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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]

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]

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]

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]

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]

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]

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]

Copyright of Iraqi Journal of Science is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Copyright of Anales de Geografía de la Universidad Complutense is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

Copyright of Iraqi Journal of Science is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

High levels of rainfall, tidal flooding, land subsidence, intensified urban development, scarce barren land and a shortage of green open spaces (GOS) are contributing factors to the persistent flooding in Jakarta. Therefore, this study was conducted to map the GOS, built-up, and barren land in the city in order to calculate the biopore infiltration hole (LRB) potential for water infiltration as part of Jakarta's flood mitigation efforts using the Landsat 8 operational land imager (OLI). The Landsat data acquired on September 11, 2019, with path/row 122/064 were processed using the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) method for the radiometric correction, and geometric correction with a root mean square error (RMSE) of 7.57 meters. Moreover, the normalized difference vegetation index (NDVI) was applied to classify the GOS, the normalized difference built-up index (NDBI) for the built-up areas, and the normalized difference barren land index (NDBaI) for barren land areas which were further confirmed using NDBI to distinguish them from the built-up areas. It is also important to note that the LRB potential was calculated by adding the GOS and barren land, dividing the result by the ideal land area multiplied by the ideal number of holes. The results showed that the GOS, built-up area, and barren land were 8.34%, 85.29%, and 2.48%, respectively. Furthermore, the LRB potential through the optimization of GOS and barren land was found to be 70.06 km2 and produced 16,816,248 LRB (18.27% of total needed). The realization of this value is expected to reduce the potential inundation in Jakarta by 15.6%. [ABSTRACT FROM AUTHOR]

Increasing land surface temperature (LST) is one of the major urban climatology problems arising in urban development. In this paper, the impact of vegetation and built-up areas on the LST and impact of LST on human health are assessed using the Landsat thermal data in Bartin, Turkey. The results show that there is a constant change in the share of vegetation and built-up areas due to rapid urbanization in Bartin. Strong positive correlation has been found between NDBI and LST while strong negative correlation has been found between NDVI and LST, suggesting their strong impacts on land surface temperatures. Similarly, a strong positive correlation has been observed between LST, sleep deprivation, and heat stress. This study provides precise information on effects of urbanization and man-made activities, which cause major changes in micro-climate and human health in the city. This study can assist decision-makers or planners to plan future developments sustainably. [ABSTRACT FROM AUTHOR]

Copyright of Nigde Omer Halisdemir University Journal of Engineering Sciences / Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi is the property of Nigde Omer Halisdemir Universitesi (NOHU), Muhendislik Fakultesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Natural and man-made changes in the environment cause surface heating or cooling in the metropolitan areas in comparison with the rural areas. The urban area and surrounding rural areas have differences in energy balance due to variations in surface characteristics. These differences in temperature are the main reason for the formation of Urban Heat Islands or Urban Cool Islands. This research explores the spatio-temporal variations in surface temperatures during the daytime in Bhopal city—a case of the fast-developing metropolitan city having a composite climate. To explore the surface cool island phenomena, this research built a temporal and spatial difference in Local Climate Zones (LCZ) with Land Surface Temperature (LST) and Spatial indices. Remotely sensed Satellite data—Landsat-5 and Landsat-8, from 1990 to 1995 and 2015 to 2020, were acquired to investigate the LST and generate the LCZs. Both pre-monsoon and post-monsoon period data were analysed. LCZ was classified on the basis of built-up area, vegetation, and agricultural areas of Bhopal. The LCZ classes were analysed with LST, and LST was further correlated with vegetation and moisture indices using Pearson's correlation. Different indices are investigated in order to determine the major causes of observed LST patterns in different LCZ. A linear negative correlation was found between NDVI and LST up to − 0.4 at 0.01 significance. The statistical association between NDBI and LST has shown a positive correlation across the seasons, indicating that impervious surfaces result in high surface temperatures. The LST of water surfaces, i.e. LCZ G is 3 °C to 5 °C lower than that of other LCZ classes. The moisture Index (NDMI) and LST have a negative correlation of −0.55 that was greater and more consistent. The result from 1990 to 2020 shows that the LST of LCZ in rural areas of Bhopal is almost 2.5 °C to 3 °C higher than the urban area LCZs. The above spatio-temporal analysis of LST thus confirms the formation of Surface Urban Cool Island in the Bhopal urban area during day time and has a comparatively low surface temperature as compared to its surroundings. [ABSTRACT FROM AUTHOR]

We reexamined the efficacy of Pathways early autism intervention using generalized measures of social communication and language skills administered by an unfamiliar adult in a novel environment. Generalized measures improve on sources of measurement bias. Sixty-seven autistic children blocked on age (under versus over 3 years) were randomly assigned to 15 weeks of Pathways or services-as-usual. Age moderated the effects of Pathways for social communication. Specifically, Pathways had a significantly large effect for children under 3 and a small effect that approached significance for children over 3. Pathways also had a small effect on expressive speech/language skills. Results replicate previous findings of the efficacy of Pathways on proximal and distal skills and support the importance of early intervention. [ABSTRACT FROM AUTHOR]

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

The purpose of this study was to analyze the trend of change in land use land cover (LULC) and land surface temperature (LST) in Mirpur and its surrounding area over the last 30 years using Landsat satellite images and remote sensing indices, and to develop relationships between LULC types and LST, as well as to analyze their impact on local warming. Using this analyzed data, a further projection of LULC and LST change over the next two decades was made. From 1989 to 2019, 5-year intervals of Landsat 4–5 TM and Landsat 8 OLI images were utilized to track the relationship between LULC changes and LST. The modeled LST was validated with MODIS-derived LST within the study area. Cellular automata-based artificial neural network (CA-ANN) algorithm was used to model the LULC and LST maps for the year 2039. The Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-up Index (NDBI) were analyzed to determine their link with LST. The relation between LST and LULC types indicates that built-up area raises LST by substituting non-evaporating surfaces for natural vegetation. The average surface temperature was increasing steadily for the last 30 years. For the year 2019, it was determined that roughly 86% of total land area has been converted to built-up area and that 89% of land area had an LST greater than 28 °C. According to the study, if the current trend continues, 72% of the Mirpur area is predicted to see temperatures near 32 °C in 2039. Additionally, LST had a significant positive association with NDBI and a negative correlation with NDVI. The overall accuracy of LULC was greater than 90%, with a kappa coefficient of 0.83. The study may assist urban planners and environmental engineers in comprehending and recommending effective policy measures and plans to mitigate the consequences of LULC. [ABSTRACT FROM AUTHOR]

Copyright of Journal of The Planner & Development is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Jakarta, as a metropolitan city, has a complexity of urban problems, one of which is the shape of the city, which is spread out and results in people's dependence on motorized vehicles. Transit-oriented development (TOD) areas are one alternative to solving these problems by increasing density and accessibility between destinations and integrating modes of public transportation. This article aims to predict the occupancy density that has not been optimized by vertical development to optimize the use of space in the Dukuh Atas TOD area through spatial analysis. This study uses quantitative analysis through the Geographic Information System (GIS) method by analyzing land suitability through overlay techniques, calculating environmental carrying capacity in residential areas, analyzing building density index using the Normalized Difference Built-up Index (NDBI) method, and extracting dense areas by superimposing on Floor Area Ratio (FAR) data. Based on the results of the conformity analysis, it was found that there were areas that were not suitable for approximately 16.33% of the total area of the Dukuh Atas TOD area, especially in the western part. The calculation of environmental carrying capacity results shows that the TOD area of Dukuh Atas can still accommodate 2.05 times the current population. To re-optimize it, an allocation of residential density area is generated following the FAR in Jakarta's Detailed Spatial Plan so that the maximum number of floors can be achieved. The results of these calculations can produce predictions of residential needs that are more detailed and consistent with the conditions of the TOD area in Dukuh Atas. [ABSTRACT FROM AUTHOR]

Land is a vital component of nature around the world and is essential for humans, terrestrial plants, and animals. However, urbanization is growing worldwide and the groundwater quality in urban areas is declining due to rapid development, industrialization, and pollution. Hence, it is important to determine the hydrogeochemistry and changes concerning land use and land cover (LULC). This study was conducted to investigate the hydrogeochemical mechanism of Sargodha, one of Pakistan's fastest-growing cities, during 2015 and 2021 under two different LULC indices named normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI). Forty-eight groundwater samples were collected in 2015 and 2021 to assess groundwater quality for domestic use and irrigation. The Piper diagram revealed that (Ca2++Mg2+–HCO3−+CO32−) and (Na++K+–SO42−+Cl−) were the main components of hydrogeochemistry in both years. The Gibbs plot and silicate weathering of groundwater samples indicated that rock dominance and silicate weathering played a major role in aquifers. Additionally, the results showed that 4% of the groundwater in 2015 and 21% of the groundwater samples in 2021 were unfit for human consumption. However, 37% and 40% of samples were considered not fit for irrigation in 2015 and 2021, respectively. The LULC, NDVI, and NDBI clearly revealed higher urban areas in 2021 compared to 2015. The relationship between groundwater parameters and land use land cover indices (NDVI and NDBI) explained that none had a major relationship. The non-carcinogenic risk showed health quotient HQ < 1, indicating no severe health risk due to nitrate (NO3−) exposure in the city. The current study suggests conducting future investigations considering a larger scale to recommend efficient management strategies, urbanization planning, and ensuring safe irrigation and drinking water to prevent groundwater pollution. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

This study describes the development of burn severity and vegetation regrowth classes using vegetation (NDVI) and bareland (NDBI) indices-based change vector analysis (VI-CVA) with a case study on the fire event that occurred at the Berbak National Park, Jambi Province, in 2015. The main objective was to determine the type and the severity level of change due to fire or vegetation regrowth, as summarised in CVA magnitude and direction images. The vegetation and bareland indices were derived from Landsat medium-resolution images to detect the degree of change caused by the forest fires. The study found that severity and vegetation regrowth could be classified into five classes: unburnt, very low, low, and moderate severity burn classes and a moderate regrowth class from bare land to oil palm plantation, and unburnt. It was also found that the performance of this CVA approach was superior to the delta normalized burn ratio (dNBR) method as indicated by its ability to detect five post-fire severity classes with 87.7% overall accuracy compared with dNBR, which detected four post-fire severity classes with 66.9% overall accuracy. This paper reports that burn severity and vegetation regrowth can be classified well using change vector analysis (CVA). CVA using an NDVI and NDBI approach was superior to the dNBR method as indicated by the accuracy difference between both methods. [ABSTRACT FROM AUTHOR]

Settlements and built-up areas can lead to the degradation of ecological systems. Good quality and efficient regional planning is therefore needed for urban areas. Spatial data and satellite imagery can be used for mapping and monitoring urban growth. Unfortunately, mapping urban areas can sometimes be difficult due to local variations, and different algorithms can provide varying results. Urban indices often rely on remote sensing reflectance, the accuracy of which can be influenced by land characteristics. No studies have examined the impact of land characteristics on the accuracy of remote sensing urban indices in the humid tropics. The purpose of this study was to compare urban and built area indices, namely EBBI, NDBI, UI, and IBI, in two climatically and topographically different cities. This study also examined the stability and relationship between these indices with environmental factors such as slope, elevation, and temperature. The results showed that EBBI was the index with the highest accuracy in both study areas: 85% for Batu City and 89.17% for Pasuruan City. Also, EBBI was the most stable index for the temporal studies. Environmental factors, especially slope and elevation, had a strong relationship with the index value applied. Therefore, these findings need to be considered in applying the index in areas that have topographical variations. [ABSTRACT FROM AUTHOR]

The study focused on deriving the LST of the Raipur City of India and generating the relationships of LST with six selected remote sensing indices, like MNDWI, NDBaI, NDBI, NDVI, NDWI, and NMDI. The entire study was performed by using 210 cloud-free Landsat data of different months from 1988 to 2019. The LST retrieval mono-window algorithm was applied in the study. Based on Pearson's linear correlation coefficient (r), the study finds that LST builds a strong positive correlation (r = 0.65) with NDBI, a moderate positive correlation (r = 0.30) with NDBaI, a weak positive correlation with NDWI (r = 0.19), a strong negative relation with NMDI (r = −0.54), and a moderate negative correlation (r = −0.38) with MNDWI and NDVI. These relationships were consistent and stronger in earlier years. The LST-NDBI correlation is the most consistent (CV = 9.09), while the LST-NDBaI correlation is the most variable (CV = 60.21). [ABSTRACT FROM AUTHOR]

Improving the urban thermal environment can enhance humans' well-being. Nevertheless, it was not clear which land-use/land-cover (LU/LC) indices were optimal for explaining land surface temperatures (LSTs) and how they affected LSTs in cities in different climatic zones, especially during the nighttime. Thus, the Aqua/MODIS and Landsat/OLI data were mainly used to explore the optimal indices of building, vegetation, water and bare soil and to analyze their effects on LSTs in eleven urban centers in global distinct climatic regions. Results showed several LU/LC indices had high probabilities of being optimal indices to explain LSTs under different conditions. The daytime LSTs were usually significantly negatively correlated with vegetation indices and positively correlated with building and bare soil indices (p < 0.05). These relationships were stronger in the summer than winter. The nighttime LSTs were usually significantly positively and negatively correlated with building and vegetation indices in the summer, respectively (p < 0.05). These correlations were generally weaker during the nighttime than daytime. The nighttime LSTs were significantly positively and negatively correlated with water and bare soil indices, respectively (p < 0.05). Significant linear multiple regressions commonly existed between daytime and nighttime LSTs and four kinds of LU/LC indices (p < 0.05). These findings helped optimize urban thermal comfort, downscale city LSTs, etc. [ABSTRACT FROM AUTHOR]

Over the recent two decades, land use/land cover (LULC) drastically changed in Estonia. Even though the population decreased by 11%, noticeable agricultural and forest land areas were turned into urban land. In this work, we analyzed those LULC changes by mapping the spatial characteristics of LULC and urban expansion in the years 2000–2019 in Estonia. Moreover, using the revealed spatiotemporal transitions of LULC, we simulated LULC and urban expansion for 2030. Landsat 5 and 8 data were used to estimate 147 spectral-textural indices in the Google Earth Engine cloud computing platform. After that, 19 selected indices were used to model LULC changes by applying the hybrid artificial neural network, cellular automata, and Markov chain analysis (ANN-CA-MCA). While determining spectral-textural indices is quite common for LULC classifications, utilization of these continues indices in LULC change detection and examining these indices at the landscape scale is still in infancy. This country-wide modeling approach provided the first comprehensive projection of future LULC utilizing spectral-textural indices. In this work, we utilized the hybrid ANN-CA-MCA model for predicting LULC in Estonia for 2030; we revealed that the predicted changes in LULC from 2019 to 2030 were similar to the observed changes from 2011 to 2019. The predicted change in the area of artificial surfaces was an increased rate of 1.33% to reach 787.04 km2 in total by 2030. Between 2019 and 2030, the other significant changes were the decrease of 34.57 km2 of forest lands and the increase of agricultural lands by 14.90 km2 and wetlands by 9.31 km2. These findings can develop a proper course of action for long-term spatial planning in Estonia. Therefore, a key policy priority should be to plan for the stable care of forest lands to maintain biodiversity. [ABSTRACT FROM AUTHOR]

The DMSP/OLS Nighttime light (NTL) data directly reflect the spatial distribution and light intensity of artificial lighting from the Earth's surface at night, and has become an emerging instrument for urbanization research, including in the monitoring of urban expansion, assessment of socio-economic vitality, and estimation of energy consumption and population. However, due to the imperfect sensor design of DMSP/OLS, the dynamic range of the digital number (DN) of NTL is limited (0, 63), leading to a significant saturation problem when describing the actual light intensity, especially in dense urban areas with high light intensity. This saturation problem masks spatial differences in light intensity and weakens the reliability of DMSP/OLS NTL data. Therefore, this study proposes a novel desaturation indicator that combines NDBI and POI, the Building and POI Density-Adjusted Nighttime Light Index (BPANTLI), to regulate the DMSP/OLS NTL saturation problem based on the spatial characteristics of urban structures and human activity intensity. The proposed method is applied to three urban agglomerations with the most severe light saturation issues in China. The geographical detector model is firstly utilized to quantify the effectiveness of NDBI and POI in reflecting the difference in light intensity distribution from the NTL potential saturation region (NTL DN value (53, 63)) and NTL unsaturation region (NTL DN value (0, 52)), so as to clarify the feasibility of developing the BPANTLI. The applicability of BPANTLI is validated through three aspects—comparison of the desaturation capacity and the performance of delineating light intensity; verification of the consistency of BPANTLI with radiometric calibration nighttime light product (RCNTL) and NPP/VIIRS data; and assessing the accuracy of the BPANTLI in estimating socio-economic parameters (GDP, electricity consumption, population density). The results indicate that the BPANTLI possesses superior capability in regulating the NTL saturation problem, achieving good performance in distinguishing inner-urban structures. The regulated results reveal a remarkably improved correspondence with the RCNTL and NPP/VIIRS data, providing a more realistic picture of the light intensity distribution. It is worth noting that, given the advantages of NDBI and POI vector data in spatial resolution, the BPANTLI established in this study can overcome the limitation of the spatial resolution of DMSP/OLS nighttime lighting data and achieve dynamic transformation of the spatial resolution. The higher spatial resolution desaturation results allow for a better characterization of the light intensity distribution. Moreover, the BPANTLI-regulated light intensity significantly improves the accuracy of estimating electricity consumption, GDP, and population density, which provides a valuable reference for urban socio-economic activity assessment. Thus, the BPANTLI proposed in this study can be considered as a reasonable desaturation method with a high application value. [ABSTRACT FROM AUTHOR]

Groundwater depletion has become a major concern all over the world. Recently, the rapid population growth and need for water and food have placed a massive strain on land and water resources. In this study, groundwater depletion resulting from land-use and climate change was investigated in the Faisalabad district, Pakistan, from 2000 to 2015. A Pearson correlation analysis between climatic parameters and land-use indices with groundwater was conducted to explore the major influencing factors. Interpolation maps of groundwater were generated using the inverse distance weighting interpolation (IDW) method. The Normalized Difference Built-up Index (NDBI) of five-year intervals demonstrated a strong increasing trend, whereas the Normalized Difference Vegetation Index (NDVI) presented a declining trend. The results also indicated a significant declining trend in groundwater levels in the region, with the annual average groundwater level decreasing at a rate of approximately 0.11 m/year. Climatic parameters (i.e., precipitation and temperature) further reveal an insignificant increasing trend estimated using the Mann–Kendall test and Sens's slope. Overall, spatial analysis results showed a statistically significant positive trend in the groundwater level of the Faisalabad district, where the NDBI ratio is high and the NDVI is low, owing to the extensive extraction of groundwater for domestic and industrial use. These findings may be useful for a better understanding of groundwater depletion in densely populated areas and could also aid in devising safety procedures for sustainable groundwater management. [ABSTRACT FROM AUTHOR]

This paper addresses the assessment of the relation of land-use dynamics and climate change based on the relationship of land surface temperature (LST), normalised difference vegetation index (NDVI) and normalised difference built up index (NDBI) using Landsat 4, 5 TM and 8 OLI/TIRS between 1989 and 2019. In situ condition was assessed using ground observations for validating satellite-derived temperature. LST was derived using NDVI-based emissivity method which uses non-linear split-window algorithm. To establish relationship among LST, NDBI and NDVI pixel-based approach was adopted. Increase in LST was observed with an increase of impervious surface and decrease of greenery. A strong positive correlation coefficient of 0.573 (P value = 0.01) was observed between LST and NDBI for the period 1989–2019 along with a strong negative correlation between LST and NDVI (r = −0.431, P value = 0.01). The correlation of NDBI–NDVI was also moderately negative (correlation coefficient = −0.284, P value = 0.01). A section of Greater Dhaka has been identified because it showed the highest rise in LST, air temperature and impervious surface and highest decrease in vegetation and rainfall. The trend of urban increase shows that in future, areas which share their boundary with Dhaka city will experience rapid urbanisation. Those areas are also expected to experience high air and surface temperature as well. [ABSTRACT FROM AUTHOR]

This study examines the environmental impacts of urban sprawl in Surat inner city in India. Urban sprawl is examined by studying land-use land-cover change from 1998 to 2016. Changes in spatial characteristics of urban land cover are further verified using Shannon's entropy. The impact of urban sprawl is examined by computing normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and normalized difference built-up index (NDBI) values. Land surface temperature (LST) is also calculated using thermal band of multi-temporal Landsat data. Regression analysis is used to calculate the correlation between LST and NDVI, NDWI and NDBI. The study showed a negative correlation between NDVI, NDWI and LST and a positive correlation between NDBI and LST. Urban areas in Surat have grown an approximately 60.41 sq.km, a 102% increase while surface temperature in Surat inner city has risen by 5.1 °C during the study period. The study also showed that temperature increase was particularly pronounced throughout areas classified as urban and bare soil and showed an increasing trend in parts of the city with dense urban areas. [ABSTRACT FROM AUTHOR]