Asian Journal of Geographical Research

Machine Learning for Predicting Environmental Impact in Green Buildings: A Systematic Review

2025-06-20T13:21:21+00:00

The construction industry significantly contributes to global environmental challenges, accounting for approximately 40% of global energy consumption and 36% of CO2 emissions. Green building practices have emerged as a critical solution, yet accurately predicting their environmental impact remains challenging. This systematic review examines the application of machine learning (ML) techniques for predicting environmental impacts in green buildings. A comprehensive literature search identified 32 relevant studies published between 2018-2024, focusing on energy consumption prediction, carbon footprint assessment, indoor environmental quality, and lifecycle impact analysis. The findings reveal that ensemble methods, deep learning algorithms, and hybrid models demonstrate superior performance in predicting various environmental metrics. Random Forest, Support Vector Machines, and Artificial Neural Networks emerged as the most frequently employed techniques, achieving accuracy rates exceeding 80% in energy consumption predictions. Key challenges include data quality, model interpretability, and integration with building information modeling systems. This review provides insights for researchers, practitioners, and policymakers seeking to leverage ML for sustainable building design and operation.

Understanding Climate Change Perception and Knowledge in Bangladesh: A Review from a Non-global North Perspective

2025-06-25T09:40:58+00:00

This paper reviews the existing studies on scientific consensus on climate change within the framework of the gateway belief model which showed that majority of the existing studies on consensus messaging have focused and experimented in the global north. That led this study to explore public climate change perception and knowledge in Bangladesh from the existing research and examine whether the initiatives and interventions are required to be approached within the framework of the gateway belief model and thus, figure out the scope to test the gateway belief model to enhance public perception of climate change in Bangladesh. In order to identify the articles that align with the objective of this study and could answer the research question, the keywords “climate change perception” AND “climate change knowledge” AND Bangladesh were applied in Google Scholar database, and the prompt “climate change perception and knowledge of people in Bangladesh” was used in the Consensus (AI) tool, and the time frame was limited to the years between 2010 and 2025. The overall findings of the reviewed articles showed students’ perceptions of climate change vary between educational institutions in Bangladesh. Also, people that are experiencing the impact of climate change and living in high climate risk communities in Bangladesh have differences in climate change perception and knowledge due to several factors, for instance, cultural beliefs, education, economic situation, information gap, and so forth. This research concludes that in the developing country setting, explicitly Bangladesh, the gateway belief model could be tested by adapting to the localized settings applying social consensus and in-group consensus messaging to increase public perception of climate change and examine the effectiveness, which will provide a notion of whether or not the gateway belief model is relevant in the developing country context, namely Bangladesh.

Assessing Urban Green Infrastructure Transformation in Delhi (1991–2021): A Landscape Ecology and Remote Sensing Approach

2025-05-05T13:37:08+00:00

Urban green spaces (UGS) play a crucial role in ensuring ecological stability and improving the quality of life in rapidly urbanizing regions. This study investigates the long-term transformation of UGS in the National Capital Territory of Delhi (NCTD), India, over a three decades (1991–2021), a time marked by unprecedented urban expansion. Multi-temporal Landsat satellite imagery was used for analysis, including Landsat 5 TM (1991, 2001), Landsat 8 OLI (2011), and Landsat 9 OLI-2 (2021). An unsupervised classification was carried out using the ISODATA clustering algorithm in ERDAS Imagine software to classify six major land use/land cover (LULC) categories. Change detection matrices were also constructed to analyze land transitions across three decadal intervals and cumulatively over the entire study period. Landscape and class-level metrics (PLAND, PD, LPI, LSI, COHESION, CONTAG, SHDI, and SHEI) were computed to assess changes in landscape structure and spatial configuration. Results show a significant increase in built-up area (from 263.18 to 570.56 km²) primarily at the expense of agricultural land, vegetation, and open space. Forest cover demonstrated a net gain in the final decade, likely reflecting restoration efforts and reclassification, while vegetation showed consistent fragmentation and loss. The CONTAG index revealed increasing spatial aggregation, while SHDI and SHEI declined, indicating reduced landscape diversity and evenness. Class-level metrics revealed rising patch density and geometric irregularity in vegetation and forest classes, suggesting ecological fragmentation. The findings highlight the urgent need for integrated urban planning, policy reform, and proactive monitoring strategies to mitigate the ecological consequences of unbalanced urban growth. This research provides valuable insight for sustainable green space management in megacities undergoing intense land transformation.

Urban Development and Population Growth in Bhopal, Madhya Pradesh, India: Challenges and Opportunities

2025-05-06T12:00:38+00:00

The accelerating pace of urbanization globally has ushered in profound transformations in cities, particularly in developing nations like India. Bhopal, the capital of Madhya Pradesh, exemplifies this rapid urban evolution, driven by population growth, and industrial expansion. This study examines the demographic trends, spatial growth patterns, and the multifaceted challenges and opportunities arising from urban development in Bhopal. Utilizing secondary data sources, census reports, government planning documents, and satellite imagery, the research employs both quantitative and spatial analysis to map the city's transformation from a historical town into a dynamic urban center. The findings reveal a significant population increase of over 380% from 1961 to 2011, accompanied by spatial expansion from 26.3 sq km in 1975 to 185.19 sq km in 2024. Bhopal faces acute urban challenges, including inadequate water supply infrastructure, proliferation of slums, and uneven spatial development. The study highlights that 36.2% of Bhopal's population resides in slums and the city has seen a sharp decline in its Ease of Living Index ranking, underscoring governance and service delivery issues. The research identifies key opportunities presented by integrated urban planning frameworks like the Bhopal Development Plan 2031, which advocates for sustainable growth through enhanced green cover, efficient land use, infrastructure development, and public participation.

A GIS-Based Identification of Spatial Analysis of Road Density and Understanding the Pattern of Road Network in Ahilyanagar District of Maharashtra State, India

2025-05-08T09:38:18+00:00

The transportation system contributes to the socio-economic and political development of any geographical area. This factor is the most important factor for urbanization and market development. Transportation is the means of transporting any goods and people from one place to another. Although there are various types of transportation systems such as international, national, state, district, village roads, the main types of transportation systems are air, water, land, pipelines. Mean and Standard Division have been used with the help of statistical techniques to study the road traffic pattern and road density in Ahilyanagar district using GIS. With the help of statistical methods, four main types of road levels in Ahilyanagar district have been identified Very Low, Low, Moderate, and High Density or Level. For this, the calculation is done according to the index value for Mean and S.D. The overall condition of the roads density in Shrirampur Tehsil of Ahilyanagar district is excellent. Also, if we consider rural roads, the density of rural roads in Ahilyanagar district is not very low in any tehsil and it is not very high either, which means that rural roads have been developed in this study area. District roads have also been developed accordingly. But even so, if we consider according to the State Highway, the tehsils of Nevasa, Shevgaon, Pathardi, Rahuri and Parner have very low road density.

Livelihood Challenges and Transitions: Evaluating the Effects of Land Acquisition in Azamgarh, Uttar Pradesh, India

2025-05-17T11:04:23+00:00

Land acquisition for national development projects, such as road infrastructure building, urban expansion, and industrialization, is often positioned as a necessary step for economic growth. The purpose of this paper to identify the challenges faced by marginalized groups (e.g., women and indigenous people) during and after land acquisition and to measure the shift in livelihood practices, especially in agriculture and non-agriculture sectors. A case study of the livelihood conditions of a sample of 330 farmers having different land-holding sizes, residing in the selected of nearest village to the connected to Purvanchal Expressway in Azamgarh District. The study showed that there have been considerable change in occupation structure, income, land cultivated, number of households owning livestock, and total livestock numbers of various affected household. The government should amend the policy because most people will not be satisfied with compensated money. In particular, its impacts on agriculture-dependent families, landless labourers, and those engaged in traditional occupations are analysed. The research found that after the acquisition, many families faced unemployment, income instability, and breakdown of social structure. Although in some cases compensation and the possibility of urbanisation offered new economic options, they were not sufficient for the wider community. Land acquisition has disrupted the traditional agriculture-based livelihoods of the affected families. The degradation of cultivable land has not only reduced production capacity but also forced villagers to look for alternative livelihoods. Some migrated to urban areas, while others started working in construction, the unorganised sector or small businesses.

Impact of Development-Induced Resettlement on the Occupational Structure of Slum Dwellers: A Case of Cuttack City, India

2025-05-24T10:08:56+00:00

Urbanization and Urban Development often results in displacement and resettlement of slum dwellers to make a way for infrastructural development. Cuttack is the second most populated city of Odisha with very high density of population. Decades of unplanned growth and rapid increase in urban population due to rural-urban migration results in haphazardly distributed settlements with small roads, limited parking and open space, development of slums/squatter settlements within the city. In recent times, developmental activities of Cuttack city under the 5T (Transparency, Technology, Teamwork, time and Transformation) initiative of government leads to the displacement of more than 20 slums from the city centres and resettled at outer parts of the city. The main focus of this study is to examine the impacts of urban development-induced resettlement of slum dwellers on their workforce structure. This study is based on both primary and secondary data. Primary data has been collected through questionnaire survey based on simple random sampling. In this study, 180 samples collected from 100 households which constitutes approximately 5% of the total household. On other hand, secondary data has been collected from Cuttack Municipal Corporation (CMC), Google earth engine. This study used descriptive statistics and simple cartographic technique for the data analysis. This study found that resettlement of slum dwellers highly impacted on their income due to increasing working distance, change of mode of transportation and decreasing working days. This study also found that 11.1% of workers lost their work after resettlement and out of which 75% were female workers. There is 33.3% rise in use of public transportation after resettlement resulting in higher transportation cost and fall in average monthly working days. This study will help the city planners for better slum management in near future.

Effect of Climate Variability on Malaria Prevalence among Children in Elgeyo Marakwet West Sub County, Kenya

2025-05-31T07:44:13+00:00

Malaria remains an issue of great public health concern and, in developing nations, children under five years old are particularly susceptible due to hygiene and poverty. It’s caused by the parasite Plasmodium falciparum spread by female Anopheles mosquitoes and is affected by climate change, especially temperature and rainfall. The purpose of this research was to evaluate these climatic impacts on the malaria incidence in children in Elgeyo Marakwet West Sub-County through spatio-temporal spatial distribution and relationship between climate and malaria prevalence.

The study applied purposive and systematic random sampling with mathematical models to show the correlation between malaria incidence and climate using R-studio and SPSS. Results showed that climate was highly correlated with malaria prevalence, with hotter weather and more frequent rains leading to more cases of malaria. The results imply that climate change might further worsen malaria in this area, thus the necessity for an effective surveillance system using Geographic Information Systems (GIS) for real-time monitoring. There should also be a local education campaign to increase prevention, use insecticide-treated nets (ITNs), and eradicate mosquito nests.

Water Quality, Pollution and Management of Kuuru River, Meru County, Kenya

2025-06-06T12:54:53+00:00

Water pollution is a significant concern as it impacts the quality and availability of essential water resources. The Kuuru River, a tributary of the Tana River in Meru County, is vital for drinking water and irrigation. This study evaluated water quality, land use, and environmental conservation in the Kuuru River's riparian zone, from its source to the Kathita River. It also assessed institutional contributions to river conservation under the legislative framework. Turbidity, total dissolved solids (TDS), pH, temperature, electrical conductivity (EC), nitrates, and phosphates from 18 water samples. A descriptive survey using semi-structured questionnaires was administered to 384 household heads to obtain data on land use and environmental conservation practices. Semi-structured questionnaires were also administered to 6 key informants from relevant institutions to gather information on their interventions in the river protection activities. Physicochemical parameters were analysed using one-way ANOVA, and a One-sample t-test was employed to determine whether the values exceeded the permissible standards. The questionnaires were entered into SPSS software for data management, where comparative analysis was used for data analysis. Among the parameters measured TDS (94.4-230mg/L), pH (7.06-8.29), temperature (19.4-20.90C) and Nitrates (0.0045-0.0125mg/L) met the set standards by World Health Organization (WHO), the National Environmental Management Authority (NEMA), and the Kenya Bureau of Standards (KEBS) for drinking water. However, levels of EC (461S/m), turbidity (640NTU) and phosphates(3mg/L) were elevated, indicating the presence of pollutants. Anthropogenic activities in Maskani, Kanthiari, Kimachia markets and Meru-Mikinduri highway were identified as the main drivers of pollution. The study highlighted a lack of awareness regarding riparian conservation, linked to inadequate stakeholder involvement and support. It recommends periodic water quality assessments and increased stakeholder engagement for better conservation awareness.

Urban Spatial Characteristics Analysis of Siliguri (A Class One City of West Bengal, India) Using GIS Technique

2025-06-10T06:59:37+00:00

To track and evaluate the urbanization process and provide a theoretical foundation for rural restructuring and landscape dynamics, it is imperative to quantify spatiotemporal patterns of urban expansion. In order to examine the relationship between the central city and its suburbs and to assess the overall spatiotemporal features of urban expansion in Siliguri and the surrounding area, this study combines remotely sensed data, and GIS-based buffer gradient analysis. Based on the landscape expansion index, intensity index and differentiation index of urban growth, this paper presented the multifaceted features of urban expansion patterns. The findings demonstrate that while there are noticeable geographical variances, the distance from the urban center has a significant impact on the overall spatiotemporal changes of the area. According to the study, the western and southwestern regions, particularly those near highways, have had fast expansion whereas the eastern part is being held back from further expansion by natural obstacles such as forests. Edge expansion (76.73%) is the most prominent growth type, with outlying (26.13%) being the second most important growth type. Within the Municipal Corporation, there is compact expansion, but dispersed growth is more common outside the city center. This present study assists urban policy makers in understanding the composition and layout of the urban landscape. It might have a further impact on the city's sustainable development circumstances.

Geospatial Assessment of Soil Loss Using Revised Universal Soil Loss Equation (RUSLE) in the Dibrugarh District, Assam, India

2025-06-11T08:30:14+00:00

Soil erosion is a critical global challenge, leading to the loss of fertile topsoil and contributing to decreased agricultural productivity, increased sedimentation in waterways, and ecosystem disruption. This environmental problem is more vulnerable in developing countries because of farmers' failure to restore degraded soil and nutrients. The depletion of soil is driven by extensive farming practices, land degradation, and various human activities that impact the environment. It is an emerging threat to sustainable land management in Dibrugarh District, Assam. This study uses the Revised Universal Soil Loss Equation (RUSLE) model, integrated with remote sensing and GIS, to quantify soil erosion that incorporates annual average rainfall, soil properties, topographic characteristics, and LULC as inputs to detect the soil erosion-prone areas. This study divides the whole Dibrugarh district into five soil erosion severity classes, i.e., very slight, slight, moderate, severe, and very severe. The results demonstrate that 91.147% of the area experiences very slight erosion (<2 t ha-1 yr-1) while severe erosion affects 0.148% and very severe erosion impacts 0.044% of the area, requiring urgent conservation efforts. Effective soil management and targeted conservation strategies are essential to mitigate erosion and ensure the region's long-term land productivity and environmental health.

Evaluation of Petrophysical and Geomechanical Analysis of Subsurface Geological Information for Sustainable Groundwater and Engineering Development in Parts of Anaocha Local Government, Anambra State, Nigeria

2025-06-12T13:29:51+00:00

A well log is the recording of the measurement of a geophysical parameter plotted continuously against depth in the well bore. It is used to identify and correlate underground rocks, determine their lithology, generate their physical properties and the nature of the fluids they contain. The study aimed to conduct a geophysical evaluation of geologic formations for sustainable groundwater and engineering development. Electrical resistivity logging was carried out on the existing wells at Anoacha to evaluate the geological formation of the subsurface and well efficiency. The study area is positioned within the geographical coordinates of 6° 12' 25''N latitude and 7° 04' 04''E longitude. In the study area Aguluzibo location showed resistivity range from top to 40 m sandstone, 40 m – 60 m shaly sand and 60 m – 180 m is sandstone, the resistivity signal became irregular in ranges at the depth of 162 m – 180 m, this reflects the negative deflection of Spontaneous Potential (SP) long. At Awkaeze location, the lithology from the resistivity log revealed shaly sandstone at a depth of 50 m, sandstone at 50 m – 135 m, shale at a depth range of 135 m – 152 m and at terminal depth 152 m – 204 m of the drilled well is sandstone. In this location, the SP log shale baseline showed at two occurrences beds of 20 m – 75 m and 135 m – 204 m, respectively. The existing well at the Amatutu Agulu location revealed irregular deflection of SP long. The range of negative and positive deflection depicts the presence of salinity, and the resistivity value shows the predominant formation of shaly sand and sandstone. The results revealed the geological constituents of the study area. For the shaly sandstone reservoir, the presence of both top and bottom seals, along with the resistivity characteristics, helps in identifying it as a potential reservoir zone. However, the infrastructural and structural integrity concerns due to the presence of shale and the variation in resistivity with depth necessitate careful planning and advanced engineering solutions to ensure successful development and production.

Integrated Geomorphological Assessment of the Nirguna (Bhikund) River Watershed Using Remote Sensing and GIS Technique

2025-06-14T13:27:49+00:00

It has been attempted to define the different groundwater potential zones based on hydro geomorphological studies through detailed morphometric research of the Nirguna (Bhikund) river watershed in Akola and Washim Districts. Morphometric analysis is the measuring and quantitative examination of the landforms' dimensions, shapes, and configurations on Earth. A low to moderate drainage density is indicated by the research area's drainage density (D) value. Maps have been created to illustrate many topics by applying remote sensing and GIS technology. Portion and enhancing the possibility for groundwater. Additional research using high-resolution remote sensing and GIS in the field, integrating remote sensing data with ground control data is more efficient for creating the right kind of Mechanisms for managing natural resources. The examination of all morphometric parameters indicates that the drainage development has been influenced by lithology and that the erosional development of the land by the streams has advanced well. Planning for rainwater collecting and watershed management can greatly benefit from this study. The detail study of geomorphological aspects have been carried out which suggests that there are five mainly landforms have been depicted such as anthropogenic origin, denudational origin, Fluvial origin, structural origin and water bodies mainly.

Geo-spatial Analysis of AI Deployment in Education: Identifying Patterns and Predictors of Adoption in Southeast Nigeria

2025-06-16T13:18:47+00:00

The rapid evolution of Artificial Intelligence (AI) technologies is transforming global education systems, offering innovative pathways for personalized learning, administrative efficiency, and intelligent content delivery. However, disparities in regional adoption, particularly in developing contexts, remain a pressing concern. This study aims to explore the spatial distribution, intensity, and key determinants of AI integration in educational institutions across the southeastern geopolitical zone of Nigeria. Given the socio-economic and infrastructural heterogeneity of this region, a geo-spatial analytical approach will be chosen to unravel not just whether AI is being adopted, but where and why disparities exist. A convergent mixed-methods design will be employed, combining quantitative spatial analysis with qualitative inquiry to provide both breadth and depth. Using Geographic Information Systems (GIS) and remote sensing data, AI deployment patterns will be mapped to visualize adoption hotspots and lagging areas. This will be complemented by institutional surveys and interviews with education stakeholders to uncover contextual drivers and inhibitors of adoption. The choice of GIS is rooted in its capacity to spatially contextualize data, allowing for pattern recognition that would be obscured in non-spatial datasets. Quantitative data will be analyzed using the Statistical Package for the Social Sciences (SPSS) for descriptive statistics, and R programming for more advanced inferential analyses. Specifically, multiple regression, logistic regression, and Geographically Weighted Regression (GWR) will also be used to identify predictors of AI adoption such as infrastructure quality, access to digital tools, institutional policy readiness, educator digital competence, and urban-rural divide. By identifying the geospatial and systemic factors influencing AI adoption, this study provides actionable insights for policymakers, education administrators, and technology providers. It advocates for targeted interventions that address regional disparities, foster digital equity, and promote scalable AI integration strategies tailored to local realities.

Hotspot Analysis of Structure Fires in Urban Agglomeration: A Case Study of Hyderabad City, Telangana, India

2025-06-24T09:27:58+00:00

Urban structural fires pose a significant threat to life, property, and urban sustainability, particularly in rapidly growing cities like Hyderabad, India. These fires are often exacerbated by factors such as high population density, unplanned development, aging infrastructure, and inadequate fire safety regulations. Additionally, the increasing demand for electricity, mixed land use, and seasonal climatic variations contribute to heightened fire risks. This study assesses the spatial and temporal distribution of urban fire incidents within the Greater Hyderabad Municipal Corporation (GHMC) region from 2017 to 2024. Fire incidents were aggregated using a 50-meter threshold, and spatial autocorrelation analysis confirmed that these incidents are significantly clustered. Hotspot analysis using the Getis-Ord Gi* statistic yielded GiZ-scores ranging from –3.62 to 6.65. This allowed for the delineation of fire risk zones by integrating a continuous fire risk surface—generated through Inverse Distance Weighted (IDW) interpolation—with census ward boundaries using zonal statistics. From 2017 to 2024, there have been a total of 4406 structural fires in the GHMC region. The temporal analysis indicates that fire incidents peak in late winter and early summer, specifically in March and April, accounting for 12 to 12.5% of annual cases. In contrast, fire incidents decline during the monsoon months, with only 4.8 to 6.2% of cases occurring during this period. Furthermore, the analysis of fire causation indicates that careless smoking (41.9%) and electrical faults (39.1%) are the primary drivers of these events. An evaluation of fire station responses, based on State Fire Advisory Committee guidelines, shows that while 52.4% of incidents occur within the Immediate Response Zone (up to 1.8 km), 18.7% of the GHMC area falls within Delayed Response Zones (beyond 5 km), suggesting critical gaps in emergency coverage. The Central, North, and South Zones exhibit the highest concentrations of incidents, with 35 wards classified as very high risk, collectively housing approximately 1.3 million residents with population densities exceeding 17,000 people per sq km. These findings underscore the need for strategic interventions, such as repositioning or adding fire stations in high-risk areas, enhancing electrical safety protocols, implementing targeted public awareness campaigns, and adopting climate-responsive urban planning. By integrating geospatial analytics with policy insights, this research provides a replicable framework for improving fire resilience in Hyderabad and similar rapidly urbanizing regions, aligning with Sustainable Development Goal 11 and India’s Smart Cities Mission.

Geoheritage Sites in Rajasthan, India: A Strategy towards Sustainable Development

2025-05-30T11:00:42+00:00

Geoheritage refers to geological features that have significant scientific, cultural, aesthetic or educational value. Rajasthan, with its vast desert landscapes, ancient rock formations and rich fossil records, is a treasure trove of geoheritage sites. These sites not only provide insight into the earth’s geological past, but also offer significant educational, recreational and economic benefits. The Geological Survey of India has identified and protected numerous sites of geological significance, fostering both conservation and geo-tourism. This paper explores the potential of geoheritage conservation in Rajasthan as a tool for promoting sustainable development. It discusses the challenges and opportunities associated with the development and management of these sites. It examines key geoheritage sites, the threats they face, and strategies to integrate their preservation with eco-tourism, education and community participation.