Department Of Geography

Permanent URI for this communityhttps://kr.cup.edu.in/handle/32116/89

Browse

Has files: No

Search Results

Now showing 1 - 10 of 62
  • No Thumbnail Available
    Item
    Evolution of Supraglacial Lakes from 1990 to 2020 in the Himalaya�Karakoram Region Using Cloud-Based Google Earth Engine Platform
    (Springer, 2023-10-27T00:00:00) Sahu, Rakesh; Ramsankaran, Raaj; Bhambri, Rakesh; Verma, Prateek; Chand, Pritam
    Evolution of glacial lakes in the Himalayan and Karakoram (H�K) mountain ranges is an important indicator of glacier changes in response to climatic warming. The study utilized multi-temporal Landsat 4, 5, 7, and 8 images accessible in the cloud-based Google Earth Engine platform to analyse the spatiotemporal variations of the supraglacial lake (SGL) in the H�K regions from 1990 to 2020 at a decadal interval. It is observed that 61% (4.79�km2) of the SGL area increased from 1990 to 2020, while 223 new lakes formed in a similar time period. The most significant increase in the area of SGLs (30.15%; 2.93�km2) was observed between 2010 and 2020, while the slowest growth was observed between 1990 and 2000 (1.13%; 0.09�km2). The results indicate heterogeneity in SGL area changes in different regions. The region of Central Himalaya (CH) experienced the highest increase of 160% (3.8�km2) in the�SGL area from 1990 to 2020 with most of the rise in the�SGL area was observed in the Everest region, while a decrease of 9.4% (0.12�km2) was observed in the Eastern Himalaya (EH) region. During the study period, some SGLs converted into proglacial lakes in the EH region, which may be responsible for reducing the SGL area. The rise of SGL in the CH region can be attributed to higher mass loss, decreased glacier surface velocity, and increased rainfall in the�CH region. We also identified 15 glaciers that have SGLs near the terminus of the glaciers. If the same trend continues, these SGLs may soon be converted into proglacial lakes. The current inventory of SGL at a decadal scale shall be useful as baseline data for other hydro-glaciological models. � 2023, Indian Society of Remote Sensing.
  • No Thumbnail Available
    Item
    Vulnerability and risk assessment mapping of Bhitarkanika national park, Odisha, India using machine-based embedded decision support system
    (Frontiers Media SA, 2023-09-29T00:00:00) Mohanty, Shantakar; Mustak, Sk.; Singh, Dharmaveer; Van Hoang, Thanh; Mondal, Manishree; Wang, Chun-Tse
    The vulnerability and flood risk assessment of Bhitarkanika National Park in Odisha, India, was conducted using a data-driven approach and a machine-based embedded decision support system. The park, located in the estuaries of the Brahmani, Baitarani, Dharma, and Mahanadi river systems, is home to India�s second-largest mangrove environment and the world�s most active and diverse saline wetland. To evaluate its vulnerability and risk, various threats were considered, with a focus on floods. Satellite imageries, such as Landsat 8 OLI, SRTM digital elevation model, open street map, Google pro image, reference map, field survey, and other ancillary data, were utilized to develop vulnerability and risk indicators. These indicators were then reclassified into �Cost� and �Benefit� categories for better understanding. The factors were standardized using the max-min standardization method before being fed into the vulnerability and risk model. Initially, an analytical hierarchy approach was used to develop the model, which was later compared with machine learning algorithms (e.g., SVM) and uncertainty analysis indices (e.g., overall accuracy, kappa, map quality, etc.). The results showed that the SVM-RBF machine learning algorithm outperformed the traditional geostatistical model (AHP), with an overall accuracy of 99.54% for flood risk mapping compared to AHP�s 91.12%. The final output reveals that a large area of Bhitarkanika National park falls under high flood risk zone. The Eastern coastal regions of Govindapur, Kanhupur, Chinchri, Gobardhanpur and Barunei fall under high risk zone of tidal floods, The Northern and western regions of Ramachandrapur, Jaganathpur, Kamalpur, Subarnapur, Paramanandapur, etc., Fall under high risk region of riverine floods. The study also revealed that the areas covered with mangroves have a higher elevation and hence are repellent to any kind of flood. In the event of a flood high priority conservation measures should be taken along all high flood risk areas. This study is helpful for decision-making and carrying out programs for the conservation of natural resources and flood management in the national park and reserve forest for ecological sustainability to support sustainable development goals (e.g., SDGs-14, 15). Copyright � 2023 Mohanty, Mustak, Singh, Van Hoang, Mondal and Wang.
  • No Thumbnail Available
    Item
    Spatial and Temporal Analysis of Hydrological Modelling in the Beas Basin Using SWAT+ Model
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023-09-24T00:00:00) Singh, Suraj Kumar; Kanga, Shruti; Gulati, Bhavneet; Rai?, Mirna; Sajan, Bhartendu; ?urin, Bojan; Singh, Saurabh
    In this research, the SWAT+ model was employed to elucidate hydrological dynamics within the Beas Basin. The primary objectives encompassed the calibration of the SWAT model for accurate water balance quantification, annual simulation of salient hydrological components, and a decadal analysis of trends in fluvial discharge and sediment transport. The methodology encompasses simulating hydrological data with the SWAT+ model, followed by calibration and validation using flow data from Larji and Mahadev hydroelectric plants. The model�s efficacy in depicting streamflow and other hydrological components is corroborated by statistical measures such as the Nash�Sutcliffe efficiency and PBIAS. The water balance analysis delivers insights into the basin�s hydrological characteristics, including surface flow, water yield, and evapotranspiration. The temporal analysis exposes intricate seasonal and interannual variability in flow and sediment discharge, while spatial distribution highlights heterogeneity across the basin. These findings have practical implications for water resource management, including optimizing water allocation, hydroelectric power generation, irrigation, and environmental concerns. Limitations, such as data quality and model simplifications, are acknowledged, and future data collection and observations are recommended for improved model performance. In essence, these researches enhance understanding of the Beas Basin�s hydrology, setting a course for future investigations to integrate more data sources, refine model parameters, and consider climate and land-use changes for a richer comprehension of the basin�s hydrological dynamics. � 2023 by the authors.
  • No Thumbnail Available
    Item
    Assessment of Ground Water Quality of Lucknow City under GIS Framework Using Water Quality Index (WQI)
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023-08-28T00:00:00) Saqib, Nazmu; Rai, Praveen Kumar; Kanga, Shruti; Kumar, Deepak; ?urin, Bojan; Singh, Suraj Kumar
    Continuous groundwater quality monitoring is crucial for ensuring safe drinking and irrigation by mitigating risks from geochemical contaminants through appropriate treatment methods. Therefore, the primary objective of this study was to assess the suitability of groundwater collected from Lucknow, India, for both drinking and irrigation. Forty samples were collected from different sites within the study area to evaluate groundwater quality. Various parameters such as pH, turbidity, total dissolved solids (TDS), chlorides ((Formula presented.)), total alkalinity, total hardness, sulphate ((Formula presented.)), nitrate ((Formula presented.)), fluorides ((Formula presented.)), iron (Fe), arsenic (As), magnesium ((Formula presented.)), and calcium ((Formula presented.)) were analyzed. The weighted arithmetic water quality index (WAWQI), a vital rating system representing overall water quality, was employed to classify the water into different categories, such as very good, good, moderate, poor, and unfit for drinking. This classification is invaluable for public awareness and decision-making to make informed decisions regarding effective management, treatment, and sustainable societal development on a broader scale. A correlation matrix was generated and analyzed to observe correlations between the various parameters. Additionally, spatial distribution maps for the analyzed parameters and WQI were prepared using the inverse distance weighted (IDW) method. The study found that WQI values in the area ranged from 2.64 to 168.68, indicating good water quality in most places except for the Kukrail region, where the water quality is unfit for drinking purposes. The water quality map shows that 86% of the area falls under the very good category, 14.63% under good to moderate quality, and 0.37% is categorized as unfit for drinking. Consequently, the findings suggest that the groundwater in the studied area is safe and suitable for drinking and irrigation purposes. � 2023 by the authors.
  • No Thumbnail Available
    Item
    Unveiling Nature�s Resilience: Exploring Vegetation Dynamics during the COVID-19 Era in Jharkhand, India, with the Google Earth Engine
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023-09-08T00:00:00) Ahmad, Tauseef; Gupta, Saurabh Kumar; Singh, Suraj Kumar; Meraj, Gowhar; Kumar, Pankaj; Kanga, Shruti
    The Severe Acute Respiratory Syndrome Coronavirus Disease 2019 (COVID-19) pandemic has presented unprecedented challenges to global health and economic stability. Intriguingly, the necessary lockdown measures, while disruptive to human society, inadvertently led to environmental rejuvenation, particularly noticeable in decreased air pollution and improved vegetation health. This study investigates the lockdown�s impact on vegetation health in Jharkhand, India, employing the Google Earth Engine for cloud-based data analysis. MODIS-NDVI data were analyzed using spatio-temporal NDVI analyses and time-series models. These analyses revealed a notable increase in maximum vegetation greenery of 19% from April 2019 to 2020, with subsequent increases of 13% and 3% observed in March and May of the same year, respectively. A longer-term analysis from 2000 to 2020 displayed an overall 16.7% rise in vegetation greenness. While the maximum value remained relatively constant, it demonstrated a slight increment during the dry season. The Landsat data Mann�Kendall trend test reinforced these findings, displaying a significant shift from a negative NDVI trend (1984�2019) to a positive 17.7% trend (1984�2021) in Jharkhand�s north-west region. The precipitation (using NASA power and Merra2 data) and NDVI correlation were also studied during the pre- and lockdown periods. Maximum precipitation (350�400 mm) was observed in June, while July typically experienced around 300 mm precipitation, covering nearly 85% of Jharkhand. Interestingly, August 2020 saw up to 550 mm precipitation, primarily in Jharkhand�s southern region, compared to 400 mm in the same month in 2019. Peak changes in NDVI value during this period ranged between 0.6�0.76 and 0.76�1, observed throughout the state. Although the decrease in air pollution led to improved vegetation health, these benefits began to diminish post-lockdown. This observation underscores the need for immediate attention and intervention from scientists and researchers. Understanding lockdown-induced environmental changes and their impact on vegetation health can facilitate the development of proactive environmental management strategies, paving the way towards a sustainable and resilient future. � 2023 by the authors.
  • No Thumbnail Available
    Item
    Spatial accessibility analysis of public healthcare resources in Muktsar district of Punjab, India using geospatial technology
    (Springer Science and Business Media Deutschland GmbH, 2023-06-18T00:00:00) Singh, Amritpal; Guite, L. T. Sasang
    The public health policy depends on the management, quality, and coverage aspects. However, the assessment analysis of spatial patterns and distribution of public health services is still a challenge. This paper attempts to analyze the availability and accessibility of public health facilities in the Muktsar district of Punjab at the village level. Spatial and attribute data for public health facilities have been used within the GIS platform to produce accurate measures of accessibility. The average nearest neighbor tool has been used for spatial patterns of services in the district. Near analysis tool has been used to calculate distances from demand points (populations) to providers (facilities). Apart from these, the ratios of public health facilities to population were calculated for the identification of underserved and over-served areas. The study advocates that the spatial pattern of public health facilities is significantly clustered (p value 0.000) with a Z-score of ?�5.18. It has been found that urban areas of the Muktsar district were identified as having a higher density of health facilities, whereas villages located in the marginal parts have the lowest density of health facilities. When looking at the average distance from village centroids to health facilities, it varies considerably from village to village. Considerably less than 60 percent of the population living in 108 villages has access to public health facilities. Apart from these, 40 percent of the population living in 126 villages has the greatest increase in the distance while accessing these facilities. � 2023, The Author(s), under exclusive licence to Springer Nature B.V.
  • No Thumbnail Available
    Item
    Assessing Sustainable Ecotourism Opportunities in Western Rajasthan, India, through Advanced Geospatial Technologies
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023-07-25T00:00:00) Chandel, Rajeev Singh; Kanga, Shruti; Singh, Suraj Kumar; �urin, Bojan; Or�uli?, Olga Bjelotomi?; Dogan?i?, Dragana; Hunt, Julian David
    The present study focuses on finding potential sites for ecotourism development using GIS and remote-sensing-based weightage sum overlay techniques in Western Rajasthan, India. Ecotourism is one of the fastest growing and revenue-making sectors incorporating a sustainable future. Western Rajasthan has a broad scope to develop tourism-based activity in various ways, mainly through cultural heritage, historical and archaeological wonders, and rare wildlife. Weightage sum overlay analysis is a useful and simple tool to compare each thematic layer. These values are based on various factors and understanding taken during the study. For this purpose, different data types have been taken from the USGS website. Arc GIS 10.8 and ERDAS Imagine software 2015 have been utilized to process the data. This research incorporates seven thematic layers, i.e., elevation, proximity to streams, land use/cover, population density, road connectivity, proximity to protected areas, and heritage hotspots. Based on the physical and cultural characteristics of Western Rajasthan, the weightage of each thematic layer has been decided, which is finally overlaid using Arc GIS software. After processing all the thematic layers, we finally get an outcome in the form of a suitability map. The final suitability map represents five suitability classes that divide the total area into the following categories, very high (37.31%), high (26.85%), moderate (7.89%), low (0.83%), and very low (27.12%), which represents the potential of ecotourism in Western Rajasthan. � 2023 by the authors.
  • No Thumbnail Available
    Item
    Predicting Future Land Use Utilizing Economic and Land Surface Parameters with ANN and Markov Chain Models
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023-09-18T00:00:00) Rani, Ankush; Gupta, Saurabh Kumar; Singh, Suraj Kumar; Meraj, Gowhar; Kumar, Pankaj; Kanga, Shruti; ?urin, Bojan; Dogan?i?, Dragana
    The main aim of this study is to comprehensively analyze the dynamics of land use and land cover (LULC) changes in the Bathinda region of Punjab, India, encompassing historical, current, and future trends. To forecast future LULC, the Cellular Automaton�Markov Chain (CA) based on artificial neural network (ANN) concepts was used using cartographic variables such as environmental, economic, and cultural. For segmenting LULC, the study used a combination of ML models, such as support vector machine (SVM) and Maximum Likelihood Classifier (MLC). The study is empirical in nature, and it employs quantitative analyses to shed light on LULC variations through time. The result indicates that the barren land is expected to shrink from 55.2 km2 in 1990 to 5.6 km2 in 2050, signifying better land management or increasing human activity. Vegetative expanses, on the other hand, are expected to rise from 81.3 km2 in 1990 to 205.6 km2 in 2050, reflecting a balance between urbanization and ecological conservation. Agricultural fields are expected to increase from 2597.4 km2 in 1990 to 2859.6 km2 in 2020 before stabilizing at 2898.4 km2 in 2050. Water landscapes are expected to shrink from 13.4 km2 in 1990 to 5.6 km2 in 2050, providing possible issues for water resources. Wetland regions are expected to decrease, thus complicating irrigation and groundwater reservoir sustainability. These findings are confirmed by strong statistical indices, with this study�s high kappa coefficients of Kno (0.97), Kstandard (0.95), and Klocation (0.97) indicating a reasonable level of accuracy in CA prediction. From the result of the F1 score, a significant issue was found in MLC for segmenting vegetation, and the issue was resolved in SVM classification. The findings of this study can be used to inform land use policy and plans for sustainable development in the region and beyond. � 2023 by the authors.
  • No Thumbnail Available
    Item
    Uncovering the hydro-meteorological drivers responsible for forest fires utilizing geospatial techniques
    (Springer, 2023-05-29T00:00:00) Gupta, Saurabh Kumar; Kanga, Shruti; Meraj, Gowhar; Kumar, Pankaj; Singh, Suraj Kumar
    Forest fires have become a growing concern worldwide, with climate change exacerbating their frequency and intensity. In the Simlipal region of India, forest fires are relatively rare; however, in 2021, significant damage occurred in the buffer area�s forests. Understanding the driving factors behind these events is essential for developing effective management strategies. This study investigates the impact of hydro-meteorological conditions on forest fire causes in the Simlipal region by analyzing Terra climatic data and geo-statistics for the period of 1984 to 2021. Long-term trends were determined using non-parametric tests on the Google Earth Engine (GEE) cloud computing platform. Our findings reveal that the maximum burned area location has a decreasing trend in Land Surface Temperature (LST), with a small portion (<10%) showing an increasing trend (0.02 �C/year) near burned locations. Wind speed is decreasing at a rate of ?0.006 m/s/year. The sudden forest fires are caused by the combined effect of increasing LST and decreasing wind speed in some areas (<10% of the region). However, the major factor contributing to forest fires in the entire area is the rising trend of annual potential water deficit and actual evapotranspiration, as well as an increasing trend of minimum temperature. The soil moisture deficit during the summer season, especially between 2012 and 2021, contributed to forest fires in the burned area. The soil moisture deficit during the summer season, particularly from 2012 to 2021, played a significant role in the occurrence of forest fires in the affected area. The study emphasized the need for increased attention to this region in order to preserve biodiversity, which was assessed through an analysis of burned severity mapping in GEE (Google Earth Engine). These findings have important implications for future forest management strategies in the Simlipal region. Climate variability is likely to exacerbate the frequency and intensity of forest fires in the region, necessitating effective management strategies to mitigate their impact. Such strategies could involve improving fire prevention and control measures, such as creating fire breaks and increasing the availability of fire-fighting equipment, as well as enhancing forest monitoring systems to detect potential fires early. Additionally, efforts to address climate change, proper management of land use practices, and reduce greenhouse gas emissions could help to mitigate the future impacts of forest fires in the Simlipal region and elsewhere. � 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
  • No Thumbnail Available
    Item
    Contextualizing the lake ecosystem syndromes and research development activities in Chilika Lake (Odisha coast, India): a bibliometric overview (1970�2021)
    (Springer Science and Business Media B.V., 2023-05-25T00:00:00) Acharyya, Tamoghna; Sudarsan, Desul; Mishra, Manoranjan; Santos, Celso Augusto Guimar�es; Chand, Pritam; da Silva, Richarde Marques; Pradhan, Subhasis
    Chilika Lagoon is traditionally known as a productive study site for various areas of knowledge. It is also well-known for its successful ecological restoration in 2000, following ecological degradation due to siltation and proliferation of weeds in the 1980s and 1990s. Since then, Chilika Lagoon has been facing various coastal syndromes that are likely to worsen due to climate change and increasing anthropogenic pressure on its waters and catchment area. This study analyzed bibliometric data from the Scopus database over the past five decades (1970?2021) to understand the ever-evolving publication pattern and research domains in Chilika Lagoon. A total of 457 records were selected for the analyzed period, with contributions from 944 authors, primarily in peer-reviewed journal articles (86%). Although the number of publications and citations is increasing, as expected, there is minimal international collaboration. An interesting pattern was found in�publication and research themes, correlating with the evolving history of lagoon management and governance. The establishment of the Wetland Research and Training Centre led to a surge in research publications from 2002 onwards. However, a mismatch appears to exist�between the research scope and publication records, as evidenced by the mere 11 seagrass-related records in Scopus, even though Chilika Lagoon hosts the second-largest seagrass patch in India. Simultaneously, there is a lack of research addressing the real-world challenges faced by the local people who depend on Chilika Lagoon for their livelihoods. Graphical abstract: [Figure not available: see fulltext.]. � 2023, The Author(s), under exclusive licence to Springer Nature B.V.