GIS Approach Research Articles

Characterization and Classification of Soils of Chamba Block of Tehri Garhwal District of Uttarakhand, India: A Case Study from Lesser Himalayas

In the present study, an attempt was made to characterize and classify the soils occurring on different topography in the Chamba block of Tehri Garhwal district of Uttarakhand. A detailed soil survey was carried out by simple random sampling and studying master profiles using Landscape Ecological Unit’s map on 1:10000 scale to study the soils. The high-resolution remote sensing data product derived from the IRS-R2, specifically the LISS-IV data and GIS approaches were used. Nine representative pedons (covering all the soil types) were studied for their morphological, physical and chemical properties. These soils were very shallow to deep, dark grayish brown to dark brown/dark yellowish brown, brown to dark yellowish brown, dark grayish brown to olive brown and very dark grayish brown to dark yellowish brown in colour. Structure of the surface soils varied from sub-angular blocky to disturbed to single grain.Soil texture varied fromsandy loam to sandy loam, sandy loam to loam, loamy sand to sand and loam to clay loam in texture, strongly acidic to acidic (<5.5-6.5) and neutral (6.5-7.5) in reaction. The electric conductivity exhibited a range from 0.17 to 1.83 dS m-1 within surface horizons and from 0.02 to 0.80 dS m-1 within the sub-surface horizons, accompanied by organic carbon content categorized as medium (0.50-0.75%) to high (>0.75%). The exchangeable cations, specifically Ca2+, Mg2+, Na+, and K+, demonstrated variability ranging from 4.90 to 10.40, 1.30 to 4.00, 0.39 to 1.01, and 0.44 to 1.27 cmol p+kg-1, respectively, in surface horizons. Base saturation (BS) varied from 80 to 92% in surface horizons and from 68 to 91% in the sub-surface horizons. The cation exchange capacity (CEC) varied between 8.6 to 19.9 cmol p+kg-1 in surface horizons and from 2.7 to 17.2 cmol p+kg-1 in the sub-surface horizons. The soils were classified within the Entisols and Inceptisols orders. To ensure sustainable agricultural production within these soils, it is imperative to implement appropriate management strategies to mitigate the impacts of soil degradation.

Development of a localized Web-based GIS Visualization Platform as a tool for Disseminating Habitat Abundance of Aedes Mosquito Vectors in the Philippines

Abstract. Disseminating up-to-date information on dengue mosquito habitats aided by modern GIS approach would yield benefits to people being informed on the localized developments of the vector and therefore reduce people’s risk of being affected by the disease. This paper discusses the development of this monitoring and sensing mechanism through a Web-based GIS mapping and visualization. It utilizes the environmental, WHO dengue indices and weather information for a case of a city in the Philippines to visualize hotspot areas for habitats of dengue vectors. The paper would aid the government in deploying key assets and supporting DOH’s 5S drive or Search, Self, Seek, Support and Sustain strategy to curtail the spread of the disease. Through this paper, the author intends to develop a localized web-based platform Aedes mosquito vector. Presented in this study provides the data workflow from field observations and the inputs from environmental and meteorological data which has the potential to help enhance the data dissemination as well as the IEC campaign of local health leaders in reducing the mortality and morbidity of people affected by Dengue mosquitoes. This visualization platform includes an easy to set-up system using the available Web-based GIS which can be updated depending on the availability of field data and meteorological observations.

Seasonal spatial distribution of groundwater suitability in the Cabo Frio shallow coastal aquifer, Rio de Janeiro, Brazil: applying groundwater quality index and GIS approaches

Seasonal spatial distribution of groundwater suitability in the Cabo Frio shallow coastal aquifer, Rio de Janeiro, Brazil: applying groundwater quality index and GIS approaches

Mapping Rural Mobility in the Global South: Case Studies of Participatory GIS Approach for Assessments of Daily Movement Needs and Practice in Nepal and Kenya

This paper investigates rural mobility in the Global South using a participatory GIS approach to address the lack of mobility data that hampers sustainable planning to support rural development and resilience. Limited rural mobility due to poor infrastructure and financial constraints hinders social and economic activities, impeding development. The study aims to explore the socio-economic impacts of limited mobility, identify software needs for data-scarce environments, and map daily mobility patterns. Fieldwork was conducted in Kenya (2022) and Nepal (2023), collecting geographic data related to mobility. The methodology included community engagement and digital mapping using the QField app for precise data collection. The study highlights the use of participatory GIS to fill data gaps, enabling more accurate mobility assessments. Community engagement revealed gender-specific mobility patterns, with women facing particular challenges in daily activities. The study emphasizes the need for adaptable data models to reflect community-specific mobility needs and the integration of qualitative insights to propose effective and sustainable mobility solutions. This research contributes to understanding rural mobility in the Global South and demonstrates the effectiveness of participatory GIS in overcoming data scarcity and enhancing mobility analysis.

Greenspace and mental health research – the question of scale

Abstract Background Greenspaces have been proven to promote mental health and wellbeing. Research is conducted in diverse fields with various methods. However, studies and theoretical concepts frequently fail to address or define the scale of the environment in question. Furthermore, the different types of greenspace at the same scale are often inconsistently or inaccurately defined. Such limitations may impede the comparability of results and interdisciplinary understanding. The aims were therefore: 1. To provide a quantitative overview of the combinations of greenspace and mental health measures used at the ecological scales; 2. To embed the results in the existing theoretical background. Methods A systematic search and a scoping review were conducted, applying an PEO framework. The data was charted with an extraction table and analysed with regard to the ecological scales which are: landscapes, ecosystems/land-use types, and species/natural elements. Preliminary Results Generally, distinct greenspace measures are used at different scales, while the mental health measures do not show such a clear pattern. The “landscape” scale is most often assessed via GIS approaches. The scales “ecosystems” and “species” are mostly investigated via interventions. Overall, the “ecosystems” scale is the most frequent in both research and theory. Qualitative mental health measures often focus on ecosystems. However, the qualitative theoretical concepts are based on landscapes, e.g. Therapeutic Landscapes. Species and natural elements are rarely directly addressed by both studies and theories. Conclusions We propose increased attention to the types and scales of green and nature at both the theoretical and the practical research level. Established ecological scales can provide a common basis for interdisciplinary research and improve the comparability of studies. This can elucidate the potential differences in the impact of the diverse forms and dimensions of nature on human health. Key messages • The methods employed to assess the relation between greenspace and mental health vary according to the ecological scale. Ecosystems are the main focus in research and theory, species the least. • The type and scale of nature should be considered in environmental health research and theory. Established ecological scales can provide a basis for interdisciplinary comparability and understanding.

A GIS and Remote Sensing-based Approach on Supraglacial Lake Dynamics Study in the Himalayan Glaciers

ABSTRACT The formation of supraglacial lakes is one of such essential indications for the ice mass loss as well as global warming in the glaciers of the high mountains. Here, a total of 2072 glaciers with size >2km2 and supraglacial debris cover >15% were taken for the supraglacial morphodynamic study in the Himalaya. Moreover, a detailed study was performed in Everest and Uttrakhand regions as representative of eastern and western Himalaya concerning the supraglacial lake's behavior and its future consequences. Normalized elevation, feature selection techniques, cumulative frequency, and lake density were adopted for the supraglacial lake morphodynamics analysis. Lake size and lake numbers were continuously increasing since 1990 in those two sub-regions as well as in the whole Himalaya. A total of 14421, 23215, 24263 and 26112 supraglacial lakes and 58.55km2, 72.75km2, 73.34km2 and 87.75km2 of supraglacial lake size were demarcated for the years 1995, 2010, 2015 and 2019, respectively in the Himalaya. Unlike Uttarakhand and Arunachal regions, supraglacial lake density is higher in Everest, Sikkim and Bhutan regions. Most of the supraglacial lakes were gathered at the lower part of the ablation area (NE<2). Overall lake size is higher in Everest region (8.9km2) than in the Uttarakhand region (3.2km2). Similarly, Lake coalescing was also observed in Everest region only. The feature selection technique exhibited that the lake density is controlled mostly by slope followed by ice thickness and surface velocity.

Delineation of fresh groundwater potentiality zones in saline coastal aquifers, Southwest Bangladesh using remote sensing and GIS approaches.

Bay of Bengal in southern Bangladesh is a major source of water from coastal aquifers, but prone to contamination by seawater intrusion,making climate-vulnerable populations and economies unfit for potable, agricultural water, adopting crops, etc. The study area located in Khulna district lies in the southwestern coast of the country is among the most vulnerable due to its salinity issues. Therefore, this study identified fresh groundwater potential zones in the southwestern coastal zones of the country suited for community usage helping coastal peoples meet their demands. This study focused on twelve thematic layers employing remote sensing and GIS with analytical hierarchy process. Here, groundwater salinity is 84% brackish to saline over 70% of the region [electric conductivity: 295-16,295 micro-Siemens/cm]. However, groundwater chloride in 88% signifies a slightly to medium salty zone. The annual average rainfall reduced surface water infiltration in 75% of the area with little to very slightly soil salinity. The fresh groundwater resource zone has classified based on its potentiality as: very high (0.52%)-for drinking, agricultural irrigation, or industrial work; high (25%)-marginal salinity suitable for agricultural or industrial uses; low (11%)-low salinity, but usable for high salt tolerant crops in irrigation; and very low (64%)-very high groundwater salinity, and not suitable for human consumption and community uses. Finally, this study will help develop sustainable groundwater resources in the coastal region and a fresh groundwater supply plan in saline-prone areas.

Assessing glacier mass balance variations and climate drivers of Shisper and Muchuhar glaciers in the Karakoram region, Pakistan: a remote sensing and GIS approach

ABSTRACT Glaciers in the Karakoram region of Pakistan are crucial water sources for downstream communities, supporting irrigation and power generation. Global warming has led to significant glacier mass loss and size reduction, posing risks to ecology, climate, and water resources. Understanding Glacier Mass Balance (GMB) is essential for climate change insights and predicting future trends, mainly due to limited long-term GMB and Equilibrium Line Altitude (ELA) data from the Karakoram region. We employed hypsometrically controlled methods, Accumulation Area Ratio (AAR) and Accumulation Area Balance Ratio (AABR) to fill this gap. AAR values ranged from 0.4 to 0.8 at 0.5 intervals, and AABR from 0.9 to 2.2 at 0.01 intervals. Findings indicate that Shisper Glacier had a negative mass balance of –1.0 m/y w.e., with the area below ELAs expanding by 1.72 km². Muchuhar Glacier showed a negative mass balance of -0.05 m/y w.e., with the area below ELAs decreasing to 0.96 km². Surface temperature trends indicate 6.44°C in 2023, highlighting a warming trend. Rising average air temperature (Tavg) is the significant factor influencing ELAs (26% and 72%, respectively), followed by average precipitation (Pavg) at 20% and 26%. These findings highlight the critical role of temperature and precipitation in glacier mass balance.

GIS, remote sensing, and analytical hierarchy process (AHP) approach for rainwater harvesting site selection in arid regions: Feija Plain case study, Zagora (Morocco)

GIS, remote sensing, and analytical hierarchy process (AHP) approach for rainwater harvesting site selection in arid regions: Feija Plain case study, Zagora (Morocco)

Pollution source characterization and evaluation of groundwater quality utilizing an integrated approach of Water Quality Index, GIS and multivariate statistical analysis

ABSTRACT The Mid-Gangetic Plain, a vital farmland in India, faces increasing groundwater quality deterioration due to anthropogenic activities. This study aimed to assess groundwater quality and contamination sources in the region utilizing statistical methods. A total of 78 groundwater samples were collected and analyzed using standard methods. The hydrochemistry analysis of samples revealed that several parameters such as Ca2+, Mg2+, HCO3−, NO3−, F− and PO43− surpassed the limits prescribed by the Bureau of Indian Standards (BIS). The principal component analysis yielded three significant factors, explaining 68.96% variation, highlighting geogenic and anthropogenic influences on groundwater chemistry. Hierarchical cluster analysis categorized groundwater into three clusters based on the parameters with similar trends of variation. Furthermore, Discriminant analysis identified four significant variables (Mg2+, F−, Cl− and NO3−) responsible for creating the distinction among the identified clusters. Hydrogeochemical categorization and multivariate statistical analyses indicated that rock–water interaction, weathering, leaching and anthropogenic activities collectively influenced groundwater quality throughout the studied region. The Water Quality Index reveals that 59% of samples have good water quality, while 41% exhibit poor quality predominantly concentrated in the south-western, south-eastern and central regions. This study demonstrates the efficacy of statistical techniques to interpret complex datasets and grasp water quality dynamics, enhancing groundwater management.

Optimizing biomass energy production in the southern region of Iran: A deterministic MCDM and machine learning approach in GIS

This study employs a deterministic approach, distinguishing itself from other renewable energy evaluations, to assess the potential of electrical energy derived from biomass sources in the southern region of Iran. The primary objectives include pinpointing optimal locations for maximal biomass production and subsequent energy generation within distinct climates and topographies, using fuzzy- Analytic Hierarchy Process (AHP). Additionally, Principal Component Analysis (PCA) identify key factors influencing biomass and energy production. The study quantifies electrical and thermal energy derived from biomass sources across various climates. The findings indicate that regions with lower altitudes and humid climates (1530 km2) demonstrate superior biomass performance, leading to increased electrical and thermal energy production. The feature selection process highlights the significant impact of climate and soil characteristics on biomass production and energy output. Analysis of biomass energy production reveals maximum electrical energy production ranging from 674.88 kWh/ha to 711.36 kWh/ha. The results of the Long Short-Term Memory (LSTM) method confirm its high accuracy in estimating electrical energy, with a significant correlation coefficient of 0.98. We conclude that by identifying locations with the best biomass sources based on climate, it is possible to increase the derived electrical energy. These insights are critical for informing energy policies aimed at optimizing biomass energy production and its integration into sustainable power grids.

Crime scenario of North-Eastern India: An assessment through GIS approach

Crime scenario of North-Eastern India: An assessment through GIS approach

Integrated Python and GIS approach for Geomorphometric investigation of Man River Basin, Western Madhya Pradesh, India

The Narmada Valley and adjoining region are considered to be tectonically active. The Dhar Lineament is a major zone of fracture North of Narmada River running nearly parallel to Narmada Valley. The Man River Basin spreads across the Dhar Lineament and extends up to the Narmada Lineament. The present study attempts to understand the characteristics and development of the valley of Man River. The high-resolution satellite images, GIS software, and Python program have been used for this study. The nature and characteristics of Man River Valley are quite different on either side of the Dhar Lineament. For micro-level analysis the Man Basin has been divided into 37 subbasins and their geomorphometric indices have been computed and correlated. The results indicate that in the development of Man Basin the Dhar lineament has played a crucial role. The subparallel, angular, tight meanders, and contorted streams are present in drainage. The bifurcation ratio ranges between 2 and 9, the average length of higher-order is less than the average length of lower-order for 13 subbasins, and elongated sub-basins are situated in low-lying gentle plane areas. The Drainage characteristics are largely controlled by various sets of fractures (NE-SW, NW-SE, E-W, and N-S). The anomalous behavior of parameters indicates the tectonic influence in the Man Basin development.

Assessing climatic impacts on land use and land cover dynamics in Peshawar, Khyber Pakhtunkhwa, Pakistan: a remote sensing and GIS approach

Assessing climatic impacts on land use and land cover dynamics in Peshawar, Khyber Pakhtunkhwa, Pakistan: a remote sensing and GIS approach

Identification of groundwater potential zones using geospatial technologies in Meki Catchment, Ethiopia

ABSTRACT Mapping groundwater potential zones helps in precisely planning well drilling. The Meki Catchment is currently experiencing irrigation expansion and water scarcity challenges, creating a strong need for groundwater exploitation. The goal of this study was to identify groundwater potential zones (GWPZs) in the Meki Catchment using geospatial technologies to enhance water resource management and support sustainable development in the region. Eight thematic components were used in this analysis. Analytical Hierarchy Process (AHP) method was applied to ensure consistency in judgments through paired comparisons. Weighted overlay analysis was then used to evaluate the GWPZs. The study found that out of the total Meki Catchment area (226,333.26 ha), 30.68% (69,448.31 ha) has high potential, and 34% (76,963.33 ha) has good potential. Validation was conducted using ground truth data, considering existing water point field data from borewells and springs. The results of this study can help prioritize strategies to ensure the sustainable use of groundwater in the area. Drilling organizations can utilize these findings as a resource for feasibility studies in groundwater prospecting projects to locate well sites. The validation results demonstrate that potential groundwater zones can be identified more accurately using GIS and RS approaches at a lower cost.

Geospatial mapping of an Orang Asli (Indigenous People) settlement using a UAV and GIS approach

Geospatial mapping of an Orang Asli (Indigenous People) settlement using a UAV and GIS approach

Ecological and Health Risk Assessment of Heavy Metals in Groundwater within an Agricultural Ecosystem Using GIS and Multivariate Statistical Analysis (MSA): A Case Study of the Mnasra Region, Gharb Plain, Morocco

Assessing groundwater quality is essential for ensuring the sustainability of agriculture and ecosystems. This study evaluates groundwater contamination by heavy metals (HMs) using GIS approaches, multivariate statistical analysis (MSA), pollution indices (heavy metal pollution index (HPI), metal index (MI), degree of contamination (Cd), ecological risk index (ERI), and pollution index (PI)), and human health risk assessment (HHRA). The results revealed significant variations in heavy metal concentrations across the study area, with the highest concentrations found in the southern and southeastern parts, characterized by intense agricultural activities and uncontrolled landfills. Statistical analyses indicated both natural and anthropogenic sources of contamination. Pollution indices showed medium to high water pollution levels, with HPI values ranging from 20.23 to 128.60, MI values from 3.34 to 12.17, and Cd values from 2.90 to 11.73, indicating varying degrees of contamination. ERI values suggested a low ecological risk across all samples. However, health risk assessments highlighted significant non-carcinogenic and carcinogenic risks, particularly for children, with TCR values for some heavy metals like Ni and Cr exceeding safe limits, indicating potential health hazards. The findings provide a valuable framework for policymakers to develop targeted strategies for mitigating groundwater contamination and ensuring sustainable water quality management.

Landslide Risk Assessments through Multicriteria Analysis

Natural risks comprise a whole range of disasters and dangers, requiring comprehensive management through advanced assessment, forecasting, and warning systems. Our specific focus is on landslides in difficult terrains. The evaluation of landslide risks employs sophisticated multicriteria models, such as the weighted sum GIS approach, which integrates qualitative parameters. Despite the challenges posed by the rugged terrain in Northern Algeria, it is paradoxically home to a dense population attracted by valuable hydro-agricultural resources. The goal of our research is to study landslide risks in these areas, particularly in the Mila region, with the aim of constructing a mathematical model that integrates both hazard and vulnerability considerations. This complex process identifies threats and their determining factors, including geomorphology and socio-economic conditions. We developed two algorithms, the analytic hierarchy process (AHP) and the fuzzy analytic hierarchy process (FAHP), to prioritize criteria and sub-criteria by assigning weights to them, aiming to find the optimal solution. By integrating multi-source data, including satellite images and in situ measurements, into a GIS and applying the two algorithms, we successfully generated landslide susceptibility maps. The FAHP method demonstrated a higher capacity to manage uncertainty and specialist assessment errors. Finally, a comparison between the developed risk map and the observed risk inventory map revealed a strong correlation between the thematic datasets.

Optimizing Municipal Solid Waste (MSW) Collection and Transportation Network Using GIS and Agent-based Modeling Approach: A Case Study in Hung Yen City, Vietnam

Optimizing Municipal Solid Waste (MSW) Collection and Transportation Network Using GIS and Agent-based Modeling Approach: A Case Study in Hung Yen City, Vietnam

Generation of Thematic Maps for the Vishwamitri River Basin: A Remote Sensing and GIS Approach

Generation of Thematic Maps for the Vishwamitri River Basin: A Remote Sensing and GIS Approach