climate warming. The results showed a drastic decrease in vegetative cover and green land, on the other hand, a significant expansion in urbanized areas. Hence, from 2004 to 2021, the urbanized areas and open land rose by 37% and 3%, respectively, while the vegetative cover decreased by 41%. The maximum land surface temperature has risen 4° C, and the minimum land surface temperature has risen 2.5°C. [ABSTRACT FROM AUTHOR]

The growing importance of climate change underlines the need to comprehend Urban Heat Islands (UHI), particularly those influenced by urban morphology. As progress has been made in understanding the macroscale relationship between urban morphology and UHIs, the microscale effects are often overlooked. This study, conducted in the city of Erzurum in Turkey, delves into the complex relationship between urban morphology and UHI intensity in different housing areas with distinct microclimates, focusing particularly on street networks, building systems, and land use. Pearson correlation analysis was performed to investigate the relationships between morphological indicators and UHIs in different housing areas. Key findings include that (1) noticeable UHI effects were observed, especially in dense areas with high-rise buildings. (2) UHIs reveal a strong correlation with both 2D and 3D urban morphological indicators. A moderate-to-high Sky View Factor (SVF) tends to reduce UHIs, while an extremely high SVF aggravates UHIs. (3) Enhancing street network integration emerges as a more effective strategy for mitigating UHI effects in mid-rise buildings compared to other morphological factors. The Normalised Difference Built-Up Index (NDBI) and Normalised Difference Vegetation Index (NDVI) may not reliably indicate UHIs in housing areas with a predominantly rural character. Consequently, this article recommends that urban morphology optimisation for UHI mitigation should prioritise spatial and indicator specificity in urban design and spatial planning for cities. Future research endeavours should investigate the influence of morphological indicators on UHI dynamics in different seasons, including various remote sensing indicators related to morphological structure, to enrich our understanding of daily UHI fluctuations within urban morphology research. [ABSTRACT FROM AUTHOR]

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The recent progress in CuMnAs and Mn3X (X = Sn, Ge, Pt) shows that antiferromagnets (AFMs) provide a promising platform for advanced spintronics device innovations. Most recently, a switchable Fermi‐arc is discovered by the ARPES technique in antiferromagnet NdBi, but the knowledge about electron‐transport property and the manipulability of the magnetic structure in NdBi is still vacant to date. In this study, SdH oscillations are successfully verified from the Dirac surface states (SSs) with 2‐dimensionality and nonzero Berry phase. Particularly, it is observed that the spin‐flop transition only appears when the external magnetical field is applied along [001] direction, and features obvious hysteresis for the first time in NdBi, which provides a powerful handle for adjusting the spin texture in NdBi. Crucially, the DFT shows the Dirac cone and the Fermi arc strongly depend on the high‐order magnetic structure of NdBi and further reveals the orbital magnetic moment of Nd plays a crucial role in fostering the peculiar SSs, leading to unveil the mystery of the band‐splitting effect and to manipulate the electronic transport, high‐effectively, in the thin film works in NdBi. It is believed that this study provides important guidance for the development of new antiferromagnet‐based spintronics devices based on cutting‐edge rare‐earth monopnictides. [ABSTRACT FROM AUTHOR]

Converting green areas and agricultural land into built-up areas is one of the most significant effects of urbanization in Iraqi cities. Greenery spaces are a fundamental requirement for any city because they promote a healthy lifestyle and preserve urban areas' aesthetic and ecological beauty. The current study examines urbanization's effect on Baghdad city vegetation and land surface temperature. The Normalized Difference Built-Up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Land Surface Temperature (LST) over Baghdad were used to determine the relationship among urban areas, vegetation areas, water bodies, and land temperature. The Baghdadvector-data from the General Survey Authority was used along with Landsat Thematic Mapper for 2004 and 2008 and Landsat Operational Land Imager for 2013, 2017, and 2021. In order to understand the correlation between urban areas, water bodies, and green areas with LST, a correlation was carried out using ArcGIS software, and a scatter diagram was made to evaluate the relationship among the elements. The results showed that the temperature increased on Baghdad's land surface between 2004 and 2021. Moreover, built-up areas increased from 17% in 2004 to 53.2% in 2021; in contrast, the green areas drastically declined by 39.7%. [ABSTRACT FROM AUTHOR]

The rapid increase in the urbanisation process and other developmental activities across the globe have increased the land surface temperature of built-up areas which is considered as an emerging urban environmental problem. The rapid unplanned urban sprawl has influenced the land use and land cover of the urban area leading to the development of the phenomenon of Urban Heat Island. The present study highlights how land use and land cover changes have impacted the land surface temperature and urban heat islands phenomenon in the greater Imphal city of Manipur in India. The study was carried out with multi-spectral and multi-temporal satellite imageries of 1988, 2000, 2011, and 2021, respectively. The extracted information from the rectified imageries highlights a significant increase in the land surface temperature in the built-up area of the city. The findings illustrate that the maximum and minimum LST of the Imphal urban area has significantly increased from 28.77 to 31.25 ℃ and 10.44 to 11.47 ℃, respectively, for the month of February from 1988 to 2021. The increase in land surface temperature is directly attributed to the increased built-up area (24.06% to 44.85%) and reduction in the urban forest cover (28.17% to 16.65%). Cumulatively, there is a 2.44 ℃ and 1.03 ℃ rise in maximum and minimum LST over three decades. The variability in the LST shows positive correlations with the NDBI and negative correlations with NDVI. The study witnessed nearly about 0.74 ℃ (maximum) and 0.31 ℃ (minimum) decadal changes in the overall LST in the greater Imphal area. [ABSTRACT FROM AUTHOR]

Los humedales costeros adyacentes a zonas urbanas, como los Pantanos de Villa en la ciudad de Lima, Perú, están sujetos a cambios constantes en el uso del suelo debido a la interacción antropogénica. Esto ha llevado a la reducción de áreas de vegetación densa, dando paso a zonas edificadas. Por esta razón, el presente artículo aborda la problemática de los cambios físicos experimentados en las zonas urbanas adyacentes al humedal, como las unidades de ordenamiento ambiental, en este caso la Zona de Protección de Afloramiento y Escorrentía Superficial (ZPAES y la Zona de Protección Paisajística de Borde (ZPB), así como el Refugio de Vida Silvestre Pantanos de Villa (RVSPV), como consecuencia de la rápida expansión urbana. Por ello, el objetivo de esta investigación es analizar la evolución espacial y temporal del entorno de los Pantanos de Villa y la urbanización dentro de las Unidades de Ordenamiento Ambiental ZPB, ZPAES y el RVSPV. Para ello, se utilizó la plataforma de Google Earth Engine (GEE) y se procesaron imágenes satelitales de los sensores Landsat 5 TM y Sentinel 2 MSI. Estas imágenes se trabajaron en la interfaz de GEE y se analizaron utilizando índices espectrales, NDVI y NDBI, mediante códigos de álgebra de mapas y el enmascaramiento de píxeles. Para la representación cartográfica, se empleó un Sistema de Información Geográfica (SIG). Los resultados muestran un aumento del 291.12% en la superficie edificada y una reducción del 26% en la superficie vegetal en los últimos 35 años, para las Unidades de Ordenamiento Ambiental ZPB y ZPAES, y el RVSPV. La reducción identificada se relaciona directamente con la expansión no planificada de la superficie urbana y las actividades antropogénicas.

Satellite imagery-based spectral indices are essential for monitoring natural resource changes and urban environments. Assessing these indices is vital for natural resource management and environmental sustainability. This study adopted geospatial techniques and satellite imagery (Landsat 5 TM and Landsat 8 OLI/TIRS) to analyze changes in key spectral indices, i.e. Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-Up Index (NDBI), and Normalized Difference Water Index (NDWI) over the past three decades (1991–2022) in the low land region of Far Western Nepal. The study examined the temporal trends and intricate relationships between these indices during this time frame. The substantial changes in NDVI, NDBI, and NDWI within the study area have been quantified from 1991 to 2022. The findings revealed significantly elevated NDBI values in 1991, 2001, and 2013 compared to 2022, while NDWI and NDVI values were consistently lower in 1991,2001, and 2013 compared to 2022. Notably, a negative correlation was observed between NDVI and both NDBI and NDWI, contrasting with the positive correlation found between NDBI and NDWI. The study underscores the potential of combining these spectral indices to evaluate vegetated areas, built-up areas, and water bodies, providing valuable insights for effective land management, urban planning, environmental monitoring, and sustainable water resource management. HIGHLIGHTS Used geospatial techniques and Landsat imagery to explore variations in spectral indices.; Examined NDVI, NDBI, and NDWI trends and their interrelationships.; Significant changes in NDVI, NDBI, and NDWI from 1991 to 2022.; Observed negative correlation between NDVI, NDBI, and NDWI; and a positive correlation between NDBI and NDWI.; Highlighted the potential of indices for mapping land features and recommended considering various factors in future research.;

Amid global concerns regarding climate change and urbanization, understanding the interplay between land use/land cover (LULC) changes, the urban heat island (UHI) effect, and land surface temperatures (LST) is paramount. This study provides an in-depth exploration of these relationships in the context of the Kamrup Metropolitan District, Northeast India, over a period of 22 years (2000–2022) and forecasts the potential implications up to 2032. Employing a high-accuracy supervised machine learning algorithm for LULC analysis, significant transformations are revealed, including the considerable growth in urban built-up areas and the corresponding decline in cultivated land. Concurrently, a progressive rise in LST is observed, underlining the escalating UHI effect. This association is further substantiated through correlation studies involving the normalized difference built-up index (NDBI) and the normalized difference vegetation index (NDVI). The study further leverages the cellular automata–artificial neural network (CA-ANN) model to project the potential scenario in 2032, indicating a predicted intensification in LST, especially in regions undergoing rapid urban expansion. The findings underscore the environmental implications of unchecked urban growth, such as rising temperatures and the intensification of UHI effects. Consequently, this research stresses the critical need for sustainable land management and urban planning strategies, as well as proactive measures to mitigate adverse environmental changes. The results serve as a vital resource for policymakers, urban planners, and environmental scientists working towards harmonizing urban growth with environmental sustainability in the face of escalating global climate change.

Abstract The recent progress in CuMnAs and Mn3X (X = Sn, Ge, Pt) shows that antiferromagnets (AFMs) provide a promising platform for advanced spintronics device innovations. Most recently, a switchable Fermi‐arc is discovered by the ARPES technique in antiferromagnet NdBi, but the knowledge about electron‐transport property and the manipulability of the magnetic structure in NdBi is still vacant to date. In this study, SdH oscillations are successfully verified from the Dirac surface states (SSs) with 2‐dimensionality and nonzero Berry phase. Particularly, it is observed that the spin‐flop transition only appears when the external magnetical field is applied along [001] direction, and features obvious hysteresis for the first time in NdBi, which provides a powerful handle for adjusting the spin texture in NdBi. Crucially, the DFT shows the Dirac cone and the Fermi arc strongly depend on the high‐order magnetic structure of NdBi and further reveals the orbital magnetic moment of Nd plays a crucial role in fostering the peculiar SSs, leading to unveil the mystery of the band‐splitting effect and to manipulate the electronic transport, high‐effectively, in the thin film works in NdBi. It is believed that this study provides important guidance for the development of new antiferromagnet‐based spintronics devices based on cutting‐edge rare‐earth monopnictides.

This study focuses on examining the historical trends of the surface urban heat island (SUHI) in relation to land use/cover (LULC) changes in Jeddah City from 2013 to 2022 using Landsat data. To achieve this, various parameters were analyzed, including LULC changes, normalized difference built-up index (NDBI), normalized difference vegetation index (NDVI), and LST. During this timeframe, Jeddah City underwent a comprehensive development initiative aimed at demolishing informal and illegal settlements and improving the overall quality of life, aligning with the Kingdom's 2030 vision. This provides an interesting opportunity to investigate the effect of these urban transformations on the variation, presence, and intensity of SUHIs. Based on the results, a significant positive correlation between the density of built-up and LST was found, while a negative relationship was noticed between NDVI and LST for all time points. Furthermore, a remarkable observation in 2022 was the complete absence of the SUHI phenomenon following the removal of old informal settlements from the city. The outcomes of this study highlight the impact of urban development and hold the potential to uncover environmental imbalances and contribute to the development of strategies to mitigate the negative effects of LULC changes, thereby restraining the rise in LST. [ABSTRACT FROM AUTHOR]

This study shows how remote sensing and Geographic Information System (GIS) can extract land surface temperature (LST) from the Landsat 5, 7, and 8 datasets. In this research, LST over Kharun's lower catchment, located in Chhattisgarh, India, has been estimated. LST data from 2000, 2006, 2011, 2016, and 2021 were analyzed to see how the LULC pattern changed and how that changed LST. In 2000, the average temperature of the study region was 27.73 °C, whereas in 2021, it reached 33.47 °C. When the average temperature values for each class were determined, it was discovered that forest and adjacent waterbodies had the lowest values, with about 24.15 °C in 2000 and 27.65 °C in 2021, whereas urban regions had more variation in values, ranging from 30.15 °C in 2000 to 38.95 °C in 2021. There could be an increase in LST over time because cities are replacing the green cover. For example, there was a notable increase of 5.74 °C in the mean LST over the research area. The findings revealed that places with extensive urban sprawl had LST between 26 and 45°, which was greater than other natural land cover types, such as vegetation and waterbodies, which was between 24 and 35°. These findings support the suggested method's effectiveness for retrieving LST from the Landsat 5, 7, and 8 thermal bands when combined with integrated GIS approaches. So, the goal of this study is to look at Land Use Change (LUC) and changes in LST using Landsat data and figure out how they are related to LST, the Normalized Difference Vegetation Index (NDVI), and the Normalized Built-up Index (NDBI), which are used as major components. [ABSTRACT FROM AUTHOR]

Due to the ongoing population increase over the past years, fast and unchecked urbanization has been occurring in the urban centers of developing nations like India. As a result, land transformation is taking place at a fast pace leading to the creation of urban heat island (UHI). Urban heat island (UHI) constitutes a significant human alteration to the Earth system. Hence, this study presents a rigorous and comprehensive analysis of the impact of land use and cover on land surface temperature (LST) in Aligarh City, Uttar Pradesh, India, using multi-dimensional satellite data. The research collected Landsat data for four different phases (1991, 2001, 2011, and 2021) and analyzed it in conjunction with land use and cover (LULC) data to identify trends and variations. The result shows a consistent increase in LST since 1991, with built-up and bare land areas exhibiting the highest temperatures across all phases. Moreover, the study found that impervious land had the most significant effect on LST, followed by water bodies and vegetation cover. The analysis of the proportion of the area with the lowest and highest LST showed interesting trends, with a greater portion of Aligarh City experiencing a temperature range between 15 and 16 °C in 2021 compared to previous years. However, the study also found that 13.55% of the area had a maximum LST of over 17 °C, which is higher than the previous measurement of 9.04%, and has been steadily increasing since 1991. The accuracy of the study was verified by detecting elevated temperatures in non-porous areas and cooler temperatures near green zones and water bodies. This study's contribution to the research community lies in the data-driven, systematic analysis of the complex relationship between land use and cover and LST in an urban environment. The study's findings suggest that alterations in land use/cover patterns have a significant impact on LST, which has important implications for urban planning policies. The research provides valuable insights for urban planners, policymakers, and city officials, as it highlights the need for sustainable and efficient urban planning policies to mitigate the effects of urban heat islands and rising temperatures. The study's results have broader implications beyond Aligarh City and can inform land-use planning and policymaking in other cities facing similar challenges. This research presents a comprehensive analysis that can serve as a framework to inform land-use planning and policymaking, contributing to the development of sustainable and efficient urban environments. [ABSTRACT FROM AUTHOR]

Amid global concerns regarding climate change and urbanization, understanding the interplay between land use/land cover (LULC) changes, the urban heat island (UHI) effect, and land surface temperatures (LST) is paramount. This study provides an in-depth exploration of these relationships in the context of the Kamrup Metropolitan District, Northeast India, over a period of 22 years (2000–2022) and forecasts the potential implications up to 2032. Employing a high-accuracy supervised machine learning algorithm for LULC analysis, significant transformations are revealed, including the considerable growth in urban built-up areas and the corresponding decline in cultivated land. Concurrently, a progressive rise in LST is observed, underlining the escalating UHI effect. This association is further substantiated through correlation studies involving the normalized difference built-up index (NDBI) and the normalized difference vegetation index (NDVI). The study further leverages the cellular automata–artificial neural network (CA-ANN) model to project the potential scenario in 2032, indicating a predicted intensification in LST, especially in regions undergoing rapid urban expansion. The findings underscore the environmental implications of unchecked urban growth, such as rising temperatures and the intensification of UHI effects. Consequently, this research stresses the critical need for sustainable land management and urban planning strategies, as well as proactive measures to mitigate adverse environmental changes. The results serve as a vital resource for policymakers, urban planners, and environmental scientists working towards harmonizing urban growth with environmental sustainability in the face of escalating global climate change. [ABSTRACT FROM AUTHOR]

Much of the urbanization that occurs in Africa creates the potential for technological development and economic growth but is also a breeding ground for environmental and health problems. This study was undertaken to evaluate the urban-induced land use/land cover (LULC) change and its contribution to the land surface temperature (LST) and urban heat fluxes from 2001 to 2021. More specifically, the study analyzed different scenarios of LULC change and retrieved the LST to evaluate the trends of the urban heat flux (UHI) in response to the urban-induced LULC change. The analysis of LULC change from 2001 to 2021 indicated that built-up and bare land showed the highest rate of increase at the expense of declining open spaces, agricultural land, and vegetation areas. The built-up areas in Nekemte and Jimma City increased by 929.25 ha (172.75%) and 2285.64 ha (226.93%) over the investigated period, respectively. The highest changes in LULC are seen in built-up areas followed by agricultural land, while the smallest changes are shown by water body followed by bare land. Built-up areas showed the highest net gain, while agricultural land experienced the greatest loss. In areas where the vegetation cover is low, low LST was depicted, and high LST was shown in areas where built-up areas were concentrated in both cities. Due to the LULC changes, the average LST increased by 1.9 °C and 2.2 °C in Nekemte and Jimma City, respectively, over the last 21 years. The urbanization-induced LULC change does not only cause changes in the hydrological process but also changes in the thermal variations and urban heat stress of the two urban centers. The result indicates that the increases in vegetation and green areas are significant in improving the heat stress and thermal characteristics of urban areas. Overall, to achieve sustainable urban development, the integration of land use with urban planning policies could be critical to the resilience of local environment and urban ecosystem. [ABSTRACT FROM AUTHOR]

هدف از این تحقیق بررسی روابط بین LST و LULC در منطقه گردنه حیران می باشد. شاخص های LULC متشکل از شاخص های تفاوت نرمال شده پوشش گیاهی (NDVI) ، تفاوت نرمال شده ساخت و ساز (NDBI) و تفاوت نرمال شده و اصلاح شده آب (MNDWI) می باشد. مساحت منطقه مورد مطالعه 95/156 کیلومتر مربع بوده که از این میزان در سال 1401، حدود 7/122 کیلومتر مربع اختصاص به پهنه جنگلی داشته و تنها 2/33 کیلومتر مربع اختصاص به زمین کشاورزی دارد. مقادیر شاخص MNDWI در غنی ترین منطقه در سال 1397 از مساحتی معادل 27/12 کیلومتر مربع برخوردار بوده و با کاهش شدید در سال 1401 مواجه شده و به 68/1 کیلومتر مربع رسیده است. پهنه های ساخت و ساز شده (NDBI) تا سال 1397 با افزایش مواجه بوده و تا سال 1401 با کاهش قابل توجهی روبرو گردید. حداکثر دمای سطح زمین (LST) از 42/35 درجه سانتیگراد در سال 1392 به 04/39 درجه سانتیگراد در سال 1401 رسیده است. پهنه برخوردار از دمای 20 تا 25 درجه سانتیگراد از 9/67 کیلومتر مربع به 124 کیلومتر مربع رسیده است. در نهایت، روابط همبستگی پیرسون نشان داد که شاخص NDVI و MNDWI با شاخص LST از همبستگی منفی برخوردار بوده و بین شاخص LST با شاخص NDBI همبستگی مثبت برقرار است. بیشترین همبستگی مثبت به میزان 77/0 بین LST و NDBI مربوط به بهار 1397 بوده و بیشترین همبستگی منفی به میزان 71/0- متعلق به شاخص MNDWI و LST بوده که در پاییز 1397 به ثبت رسیده است.

Increased urbanization and growing needs in urban areas resulted in causing extensive changes to the land use land cover (LULC) of urban areas. It was observed from many previous studies that the LULC changes in urban areas result in short and long-term repercussions, including increased land surface temperature (LST) and urban heat island. However, the established relationship between the LULC changes and LST needs a deeper understanding. This study examines and explores the relationship between the LULC changes in Bengaluru, India, and the corresponding impact on the LST. LULC classification done using Landsat images revealed that over 50% of vegetation had been lost between 2003 and 2021, while the built-up area had nearly doubled during the same period. Subsequently, the city experienced an increase in the minimum temperature from 16 °C in 2003 to 21 °C in 2021, whereas the mean LST had increased from 26 °C in 2003 to 29 °C in 2021. Spatial aggregation of the LST is examined using Moran's I spatial autocorrelation, and the results suggested moderately clustered LST values in the study area. Spatial indicators like normalized differentiated vegetative index (NDVI) and normalized differentiated built index (NDBI) are calculated and compared against the LST using scatter plots. The relationship is identified using simple linear regression (SLR) and geographically weighted regression (GWR), considering the non-spatial and spatial attributes inherently present within the data. Results from GWR suggest a more defined relationship between LULC and LST, NDVI, and NDBI than SLR. While NDVI exhibited a negative relationship with LST, NDBI displayed a positive relationship with LST. The results from this study highlight the need for planned growth of urban areas with sustained growth in vegetated areas through urban planning and design strategies, which can help contain the increase in LST in future scenarios. [ABSTRACT FROM AUTHOR]

Tiruppur is one of India's major textile cities in Tamil Nadu, India, and it is seeing fast urbanization. Tiruppur, like other cities throughout the world, confronts urbanization issues. The prediction of urban expansion supports planners in identifying the urbanization trend and thereby planning appropriately. There are several approaches for forecasting urbanization trends, and this study attempts to forecast the urbanization trend using logistic regression (LR) and frequency ratio (FR) to create the Urban Growth Probability Index (UGPI) map for the year 2001. The FR and LR models can be used to predict the urbanization trend for the year 2021. For the current study, elevation, slope, aspect, the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built-up Index (NDBI), distance from roads, rivers, lakes, the Land Use Land Cover (LULC) map for the years 1991 and 2001, and the population density map for the years 1991 and 2001 are regarded as independent variables and urban growth (UG) from 1991 to 2001 as the dependent variable. The UGPI map of the LR and FR models clearly showed population density, NDVI, NDBI, and LULC as isolated factors that have a strong correlation with urban development, and by changing the factors to the model, prediction of urban growth for any year is possible. The results clearly conclude that the urban sprawl is more towards the north and north-western regions due to the presence of more commercial and industrial centres, whereas the southern region shows very less urban sprawl due to the absence of industrial centres and witness more agricultural activities. It is now easier for planners to predict where the real growth in the study area will occur based on the results of the current work in the application of FR and LR models for UGPI attempts to determine the variables that are connected directly. [ABSTRACT FROM AUTHOR]

The main objective of this study is to show which of the LST-NDVI and LST-NDBI relationships can determine the most accurate index that can be used as an indicator of the effects of urban heat islands in the municipality of Guelma, using Landsat data. 8 OLI/TIRS and the geographic information system. The application of the calculation formulas made it possible to extract the Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built up Index (NDBI) of the municipality of Guelma for the four seasons of 2019. This calculation led to the determination of the relationship between all three indicators. The results obtained show a strong correlation between the LST and the NDBI for the four seasons of the year. They suggest that the NDBI is an accurate indicator of the heat island effect in Guelma. This indicator can serve as a tool for future urban planning by those in charge of this department. However, there is currently and urgent need to strengthen strategies for reducing the effects of urban heat islands in order to preserve the quality of urban life of the inhabitants and by setting up emergency programs. [ABSTRACT FROM AUTHOR]

ABSTRACTThe study focuses on evaluating the relationship between land surface temperature (LST) with four land use/land cover (LULC) indices (MNDWI, NDBaI, NDBI, and NDVI) in Hyderabad City of India using four Landsat 8 data from the winter season of 2020–21. Pearson’s linear correlation coefficient method is applied in determining the correlation analysis. The results represent a stable status of the indices in the winter season as the range of the mean is significantly low (0.04 for MNDWI, 0.04 for NDBaI, 0.02 for NDBI, and 0.05 for NDVI). All the LULC indices are very stable with each other. Moreover, these indices also build a stable relationship with LST. The indices respond differently to the change of LST. LST builds a neutral relationship with NDVI (average r = −0.07), a moderate negative relationship with MNDWI (average r = −0.57), and a moderate positive relationship with NDBaI (average r = 0.48) and NDBI (average r = 0.55). The dry winter season affects the vegetation life and generates a neutral relationship between LST and NDVI. Built-up and bare land surfaces enhance the LST while water surface reduces the LST. The study is suitable for a stable land use planning system.

Fast and accurate impervious surface extraction is important to monitor urban dynamics and ensure people's well-being. In order to improve the extraction accuracy of impervious surface, a composite impervious surface extraction index CBI based on NDBI, NDVI and MNDWI is proposed in the paper. The impervious surface extraction images in different land cover areas were compared with the NDBI and NDISI, respectively, and were assessed by using visual and statistical analysis. The results show that CBI has good robustness, less affected by the type of ground objects and sensors. The Kappa coefficients of CBI are the highest in different sensors and OLI images with different land cover areas, and the overall accuracy is above 91%. In the area with high coverage of vegetation and water, the extraction accuracy of CBI was significantly improved. CBI is more suitable for areas with high coverage of vegetation and water and has an improved Kappa coefficient of 0.1116 than that of the areas containing only a small amount of water and vegetation. As the NDISI algorithm uses the thermal infrared band, when the area of the study area is small, its extraction accuracy is low, indicating that the accuracy of the algorithm is affected by the size of the study area.

The study focused on investigating the seasonal and spatiotemporal relationship between the relationships of LST with four spectral indices (MNDWI, NDBaI, NDBI, and NDVI) in and around Manipur City of India using eight cloud-free Landsat data from the summer and winter seasons for 1991, 2001, 2011, and 2021. These spectral indices respond differently to the change of LST in an urban landscape. Pearson’s linear correlation coefficient was the basis of the correlation analysis. The study finds that LST builds a moderate negative relationship with NDVI (R = -0.42) and MNDWI (R = -0.42), a moderate positive relationship with NDBaI (R=0.48), and NDBI (R = 0.61). The relationship is more stable in the winter season (CV = 7.31, 7.04, 10.45, and 28.71 for MNDWI, NDBaI, NDBI, and NDVI, respectively) than in summer (CV = 44.46, 36.09, 23.67, and 29.71 for MNDWI, NDBaI, NDBI, and NDVI, respectively). The strength of the relationship is gradually increasing in the winter season while there is no such effect noticed on the trend in the summer season. The LST-NDBI relationship is the most consistent (CV = 18.19), while the LST-NDVI relationship is the most variable (CV = 30.37).

In recent years, climate change has caused an increase in the air temperature and consequently the temperature of the earth's surface. The temperature of the earth's surface has had various effects on urban life and has caused the formation of thermal islands in cities. Thermal islands are one of the important criteria in regional planning. The city of Shiraz is considered to be a large population center in the southwest of Iran on the one hand and one of the important tourism centers of Iran on the other hand, so the purpose of this research is to monitor the spatial form of thermal islands in this city. The satellite images of Shiraz city were first collected and extracted in the hot periods of the year from 1985-to 2020 using the data of Landsat’s 4 and 5 (TM), 7 (ETM+), and 8 (OLI/TIRS). After required preprocessing, the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Normalized Difference Built-up Index (NDBI), and the urban heat dispersion index were determined by the Urban Thermal Field Variance Index (UTFVI). The regions with UHI, the variation of the temperature in the city, and the relationship between the LST and surface vegetation were evaluated based on the results of image processing to determine the UHIs of Shiraz. The temporal variations of the temperature pattern of Shiraz city indicated that about 12.76 km2 was added to the area of the fourth temperature class from 1985 to 2020. Results of NDVI evaluation in the studied period showed a decline in the vegetation from 22.28 km2 in 1985 to 17.54 km2 in 2020 due to alteration of the land use which can explain the formation and increase of the UHIs in the mentioned regions. At the beginning of the investigated period (1985), the temperature of the earth's surface was 17°Celsius and reached 21°Celsius at the end of the period (2020). The monitoring of the spatial form of the surface temperature of the earth shows that heat islands are moving from the outskirts of the city towards the city center. UTFVI also revealed that the awful regions (very hot temperatures) are mainly concentrated in the west and north-west to the south west of Shiraz (including some parts of districts 9 and 10), south east of district 7, and north of district 1.

Rapid urbanization and land use transformation coupled with climate change impact are witnessed for development urban heat island worldwide and make it major environmental concerns for human health. National Capital Region (NCR) is one of the fast sprawling National Capital city of India. The aim of the present study is to explore the spatial changes in major biophysical parameters of city over last 20 years from 2000 to 2020 using satellite data. The spatial variation in the land surface temperature and its relation with Land use, NDVI and Built-up area were evaluated and discussed in the present work. The major changes were observed in minimum and maximum temperature of the city, in 2000 minimum temperature was 23.20 °C and maximum 34.85 °C, which increased to 26.31 and 39.92 °C in 2010; and 31.70 to 44.74 °C in 2020 . Normalized differential vegetation index (NDVI) decrease from 82 to 62%, Non-Vegetated area has reduced to 62% from 82% due to fast urbanization and land transformation in last two decades. Barren and fallow land also reduces about 27% in last two decades and built-up area also shown increasing trend . The spatial changes in biophysical parameter of the city clearly indicated that NDVI, NDBI and Land use/land cover charges are the main driving forces for development of urban heat island in the city and many health issues related to heat waves are already reported in the city along with many other negative impacts on natural landscape and resources. The observations from present work will be very useful scientific information to understand the causes of elevated land surface temperature and mitigation measures. Results could be used by policy makers to develop the suitable model for long term sustainability of the cities.