GIS-Based Flood Susceptibility Mapping of Ernakulam District, Kerala, India Using the Frequency Ratio Model | Chapter 5 | Current Research on Geography, Earth Science and Environment Vol. 6

 

Flooding remains one of the most recurrent and damaging natural hazards affecting the low-lying coastal districts of Kerala, with Ernakulam District experiencing repeated flood events during the southwest monsoon. Flood susceptibility is an important mission for early warning systems and emergency services for the prevention and mitigation of future floods. This study assesses flood susceptibility in Ernakulam District, Kerala, India, using the Frequency Ratio (FR) model integrated with Geographic Information System (GIS) techniques. A flood inventory was developed using historical flood records and satellite-derived data, and six flood-conditioning factors—geology, land use/land cover (LU/LC), soil, drainage density, rainfall, and slope—were selected based on their hydrological relevance. Each factor was classified and evaluated using the Frequency Ratio approach to quantify its contribution to flood occurrence. Satellite data, including Landsat imagery and ASTER DEM, were used to generate thematic maps such as land use/land cover, relief, slope, drainage density, rainfall, soil, and geology.

 

The results reveal that built-up areas exhibit the highest flood susceptibility (FR = 4.65), reflecting the combined influence of rapid urban expansion, impervious surfaces, and inadequate drainage systems. In contrast, forested areas demonstrate minimal flood susceptibility (FR = 0.17), highlighting their role in runoff regulation and hydrological stability. Among the conditioning factors, geology (FR = 7.73) emerged as the most influential parameter, followed by land use/land cover (FR = 6.90) and soil characteristics (FR = 6.58), while slope (FR = 1.60) showed comparatively lower control over flood occurrence. The highest flood susceptibility was associated with the 7–9 rainfall class (FR = 2.93), indicating that areas experiencing intense rainfall are more prone to flooding despite their smaller spatial coverage. The final flood susceptibility map categorises the district into low, moderate, high, and very high susceptibility zones.

 

The findings confirm that the Frequency Ratio model is an effective and reliable tool for flood susceptibility assessment in data-scarce regions. The generated susceptibility map provides valuable insights for disaster risk reduction, land-use planning, and sustainable flood management, thereby supporting climate-resilient development strategies in Ernakulam District. In future, studies should integrate high-resolution temporal data and climate change projections to enhance the accuracy and reliability of flood susceptibility assessments.

 

 

Author(s) Details

V. V. Neethu
Department of Geography, Indus International School, Bangalore, 562125, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/crgese/v6/7160

Multitemporal Monitoring of Surface Water Dynamics in Lake Tota (Colombia) Using Landsat Imagery and NDWI: A Replicable Methodological Framework | Chapter 4 | Current Research on Geography, Earth Science and Environment Vol. 6

 

Remote sensing has become an essential tool for understanding environmental dynamics, particularly the long-term monitoring of surface water bodies. Among spectral indices, the Normalised Difference Water Index (NDWI) has shown strong potential for detecting and quantifying changes in water surfaces using multispectral satellite imagery. This chapter presents a replicable methodological framework for the multitemporal analysis of surface water dynamics based on Landsat imagery and the NDWI index, integrating conceptual explanation with a step-by-step workflow accessible to researchers, professionals, and students.

 

The proposed methodology is applied to Lake Tota, the largest natural freshwater lake in Colombia, using Landsat images from 1985 to 2025. The results indicate a net reduction of 125.24 hectares in surface water area, equivalent to a decrease of 2.29% relative to the baseline year, together with marked interannual variability and a declining trend in recent years. Beyond the case study, the framework offers a transferable approach for monitoring surface water changes in different geographic contexts, contributing to more informed decision-making in environmental management and research.

 

 

Author(s) Details

Alexander Saavedra Pulido
Facultad de Ingeniería Ambiental, Universidad Santo Tomás, Colombia.

 

Carlos Caro Camargo
Facultad de Ingeniería Civil, Universidad Santo Tomás, Colombia.

 

Please see the book here :- https://doi.org/10.9734/bpi/crgese/v6/7147

 

Estimation and Prediction of Biomass Carbon Stocks in India Using Remote Sensing: Implications for Emissions Reduction and Bioenergy Potential |Chapter 4 | Current Research on Geography, Earth Science and Environment Vol. 3

 

As the global community transitions towards more sustainable energy sources, bioenergy has emerged as a promising solution, particularly for countries with substantial agricultural resources like India. With its vast reserves of organic waste and residues, India holds significant potential to transform biomass into clean, renewable energy. The objective of this study is to estimate the average availability of biomass in India in the year 2010 and predict it in the year 2025 with the help of high-resolution imagery through Google Earth Engine and GIS, also estimating the release of CO2 into the atmosphere if the same biomass is not utilised. The analysis utilises NASA’s harmonised global maps of aboveground and belowground biomass carbon density for the year 2010 at a 300-m spatial resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) product provides information about annual Gross and Net Primary Productivity (GPP and NPP) at 500m pixel resolution. The range of average above-ground biomass (agb) in 2010 varies from 0.5338 - 93.644, below-ground biomass (bgb) 1.015- 22.474, and Total biomass (TBM) 1.5488- 116.118 kg*C/m2 as computed from MODIS. Corresponding Total Biomass quantity in year 2010 is 4.39179 billion Ton and CO2 release in atmosphere is 11.539218400000001 billion Ton. However, the Gross Primary Production is 4.79646005 billion tons. However, prediction was made with NASA imagery in conjunction with Vegetation indices, Land Cover and FPAR/LAI, the results obtained are in the range of average above ground bio-mass (agb) in 2010 varies from 0.000 – 79, below ground bio-mass (bgb) 0.000- 22, and Total bio-mass (TBM) 0- 101 mg/Ha. Corresponding Total Biomass quantity in the year 2010 is 4.112982692983341 billion tons and CO2 release in the atmosphere is 13.25737496044534 billion tons. However, predicted figures in the year 2025: the above-ground biomass (agb) 85.73578643798828 mg/Ha, below-ground biomass (bgb) 22.05862045288086 mg/Ha, and Total biomass (TBM) 4.83646174936528 billion tons. Correlation and R-squared values are 0.9882423543764696 and 0.9766229509835477. The findings show that remote sensing, being an advanced technology, is quite useful for quick and reliable estimations of vegetation biomass and carbon over large areas. The study highlights that regions such as the Himalayas, North-East India, Eastern states, and the Western Ghats possess particularly high biomass potential. Future biomass research should focus on leveraging advanced technologies, addressing methodological gaps, improving data integration, and ensuring that outcomes are actionable for environmental and policy challenges.

 

Author(s) Details

Praveer Agrawal
GAIL (India) Ltd., India.

 

Rajani Kant Awasthi
Sharda University, Greater Noida, Uttar Pradesh, India.

 

 

Please see the book here :- https://doi.org/10.9734/bpi/crgese/v3/6228

Transforming Geography with Geospatial Technologies | Chapter 9 | Innovations in Science and Technology: Shaping a Sustainable Future (Vol. 2)

 

This paper explores the transformative impact of geospatial technologies in the field of geography. The specific objectives of the study include describing the role of main geospatial technologies, such as Geographic Information Systems (GIS), the Global Positioning System (GPS), and Remote Sensing in contemporary geographical research. The study highlights the diverse applications of these technologies across various fields, examines future trends and emerging technologies, and reveals their potential impacts on geographical research and practices. Additionally, this paper assesses the challenges and limitations in the adoption and implementation of these technologies. Methodologically, the study is based on an extensive review of existing literature, including research papers from national and international journals and various books. The paper is structured into four sections, Section I covers GIS, Section II discusses GPS, Section III elaborates on Remote Sensing, and Section IV provides the conclusion. The discussion of the paper reveals that Geospatial technologies have revolutionized geographical research. GIS has transformed spatial data visualization, analysis, and interpretation, becoming essential in diverse fields.  Likewise, GPS technology provides unparalleled accuracy in positioning and data collection, enhancing our knowledge through applications in numerous fields. Besides, Remote sensing's ability to gather extensive data about the earth's surface and atmosphere is vital for environmental monitoring, disaster management, urban planning and infrastructure development, agriculture, etc. The integration of these technologies has led to significant innovations in geography, promising further advancements as addressed challenges related to data interpretation, signal interference, privacy, and ethical considerations. Holding and overcoming these challenges is crucial for realizing the full potential of GIS, GPS, and Remote Sensing in progressing geographical research.

 

Author(s) Details

Narinder Kumar
Department of Geography, D.A.V. College (Lahore), Ambala City, Haryana-134003, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-48006-49-3/CH9

Innovations in Sciences and Their Impact on Community Development: A Review | Chapter 4|Innovations in Science and Technology: Shaping a Sustainable Future (Vol. 2)

 

Recent decades have seen a growing focus on the intersection of science and community development as societies grapple with complex challenges and strive for sustainable growth. This review explores recent scientific advancements and their implications for community development, drawing upon a variety of scholarly sources. Biotechnology emerges as a key driver, offering solutions to enhance agricultural productivity, fortify food security, and mitigate environmental degradation. Renewable energy technologies provide sustainable alternatives for rural communities, fostering economic resilience and environmental stewardship. Artificial intelligence revolutionizes healthcare delivery, while smart city innovations reshape urban infrastructure for enhanced livability and sustainability. Innovative agricultural practices empower rural livelihoods, while advances in environmental science address pollution and climate change. Nanotechnology holds promise for sustainable development across sectors, while education technology and mobile health innovations democratize access to education and healthcare. Water management, sustainable transportation, ICT, waste management, green building technologies, and microfinance initiatives further contribute to environmental stewardship and socio-economic progress. Remote sensing and GIS can help identify the potential beneficiaries and locations for microfinance and biotechnology interventions, based on indicators such as poverty, vulnerability, land use, vegetation, or climate conditions. By embracing interdisciplinary collaboration and prioritizing community engagement, stakeholders can harness the transformative potential of these scientific innovations to build resilient, inclusive, and equitable communities for future generations.

 

Author(s) Details

Vikram Kumar
Department of Chemistry at I.B. (PG) College, Panipat, Haryana- 132103, India.

 

Deepak Wadhwa
Department of Chemistry, Chaudhary Ranbir Singh University, Jind, Haryana-126102, India and Department of Chemistry, CBLU, Bhiwani, Haryana -127021, India.

 

Suresh Panchal
Department of Physics at DCRUST, Murthal, Sonepat, Haryana, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-48006-49-3/CH4

Association between Stroke Prevalence and PM2.5: Classical and Spatial Regression Analyses Using Satellite Remote Sensing Imagery and 500 Cities Project Data | Chapter 7 | Research Advances in Environment, Geography and Earth Science Vol. 10

This chapter assesses the association between adult stroke mortality prevalence rate and long-term exposure to PM_2.5 (ambient air pollution of particulate matter with an aerodynamic diameter of _2.5 μm or less) adjusting for unhealthy lifestyles and other health conditions. Health data, based on 2017 or 2016 model-based small area estimates of chronic disease, was obtained from the “500 Cities Project” 2019 release. PM_2.5 data for the year 2016 was acquired from the “The Global Annual PM_2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), V4.03 (1998-2019)” datasets. Average PM_2.5 was calculated for each city using a GIS zonal statistics function. First, classic ordinary least (OLS) square regression modeling (univariate linear regression, and a multivariate linear regression model fitted using a generalized linear model via penalized maximum likelihood). However, Moran’s I test found significant positive spatial autocorrelation with stroke data, PM_2.5, and the residues of the OLS multilinear regression model, which makes the OLS modeling unreliable. Therefore, two spatial regression models (spatial lag and spatial error) were further run to account for the spatial dependence. Both models have successfully explained away spatial dependency. The spatial error model has much better goodness-of-fit than the spatial lag model as indicated by the higher log-likelihood, lower Akaike info criterion (AIC), and lower Schwartz criterion. The spatial error model found that long-term exposure to ambient PM_2.5 may increase the risk of stroke and that increasing physical activity, reducing smoking and body weight, enough sleep, and controlling diseases such as blood pressure, coronary heart disease, diabetes, and cholesterol, may mitigate the effect.

 

Author (s) Details

Z. Hu
Department of Earth & Environmental Sciences, University of West Florida, Pensacola, FL, 32514, USA.

 

Please see the book here:- https://doi.org/10.9734/bpi/raeges/v10/1060

Satellite-based Monitoring of Vegetation Cover of Lalbagh Botanical Garden, Bengaluru, Karnataka, India | Chapter 7 | Geography, Earth Science and Environment: Research Highlights Vol. 9

Lalbagh Botanical Garden, is a Bengaluru’s oldest garden, spread across 240 acre, is a home to wide array of plants from around the world, is a treasure house of biological diversity. Lalbagh has 2,950 spp of plants and trees. It was started in 1760 was given the status of a Government Botanical Garden in 1856 and since then it has been an internationally renowned centre for scientific study of plants and botanical artwork and also conservation of plants. Lalbagh Botanical garden with a high diversity of species, provide a storehouse of genetic resources from within the region and they also provide food and pharmacological resources for a range of species such as birds, mammals, reptiles and insects. The aim of the study is to give an overall picture of vegetation distribution and canopy coverage in different parts of Lal Bagh through satellite imagery.

In the present study Quick Bird imagery of 2005 is used for comparative assessment of NDVI and TNDVI indices with superwised classified imagery of LalBagh Botanical Garden, one of the largest and oldest botanical Garden in the Bengaluru. The NDVI and TNDVI transformed imagery of Lalbagh showed variation in their values. The different land use classes of supervised classified imagery showed more resemblances to the NDVI than TNDVI. It was observed that 33% of lalbagh’s 240 acres is covered with thick canopy comprising mainly large mature trees. Small statured ornamental specimens and many small trees growings in thickets like groupings constituting thin canopy, covering 20% area. Water Constitute about 13%. Rocky area is present on the North West comprises about 12% and Grass area about 16.6%. The study concluded that in order to achieve environmental sustainability, the city should increase both its percent green open space and m2 of urban green open space per capita. More and more efforts should be made in this regard to increase the green spaces in the city by maintaining the old green spaces like botanical gardens, parks and avenue trees. There is a need to have a clear account on existing green spaces. This study gives various land uses of the entire lalbagh in a broader picture and more supplementary study is needed to give tree wise distribution in the entire lalbagh.

 

Author (s) Details

Malini A. Shetty
Department of Botany, Surana College Autonomous, Bengaluru-04, India.

 

Parinitha Mahishi
Department of Botany, NMKRV College for Women, Bengaluru-11, India.

 

Priyadarshini Pillai
Department of Botany, Jyothinivas College, Bengaluru-34, India.

 

R.K. Somashekar
Department of Environmental Science, Bangalore University, Bangalore-56, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/geserh/v9/4538

Evaluation of Spatial Expansion of Rift Valley Lakes Using Satellite Data: A Brief Study | Chapter 5 | Geography, Earth Science and Environment: Research Highlights Vol. 9

Assessing and studying lake expansion can reveal important information about climate change and regional responses, normally a lake recedes during the dry season and floods during the wet season. In the recent years Lake Nakuru has had variations between dry and wet seasons water levels, suspected that it is caused by increasing watershed land conversion to intensive crop production and urbanization, both reduce the capacity of soils to absorb water; recharge ground water and thus increase seasonal flooding. The present work assessed the expansion and fluctuation of Lake Nakuru in Kenya by using satellite data and information. This study was carried out in Lake Nakuru area in Nakuru County using two methods. In the first method, data was obtained from the USGS website whereby Landsat 7 and 8 images were used, though images collected after May 31, 2003, had data gaps when the SLC failed, the images had about 78% of their pixels missing. In the second method shapefiles were used, to find out how the lake surface area had changed, it was done by using different methods.  Surface water magnitude was measured from optical sensors, such as Landsat. ENVI software was used to process and analyze data from the satellite images. The data was then used to create shapefile to get the area of the lake only. The shapefiles were classified using both Supervised and Unsupervised classification, and the area of the lake was obtained in hectares. The obtained area in hectares was recorded in a table and graphs were plotted to show the trend of the lake in the years 1972-2019. Furthermore, correlation was done by assuming the area of the shapefile before any classification is more accurate, therefore it was compared with the other results obtained by using different methods. Maximum like-lihood gave the best correlation values. For R2 it gave 0.8627 and R was 0.9312. The perfect correlation coefficient is 1, the graphs for correlation gave 0.91 for NDVI, 0.83 for K-MEANS, 0.93 for Maximum Likelihood and 0.92 for Spectral Angle Mapper.  In conclusion, the change was seen using line graph and that the Lake Nakuru area is expanding from the years 2010 to 2018.

 

Author (s) Details

 

Rose Yang Mulama
Department of Physics, University of Nairobi, Nairobi, Kenya.

 

Jephter Ongige Ondieki
School of Aerospace Engineering, Sapienza University of Rome, Roma, Italy.

 

Please see the book here:- https://doi.org/10.9734/bpi/geserh/v9/4942

Tectonic Scenarios and Structural Deformation Patterns at the Northern end of the Wadi Araba Strike-slip Fault System, Jordan Plateau | Chapter 6 | Geography, Earth Science and Environment: Research Highlights Vol. 2

This chapter presents new insights into the deformational characteristics of the Wadi Shueib Structure (WSS) and the Amman-Halabat Structure (AHS) and their interaction with the regional tectonic framework of the Wadi Arab Strike-slip Fault (WAF). Utilizing Landsat-8 OLI imagery, lineament mapping was conducted through automated extraction, supported by digital image enhancement and principal component analysis (PCA) to refine lineament detection. Our findings reveal a higher density of lineaments along the main fault extensions of the WSS and AHS, with a lower density in areas covered by recent sediment deposits. Two dominant lineament trends (NE-SW and NW-SE) and a secondary trend (NNE-SSW) parallel the orientations of the WSS and AHS. In this study, two primary hypotheses have emerged to explain the forces driving the formation and evolution of deformation patterns within the AHF and WSF, as well as their connection to the WAF. The first hypothesis suggests that the AHF and WSF represent younger deformation phases that developed as horsetail structures following the formation of the WAF. The second hypothesis views them as pre-existing fault systems reactivated as restraining bends in response to the WAF’s evolution.

 

Author (s) Details

 

Mu'ayyad Al Hseinat
School of Science, Department of Geology, The University of Jordan, Amman, 11942 Amman, Jordan and Department of Geophysics, Arab Center for Laboratory and Soil (ACES), 23762 Jeddah, Kingdom of Saudi Arabia.

 

Malek AlZidaneen
School of Science, Department of Geology, The University of Jordan, Amman, 11942 Amman, Jordan.

 

Please see the book here:- https://doi.org/10.9734/bpi/geserh/v2/3260

Quantifying ETo Maps Across Egypt: A Remote Sensing Approach to Address Water Needs for Agricultural Irrigation| Chapter 7 | Engineering Research: Perspectives on Recent Advances Vol. 4

Egypt faces acute water scarcity, posing a critical challenge to its agricultural sector, which consumes approximately 85% of the nation’s water resources. This challenge is compounded by the government's horizontal agricultural expansion strategy to meet the demands of rapid population growth. To support sustainable water resource management, this study integrates GIS with the FAO Penman-Monteith equation to calculate reference evapotranspiration (ETo) across Egypt using high-resolution climate data (1970–2000) from over 10,000 spatial points. By leveraging remote sensing and advanced spatial interpolation techniques, the study generates monthly ETo maps, providing precise insights into the spatial and temporal variability of ETo. The results reveal significant seasonal trends: the highest mean ETo value (9.5 mm/day) occurs in June, while the lowest (3.28 mm/day) is observed in December. A clear north-to-south gradient in ETo values is identified, influenced by temperature and solar radiation, with the Red Sea Coast exhibiting lower ETo due to higher humidity levels. These findings hold practical implications for sustainable agricultural planning and water conservation. Policymakers can use high-resolution ETo maps to optimize irrigation schedules, reduce water wastage, and identify low-evapotranspiration zones suitable for agricultural expansion. This scalable methodology, incorporating remote sensing for enhanced data collection, offers a robust framework for addressing water management challenges in Egypt and other arid regions globally.

 

Author (s) Details

Hesham Ezz
Civil Engineering Department, National Research Centre, Dokki, Giza, Egypt and Al Madinah High Institute for Engineering and Technology, Egypt.

 

Mohamed Abdelwares
Irrigation and Hydraulics Department, Faculty of Engineering, Cairo University, Egypt.

 

Please see the book here:- https://doi.org/10.9734/bpi/erpra/v4/4303

Foundations and Applications of Remote Sensing and GIS | Book Publisher International

Remote sensing is the art and science of obtaining information about an object which is not in contact with it, Geospatial technologies such as high-resolution satellite data, GPS and GIS can be effectively used in the agricultural sector. Therefore this book provides the basic knowledge of remote sensing, GPS & GIS to students, researchers and academicians in the fields of agriculture.

 

Author (s) Details

 

Dr. Samadhan Surwase
Vasantdada Sugar Institute, Manjari Bk., Pune (MH), India.

 

Dr. Preeti Deshmukh
Vasantdada Sugar Institute, Manjari Bk, Pune (MH), India.

 

Dr. Prakash Kadu
College of Agril. Nagpur, Dr. PDKV Akola (MH), India.

 

Dr. S. K. Singh
ICAR- NBSS&LUP, Nagpur (MH), India.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-49238-73-2

Identification of Iron Ore Mine and Structural Lineaments Extraction by Using Remote Sensing Technique, Iran: A Case Study of the Sangan Khaf Iron Ore Mine | Chapter 9 | Emerging Issues in Environment, Geography and Earth Science Vol. 6

 

In recent decades, the world's space technologies in the field of remote sensing satellites have grown and expanded significantly. Remote sensing has provided many applications in the exploration of mines and various mineral deposits. In this research, an attempt has been made to investigate the method of obtaining information and characteristics of iron minerals. The study area of the research is the Sangan mine, the largest iron ore mine in West Asia, and the images used in this research are related to the ASTER sensor. The spectral behavior of the soil is processed, and by using band ratio algorithms, the spectral behavior of each iron mineral is extracted. The areas that contain iron ore can be visually observed and analyzed. Among the spectral indices used in this research are Fe+3 - Fe+2 - Laterite - Gossan – Ferrous silicates – Ferric oxides, and the algorithms of these indices are implemented in the Google Earth Engine web system. After estimating the iron minerals, according to the output obtained from the spectral indices of iron, the results showed that in the last 19 years, the amount of iron ore in the Sangan region has been decreasing. The highest amount of iron minerals is related to the areas of the Sangan mineral complex and the central areas of the Sangan mountain. The map of the structutal lineamentss in the study area was carried out using the accuracy assessment for the correctness of iron ore calculations by the structural lineaments map and the output of the Ferrous silicates index, and the RMSE shows about 0.14%, which indicates that the accuracy of the iron ore is acceptable.

 

Author(s) Details:

 

Sajad Mehri
Islamic Azad University South Tehran Branch, Iran.

 

Sara Vahidi
Islamic Azad University South Tehran Branch, Iran.

 

Vahid Hatamzadeh

Islamic Azad University South Tehran Branch, Iran.

 

Paniz Nouri
Islamic Azad University South Tehran Branch, Iran.

 

Afshin Afshinfar
Islamic Azad University South Tehran Branch, Iran.

 

Ahmad Pourheidari
Islamic Azad University South Tehran Branch, Iran.

 

Amir Shahrokh Amini

Islamic Azad University South Tehran Branch, Iran.

 

 

Please see the book here: https://doi.org/10.9734/bpi/eieges/v6/8421A

Caspian Sea Level Change and its Environmental Impacts on the Geopolitics of the Region | Chapter 2 | Emerging Issues in Environment, Geography and Earth Science Vol. 7

Caspian Sea level has experienced considerable fluctuations over the past years. Therefore, due to the unfavorable conditions of changes in Caspian Sea and also the impacts created on its surrounding ecosystems, it has increased the importance of this issue during recent decades. Accordingly, the present study examined and analyzed the trend of Caspian Sea water level changes in a long-term period (1990-2023). Also, in the current study, the effects caused by the fluctuations of Caspian Sea level were examined from various environmental, social and economic aspects. For this purpose, a set of images of Landsat 5 for 1990 and Landsat 8 for 2023 was analyzed in the Google Earth Engine (GEE) web system. The results showed that the variations of Caspian Sea level (North, Middle and South) during the period 1990 to 2023 indicate a decline of 2.34 m in the sea level. Also, it was found that the water level of Caspian Sea in 1990 was -26.18 m, and these changes reached -28.52 m in 2023. Thus, the water of Caspian Sea has experienced fluctuations during recent decades, and these changes have led to threats in infrastructure, economic and social uses, disturbance in the activity of ports and seafaring, fishing, and drying up of water reserves related to Caspian Sea (wetlands - bays), the increase of the coastal area, human occupation of the sea and adverse effects on the coastal aquifers. In this regard, the management of these issues requires a cross-sectoral and comprehensive approach within the framework of integrated coastal management.

Author(s) Details:

Afshin Motaghi,
Department of Political Geography, School of Geography Sciences, Kharazmi University, Tehran, Iran.

Mostafa Mohammadjani,
Kharazmi University, Tehran, Iran.

Please see the link here: https://stm.bookpi.org/EIEGES-V7/article/view/13333

Identification of Iron Ore Mine and Structural Lineaments Extraction by Using Remote Sensing Technique, Iran: A Case Study of the Sangan Khaf Iron Ore Mine | Chapter 9 | Emerging Issues in Environment, Geography and Earth Science Vol. 6

In recent decades, the world's space technologies in the field of remote sensing satellites have grown and expanded significantly. Remote sensing has provided many applications in the exploration of mines and various mineral deposits. In this research, an attempt has been made to investigate the method of obtaining information and characteristics of iron minerals. The study area of the research is the Sangan mine, the largest iron ore mine in West Asia, and the images used in this research are related to the ASTER sensor. The spectral behavior of the soil is processed, and by using band ratio algorithms, the spectral behavior of each iron mineral is extracted. The areas that contain iron ore can be visually observed and analyzed. Among the spectral indices used in this research are Fe+3 - Fe+2 - Laterite - Gossan – Ferrous silicates – Ferric oxides, and the algorithms of these indices are implemented in the Google Earth Engine web system. After estimating the iron minerals, according to the output obtained from the spectral indices of iron, the results showed that in the last 19 years, the amount of iron ore in the Sangan region has been decreasing. The highest amount of iron minerals is related to the areas of the Sangan mineral complex and the central areas of the Sangan mountain. The map of the structutal lineamentss in the study area was carried out using the accuracy assessment for the correctness of iron ore calculations by the structural lineaments map and the output of the Ferrous silicates index, and the RMSE shows about 0.14%, which indicates that the accuracy of the iron ore is acceptable.

Author(s) Details:

Sajad Mehri,
Islamic Azad University South Tehran Branch, Iran.

Sara Vahidi,
Islamic Azad University South Tehran Branch, Iran.

Vahid Hatamzadeh,
Islamic Azad University South Tehran Branch, Iran.

Paniz Nouri,
Islamic Azad University South Tehran Branch, Iran.

Afshin Afshinfar,
Islamic Azad University South Tehran Branch, Iran.

Ahmad Pourheidari,
Islamic Azad University South Tehran Branch, Iran.

Amir Shahrokh Amini,
Islamic Azad University South Tehran Branch, Iran.

Please see the link here: https://stm.bookpi.org/EIEGES-V6/article/view/13112

Pansharpening of Multispectral Data Based on Lagrange Optimization | Chapter 2 | Advances and Challenges in Science and Technology Vol. 2

 Satellite dossier provides images of heterogenous judgments of the scenes on the earth’s surface. It is of excellent practical value to meld images of the alike scene with various resolutions. Pansharpening is a pel-level image fusion method resulting in a extreme resolution multispectral image in conditions of both relating to space (pan) and spectral (XS) resolutions. The challenge display or take public maintaining the ghostly characteristics of each channel of the XS image when pan representation is used to estimate the high spatial determination XS image. The basic objective of the study is to preserve or uphold the spectral thickness of the multispectral data during the mixture process. A data-principal approach consisting of a linear reversion model between the panchromatic and multispectral channels is projected. In order to maximise the spectral consistency, Lagrange growth is carried out. The authentication of the proposed concept is originally established accompanying the smaller 8×8 pixel representations. Considering practical applications, the study is scaled until 512×512 pixel figures. Evaluation of the proposed method is completed activity by comparing it accompanying the existing methods of IHS, Brovey, PCA, SFIM, HPF and Multi under various performance tests such as chi-square (X2) test, R2  test, root mean square mistake (RMSE), signal to noise percentage (SNR), spectral discrepancy (SD) and ERGAS. It is proved that that the proposed form generally outperforms the existing plans based on the acting criteria considered.

Author(s) Details:

Mutum Bidyarani Devi,
Department of Electronics and Computer Sciences, Manipur International University, Manipur, India.

Rajagopalan Devanathan,
Hindustan Institute of Technology and Science, School of Electrical Sciences, Chennai, India.

Please see the link here: https://stm.bookpi.org/ACST-V2/article/view/11925

Assessment Land Changes in the Area of Kahrizak Waste Disposal Center by Using Spatial Information System and Remote Sensing Methods | Chapter 7 | Novel Perspectives of Geography, Environment and Earth Sciences Vol. 9

 For as well 50 years, Kahrizak waste center has happened a neighbor of Tehran metropolis. With the happening of the Tehran city and the increase in waste production, it's hurtful effects on the environment. Land use wholes that are always changeful under the influence of everyday events, human conduct, social and financial issues, especially about big capitals like Tehran is obvious. In these changes, various lands are convinced into built-up lands, either residential, marketing, industrial, or drive network, and in some cases, they are abandoned as barren lands. In this research, by utilizing landsat8 satellite concepts and remote sensing method, land use changes of Kahrizak waste center have been examined in thematic maps that is more available for consumers, Five vegetation indications NDVI, EVI, SAVI, LAI and VCI and six supervised categorization methods maximum prospect, parallel networks, minimum distance from the mean, neural network, Mahalanobis distance and support heading machines with four circular, linear, polynomial kernels .and branching with the alike training and test dossier on the image of 2022 were examined by using two limits of overall accuracy and Kappa cooperative. For this research 4classes was selected soil, water, construction (urban area) and land lands, the results showed that the maximum possibility classification pattern is the best design with overall veracity of 90.99% and Kappa coefficient of 0.85 and the extreme similarity of the create user map classes to the original subsidiary image. Then, a consumer map was produce from all the images from 2011 to 2022 utilizing the maximum likelihood categorization method. After manipulative the area of the classes, the results demonstrated that the area of the building class raised by 71% and the agricultural land class depreciated by 80%.

Author(s) Details:

Vahid Hatamzadeh,
Islamic Azad University Branches, Iran.

Sara Vahidi,
Islamic Azad University Branches, Iran.

Paniz Nouri,
Islamic Azad University Branches, Iran.

Niloofar Karbalaei,
Tehran University, Iran.

Please see the link here: https://stm.bookpi.org/NPGEES-V9/article/view/11628

Change Detection Using Fast Subpixel Mapping Algorithms for LISS IV Madurai Imagery | Chapter 6 | Research Highlights in Science and Technology Vol. 5

 Due to fast changes on the Earth’s surface, it is vital to perform land covering worn over the head amendment discovery (CD) at a fine abstraction and fine temporal judgment. However, remote sensing pictures accompanying each fine abstraction and momentary resolutions square measure ordinarily not achievable or, wherever obtainable, commit also be extravagant to get. This paper tries to realize fine preoccupation and temporal judgment land cowl CD with a new technology supported subpixel plan (SPM). The fine spacial resolution land covering worn over the head maps (FRMs) area unit 1st anticipated through SPM of the coarse special, nevertheless, fine temporal determination pictures, and then, subpixel resolution CD is acted by comparison of sophistication labels inside the SPM results. For the primary opportunity, 5 quick SPM algorithms, as well as uninterrupted interpolation, bicubic interpolation, subpixel/pel spacial attraction model, Kriging, and branching basis operate introduction ways, region unit projected for subpixel judgment CD. The auxiliary data from the known FRM on individual date is incorporated in SPM of rude pictures on alternative dates to extend the CD accuracy. Supported the 5 keen SPM algorithms and, therefore, the convenience of the FRM, subpixels for each category region unit expected approximate of the calculable soft type values at the aim fine abstraction resolution and appropriating data from the FRM.

Author(s) Details:

S. Rajesh,
Department of Information Technology, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India.

Please see the link here: https://stm.bookpi.org/RHST-V5/article/view/11145

A Novel Explanation of the Meissner Effect and New Applications | Chapter 2 | Fundamental Research and Application of Physical Science Vol. 7

 In the current quantity description of the Meissner effect, a superconducting material behaves accurately like a perfect diamagnetic material in the presence of an extrinsic magnetic field. However, when we place a superconductor above a bait, we observe a high ground of the superconductor above the magnet. But when ordering a perfect diamagnetic material above a magnet, no high ground is observed. In the superconducting state, the spins or attractive spin moments of the electrons (free electrons) are joined. The coupling of these spin importance leads to the creation of a magnetic field of currents around the superconductor. When it is established in an extrinsic magnetic field, the magnetic field of currents of the superconductor interacts accompanying the external magnetic field of currents, hence the Meissner effect performs. The classical writing of the Meissner effect used in this place article discloses the difference in behaviour betwixt the superconductor and the perfect diamagnetic in the presence of an outside magnetic field.  We have proved here that the Meissner effect is nothing in addition to an electromagnetic interaction betwixt the magnetic field designed by the superconductor and the magnetic field of currents of the magnet. The electromagnetic interplay between the magnetic field of currents of a superconductor and that of a bait during a Meissner effect is fundamentally similar to the electromagnetic interplay between two free electrons of the superfluid vapor.  The study also showed that the expansion of outer space is only a Meissner effect between superconducting dark matter and leading attractive fields. We also identified that this expansion is increased because the gravitational force middle from two points dark matter and the stars about it decreases as these stars move from the superconducting dark matter.  We also projected a new method of detached sensing anticipate where the superconducting subsidiary is perpetually levitating on the midnight side of the earth and a new and more persuasive way to find new particles through a superconducting indicator levitating in the upper atmosphere utilizing this classical writing of the Meissner effect.

Author(s) Details:

Elie W’ishe Sorongane,
Physics Department, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.

Please see the link here: https://stm.bookpi.org/FRAPS-V7/article/view/11117

Analysis of the Impact of Sustainable Land Management Practices on Vegetation Cover in Balaka District, Malawi | Chapter 8 | Novel Perspectives of Geography, Environment and Earth Sciences Vol. 8

 Sustainable Land Management (SLM) practices are important to reduce land degradation, considering that 25% of global land is degraded. A study was conducted in Malikula micro-catchment in Balaka District to analyse the impact of SLM practices on vegetation. Quantitative and qualitative data were collected and analysed using a mixed methods approach. A household survey was conducted to collect information on existing SLM practices in the area and the factors influencing households to implement them. Selected Landsat Remote Sensing Imagery (LRSI) data for 30 years from 1991 to 2021 were downloaded and analysed in QGIS 3.22.10 (Biatoiweza) software using Semi-Automatic Classification Plugin (SCP) to determine LULC changes related to vegetation and Normalised Difference Vegetation Index (NDVI) over the study period. Additional land productivity and rainfall data obtained from the Balaka Agricultural Office and the Department of Climate Change and Meteorological Services (DCCMS), respectively, were also analysed. The results indicate that ISFM is the most practised SLM intervention and that the need for soil fertility improvement drives households to adopt it. In addition, households with access to extension services and more land have a higher probability of adopting SLM practices.

Further, more female-headed households adopt SLM practices than male-headed households despite the latter being more knowledgeable. LULC analysis (Overall Accuracy and Kappa Coefficient of 89.2% and 0.78, respectively) show an increasing trend in dense and very dense vegetation cover at the expense of wetlands. Despite a decline in annual rainfall amounts during the study period, the study has found a positive correlation between mean NDVI and land area under RWH (R = 0.51), highlighting the impact of RWH on improved vegetation cover. The study recommends further gender analysis to understand SLM information asymmetry, more investment in extension services, promotion of SLM packages that appeal to farmers with limited land and exploration of innovative financing options for SLM practices to incentivise adoption. Lastly, the study recommends additional studies in the area to understand the decline in land area for wetlands.

Author(s) Details:

Chikumbutso Kilembe,
Department of Geography and Environmental Studies, The Catholic University of Malawi, Malawi.

Maureen Kapute Mzuza,
Department of Geography and Environmental Studies, The Catholic University of Malawi, Malawi.

Please see the link here: https://stm.bookpi.org/NPGEES-V8/article/view/11016

The Application of Remote Sensing in Vegetation Cover, Sudan | Chapter 8 | Cutting Edge Research in Biology Vol. 5

 This paper wanted to review several studies on the use of detached sensing in Sudan accompanying a focus on plants cover in various domains by many scholars; the unification of remote thinking in the gum Arabic belt; pertaining to the south Gadarif region; ahable and chunk grabou area, silver Nile state with a devote effort to something the amount and mapping of land use land cover change through plan and monitoring the changes that happen in land use land cover, due to dryness, climate change, and transgression; east of the Nile Khartoum State, and in the middle during a half-of one hundred years. Following are recommendations came from these studies: the use of assessment signs including NDVI, SAVI, and PCA –maneuvered in color composite and/or unsupervised categorization can be secondhand as an appropriate mean for rangeland monitoring and amount which was urged from the study of North Kordofan state.

Author(s) Details:

Eisa M. Ahmed,
Department of Crop Protection, Faculty of Natural Resources and Environmental Studies, University of Kordofan, P.O Box 160 –Elobeid, 51111, Sudan.

El Gunaid F. Hassan,
Department of Forestry and Range Sciences, University of Bakht Er-Ruda, Ad Duwem, Sudan.

Please see the link here: https://stm.bookpi.org/CERB-V5/article/view/9853