Journal Description
Earth
Earth
is an international, peer-reviewed, open access journal on earth science, published quarterly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within ESCI (Web of Science), Scopus, GeoRef, AGRIS, and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 21.7 days after submission; acceptance to publication is undertaken in 1.8 days (median values for papers published in this journal in the first half of 2024).
- Journal Rank: CiteScore - Q2 (Environmental Science (miscellaneous))
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
Impact Factor:
2.1 (2023);
5-Year Impact Factor:
2.1 (2023)
Latest Articles
Is Zagreb Green Enough? Influence of Urban Green Spaces on Mitigation of Urban Heat Island: A Satellite-Based Study
Earth 2024, 5(4), 604-622; https://doi.org/10.3390/earth5040031 (registering DOI) - 5 Oct 2024
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The urban heat island phenomenon is a climatic condition in which urbanized areas exhibit higher temperature values than their natural surroundings. This occurs due to an unbalanced energy budget caused by the extensive use of synthetic materials. In such a scenario, urban green
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The urban heat island phenomenon is a climatic condition in which urbanized areas exhibit higher temperature values than their natural surroundings. This occurs due to an unbalanced energy budget caused by the extensive use of synthetic materials. In such a scenario, urban green areas act as stressors to mitigate the intensity of the urban heat island and improve urban well-being. This study analyzes the spatial-temporal characteristics of the urban heat island in Zagreb, Croatia, aiming to examine the role of different types of green infrastructure in mitigating elevated temperature values and facilitating the definition of greener planning strategies. To achieve this, a multitemporal remote sensing- and NDVI-based analysis was conducted for the time series 1984–2014. An urban heat island intensity map was obtained for the selected 30-year period, along with thermal graphs registering land surface temperature values among different city districts. The results reveal significant heterogeneity, displaying variable behavior dependent on the city district. The role of Zagreb’s urban green areas in urban heat island mitigation is evident but largely dependent on urban morphology, construction types, and periods. Urban forests and urban parks play the most significant role in temperature reduction, followed by residential building neighborhoods and extensive neighborhoods consisting of familiar houses with gardens. Continuously built areas, such as the city center and industrial zones, are less prone to registering lower intensity values. Additionally, multitemporal intensity variations based on land use changes are registered in several districts.
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Open AccessArticle
Assessment of Active Tectonics Using Geomorphic Indices and Morphometric Parameters in the Setifian Highlands Region
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Riheb Hadji, Hassan Taib, Matteo Gentilucci, Younes Hamed, Rayan Khalil, Basim Asghar, Maurizio Barbieri and Gilberto Pambianchi
Earth 2024, 5(4), 583-603; https://doi.org/10.3390/earth5040030 - 3 Oct 2024
Abstract
The present study aims to assess the tectonic activity in the South Setifian allochthonous complex, providing insights into the evolution of the landscape. A morphometric analysis of Jebel Youcef Mountain (JYM) in Eastern Algeria was conducted to assess neotectonic activity. Six quantitative parameters
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The present study aims to assess the tectonic activity in the South Setifian allochthonous complex, providing insights into the evolution of the landscape. A morphometric analysis of Jebel Youcef Mountain (JYM) in Eastern Algeria was conducted to assess neotectonic activity. Six quantitative parameters were analyzed: stream length-gradient index, asymmetric factor, hypsometric integral, valley floor width-to-valley height ratio, index of drainage basin shape, and index of mountain front sinuosity across the 16 river basins in the region. The geomorphic indices are combined into a single index of relative tectonic activity (IRTA), categorized into four classes: very high, high, moderate, and low. The results identified two major lineament sets. The NE-SW lineament set is the dominant structural feature, playing a key role in driving recent geological processes and deformation in the study area. In contrast, the E-W and NW-SE lineament sets exert a more localized influence, primarily affecting the Jurassic formations at Kef El Ahmar’s central peak in Jebel Youcef, though they exhibit relatively lower tectonic activity compared to the NE-SW lineament set. Based on the relative active tectonic classes, significant neotectonic activity is evident in the study area, as shown by distinctive basement fracturing. The findings contribute to understanding the structural processes in the study area. Furthermore, the study establishes a systematic framework for analyzing tectonic activity and landscape morphology evolution, enhancing our perception of the convergence between the North African Alpine zones and the Atlas range.
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Open AccessArticle
Monitoring Gas Emissions in Agricultural Productions through Low-Cost Technologies: The POREM (Poultry-Manure-Based Bio-Activator for Better Soil Management through Bioremediation) Project Experience
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Domenico Suriano and Francis Olawale Abulude
Earth 2024, 5(4), 564-582; https://doi.org/10.3390/earth5040029 - 27 Sep 2024
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Agricultural production or rural activities can involve the emission of unpleasant gases, malodors, or most commonly, greenhouse gases. In any case, the control and monitoring of such emissions in rural, unattended, and remote locations represent an issue in need of addressing. In this
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Agricultural production or rural activities can involve the emission of unpleasant gases, malodors, or most commonly, greenhouse gases. In any case, the control and monitoring of such emissions in rural, unattended, and remote locations represent an issue in need of addressing. In this article, the monitoring of gases produced by a poultry manure depot and performed by devices based on low-cost gas sensors in the context of the POREM (poultry-manure-based bio-activator for better soil management through bioremediation) project is reported. This experience has shown that the continuous and real-time monitoring of gas emissions in an unattended, remote, and rural area, where it is unfeasible to employ expensive, professional instruments, can be successfully performed by low-cost technologies. Two portable monitoring units developed in the laboratory and based on low-cost gas sensors were used to provide indications about the concentrations of NH3, CH4, H2S, and CO2. During this experiment, two monitors were deployed: the first one was placed in the manure storage depot, while the second one was deployed out of the storage site to compare the gas concentrations related to the outdoor environment with the gas emissions coming from the manure. Both devices were wirelessly linked to the Internet, even though the radio signal was weak and unstable in that area. This situation provided us with the opportunity to test a particular protocol based on sending and receiving e-mails containing commands for the remote machines. This experiment proved the effectiveness of the use of low-cost devices for gas emission monitoring in such particular environments.
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Open AccessCommunication
A Case Study of the Possible Meteorological Causes of Unexpected Fire Behavior in the Pantanal Wetland, Brazil
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Flavio T. Couto, Filippe L. M. Santos, Cátia Campos, Carolina Purificação, Nuno Andrade, Juan M. López-Vega and Matthieu Lacroix
Earth 2024, 5(3), 548-563; https://doi.org/10.3390/earth5030028 - 18 Sep 2024
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This study provides insights into large fires in the Pantanal by analyzing the atmospheric conditions that influenced the rapid fire evolution between 13 and 14 November 2023, when fire fronts spread rapidly, leading to critical situations for firefighters. The observation-based analysis helped us
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This study provides insights into large fires in the Pantanal by analyzing the atmospheric conditions that influenced the rapid fire evolution between 13 and 14 November 2023, when fire fronts spread rapidly, leading to critical situations for firefighters. The observation-based analysis helped us to identify some characteristics of the fire’s evolution and the meteorological conditions in the region. Furthermore, two simulations were run with the Meso-NH model, which was configured with horizontal resolutions of 2.5 km and 5 km. The fire behavior, characterized by satellite observations, revealed periods with a sudden increase in active fire numbers. High temperatures and low relative humidity in the region characterized the fire weather conditions. The simulations confirmed the critical fire condition, showing the benefits of increasing the resolution of numerical models for the Pantanal region. The convection-resolving simulation at 2.5 km showed the repeated development of gust fronts in the late afternoon and early evening. This study highlights this dynamic that, coupled with intense surface wind gusts, was crucial for the intensification of the fire spread and unexpected behavior. This study is a first step toward better understanding fire dynamics in the Pantanal through atmospheric modeling, and it can support strategies for firefighting in the region.
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Open AccessArticle
Quantum Tensor DBMS and Quantum Gantt Charts: Towards Exponentially Faster Earth Data Engineering
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Ramon Antonio Rodriges Zalipynis
Earth 2024, 5(3), 491-547; https://doi.org/10.3390/earth5030027 - 14 Sep 2024
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Earth data is essential for global environmental studies. Many Earth data types are naturally modeled by multidimensional arrays (tensors). Array (Tensor) DBMSs strive to be the best systems for tensor-related workloads and can be especially helpful for Earth data engineering, which takes up
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Earth data is essential for global environmental studies. Many Earth data types are naturally modeled by multidimensional arrays (tensors). Array (Tensor) DBMSs strive to be the best systems for tensor-related workloads and can be especially helpful for Earth data engineering, which takes up to 80% of Earth data science. We present a new quantum Array (Tensor) DBMS data model and new quantum approaches that rely on the upcoming quantum memory and demonstrate exponential speedups when applied to many of the toughest Array (Tensor) DBMS challenges stipulated by classical computing and real-world Earth data use-cases. We also propose new types of charts: Quantum Gantt (QGantt) Charts and Quantum Network Diagrams (QND). QGantt charts clearly illustrate how multiple operations occur simultaneously across different data items and what are the input/output data dependencies between these operations. Unlike traditional Gantt charts, which typically track project timelines and resources, QGantt charts integrate specific data items and operations over time. A Quantum Network Diagram combines several QGantt charts to show dependencies between multistage operations, including their inputs/outputs. By using a static format, QGantt charts and Quantum Network Diagrams allow users to explore complex processes at their own pace, which can be beneficial for educational and R&D purposes.
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Open AccessFeature PaperArticle
A Spatial Econometric Analysis of Weather Effects on Milk Production
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Xinxin Fan and Jiechao Ma
Earth 2024, 5(3), 477-490; https://doi.org/10.3390/earth5030026 - 11 Sep 2024
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Greenhouse gas (GHG) emission-induced climate change, particularly occurring since the mid-20th century, has been considerably affecting short-term weather conditions, such as increasing weather variability and the incidence of extreme weather-related events. Milk production is sensitive to such changes. In this study, we use
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Greenhouse gas (GHG) emission-induced climate change, particularly occurring since the mid-20th century, has been considerably affecting short-term weather conditions, such as increasing weather variability and the incidence of extreme weather-related events. Milk production is sensitive to such changes. In this study, we use spatial panel econometric models, the spatial error model (SEM) and the spatial Durbin model (SDM), with a panel dataset at the state-level varying over seasons, to estimate the relationship between weather indicators and milk productivity, in an effort to reduce the bias of omitted climatic variables that can be time varying and spatially correlated and cannot be directly captured by conventional panel data models. We find an inverse U-shaped effect of summer heat stress on milk production per cow (MPC), indicating that milk production reacts positively to a low-level increase in summer heat stress, and then MPC declines as heat stress continues increasing beyond a threshold value of 72. Additionally, fall precipitation exhibits an inverse U-shaped effect on MPC, showing that milk yield increases at a decreasing rate until fall precipitation rises to 14 inches, and then over that threshold, milk yield declines at an increasing rate. We also find that, relative to conventional panel data models, spatial panel econometric models could improve prediction performance by leading to smaller in-sample and out-sample root mean squared errors. Our study contributes to the literature by exploring the feasibility of promising spatial panel models and resulting in estimating weather influences on milk productivity with high model predicting performance.
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Open AccessArticle
Analysis of the Status of Irrigation Management in North Carolina
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Anuoluwapo Omolola Adelabu, Blessing Masasi and Olabisi Tolulope Somefun
Earth 2024, 5(3), 463-476; https://doi.org/10.3390/earth5030025 - 7 Sep 2024
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Farmers in North Carolina are turning to irrigation to reduce the impacts of droughts and rainfall variability on agricultural production. Droughts, rainfall variability, and the increasing demand for food, feed, fiber, and fuel necessitate the urgent need to provide North Carolina farmers with
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Farmers in North Carolina are turning to irrigation to reduce the impacts of droughts and rainfall variability on agricultural production. Droughts, rainfall variability, and the increasing demand for food, feed, fiber, and fuel necessitate the urgent need to provide North Carolina farmers with tools to improve irrigation management and maximize water productivity. This is only possible by understanding the current status of irrigated agriculture in the state and investigating its potential weaknesses and opportunities. Thus, the objective of this study was to perform a comprehensive analysis of the current state of irrigation management in North Carolina based on 15-year data from the Irrigation and Water Management Survey by the United States Department of Agriculture–National Agricultural Statistics Service (USDA-NASS). The results indicated a reduction in irrigation acres in the state. Also, most farms in the state have shifted to efficient sprinkler irrigation systems from gravity-fed surface irrigation systems. However, many farms in North Carolina still rely on traditional irrigation scheduling methods, such as examining crop conditions and the feel of soil in deciding when to irrigate. Hence, there are opportunities for enhancing the adoption of advanced technologies like soil moisture sensors and weather data to optimize irrigation schedules for improving water efficiency and crop production. Precision techniques and data-based solutions empower farmers to make informed, real-time decisions, optimizing water use and resource allocation to match the changing environmental conditions. The insights from this study provide valuable information for policymakers, extension services, and farmers to make informed decisions to optimize agricultural productivity and conserve water resources.
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Open AccessArticle
Support Vector Machine Algorithm for Mapping Land Cover Dynamics in Senegal, West Africa, Using Earth Observation Data
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Polina Lemenkova
Earth 2024, 5(3), 420-462; https://doi.org/10.3390/earth5030024 - 6 Sep 2024
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This paper addresses the problem of mapping land cover types in Senegal and recognition of vegetation systems in the Saloum River Delta on the satellite images. Multi-seasonal landscape dynamics were analyzed using Landsat 8-9 OLI/TIRS images from 2015 to 2023. Two image classification
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This paper addresses the problem of mapping land cover types in Senegal and recognition of vegetation systems in the Saloum River Delta on the satellite images. Multi-seasonal landscape dynamics were analyzed using Landsat 8-9 OLI/TIRS images from 2015 to 2023. Two image classification methods were compared, and their performance was evaluated in the GRASS GIS software (version 8.4.0, creator: GRASS Development Team, original location: Champaign, Illinois, USA, currently multinational project) by means of unsupervised classification using the k-means clustering algorithm and supervised classification using the Support Vector Machine (SVM) algorithm. The land cover types were identified using machine learning (ML)-based analysis of the spectral reflectance of the multispectral images. The results based on the processed multispectral images indicated a decrease in savannas, an increase in croplands and agricultural lands, a decline in forests, and changes to coastal wetlands, including mangroves with high biodiversity. The practical aim is to describe a novel method of creating land cover maps using RS data for each class and to improve accuracy. We accomplish this by calculating the areas occupied by 10 land cover classes within the target area for six consecutive years. Our results indicate that, in comparing the performance of the algorithms, the SVM classification approach increased the accuracy, with 98% of pixels being stable, which shows qualitative improvements in image classification. This paper contributes to the natural resource management and environmental monitoring of Senegal, West Africa, through advanced cartographic methods applied to remote sensing of Earth observation data.
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(This article belongs to the Topic Environmental Footprints Forecasts Using Remote Sensing, Information Technology and Artificial Intelligence Methods)
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Open AccessArticle
Index-Based Alteration of Long-Term River Flow Regimes Influenced by Land Use Change and Dam Regulation
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Raoof Mostafazadeh, Mostafa Zabihi Silabi, Javanshir Azizi Mobaser and Bita Moezzipour
Earth 2024, 5(3), 404-419; https://doi.org/10.3390/earth5030023 - 31 Aug 2024
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The growing population and expansion of rural activities, along with changing climatic patterns and the need for water during drought periods, have led to a rise in the water demand worldwide. As a result, the construction of water storage structures such as dams
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The growing population and expansion of rural activities, along with changing climatic patterns and the need for water during drought periods, have led to a rise in the water demand worldwide. As a result, the construction of water storage structures such as dams has increased in recent years to meet the water needs. However, dam construction can bring significant alterations to the natural flow regime of rivers, and it is therefore essential to understand the potential effects of human structures on the hydrological regime of rivers to reduce their destructive impacts. This study analyzes the hydrological changes in the Shahrchai River in response to the Shahrchai Dam construction in Urmia, Iran. The study period was from 1950 to 2017 at the Urmia Band station. The Indicators of Hydrological Alteration (IHA) were used to analyze the hydrological changes before and after regulating, accounting for land use changes and climatic factors. The results revealed the adverse effects of the Shahrchai Dam on the hydrological indices. The analysis showed an increase in the average flow rate during the summer season and a decrease in other seasons. However, the combined effects of water transferring for drinking purposes, a decrease in permanent snow cover upstream of the dam, and an increase in water use for irrigation and agricultural purposes resulted in a decrease in the released river flow. Furthermore, the minimum and maximum daily flow rates decreased by approximately 85% and 65%, respectively, after the construction of the Shahrchai Dam. Additionally, the number of days with maximum flow rates increased from 117 days in the pre-dam period to 181 days in the post-dam period. As a concluding remark, the construction of the Shahrchai Dam, land use/cover changes, and a decrease in permanent snow cover had unfavorable effects on the hydrological regime of the river. Therefore, the hydrological indicators should be adjusted to an acceptable level compared to the natural state to preserve the river ecosystem. The findings of this study are expected to guide water resource managers in regulating the sustainable flow regime of permanent rivers.
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(This article belongs to the Topic Climate Change and Human Impact on Freshwater Water Resources: Rivers and Lakes)
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Open AccessArticle
Using the Contrast Boundary Concentration of LST for the Earthquake Approach Assessment in Turkey, 6–8 February 2023
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Serhii Nikulin, Kateryna Sergieieva, Olga Korobko and Vita Kashtan
Earth 2024, 5(3), 388-403; https://doi.org/10.3390/earth5030022 - 18 Aug 2024
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Land surface temperature (LST) variations and anomalies associated with tectonic plate movements have been documented before large earthquakes. In this work, we propose that spatially extended and dynamic linear zones of high temperature anomalies at the Earth’s surface coinciding with faults in the
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Land surface temperature (LST) variations and anomalies associated with tectonic plate movements have been documented before large earthquakes. In this work, we propose that spatially extended and dynamic linear zones of high temperature anomalies at the Earth’s surface coinciding with faults in the Earth’s crust may be used as a predictor of an approaching earthquake. LST contrast boundary concentration maps are suggested to be a possible indicator for analyzing temperature changes before and after seismic sequences. Here, we analyze the concentration of LST contrast boundaries estimated from Landsat 8–9 data for the East Anatolian Fault Zone in the vicinity of epicenters of the destructive earthquakes with magnitudes up to 7.8 Mw that occurred in February 2023. A spatial relationship between earthquake epicenters and the maximum concentration of LST boundaries at azimuths of 0° and 90° was found to strengthen as the earthquake approaches and weaken after it. It was found that 92% of epicenters are located at up to 5 km distance from zones of maximum LST boundary concentration. The evidence presented in this work supports the idea that LST may provide valuable information for seismic hazard assessment before large earthquakes.
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Open AccessArticle
Using Public Participation GIS to Assess Effects of Industrial Zones on Risk and Landscape Perception: A Case Study of Tehran Oil Refinery, Iran
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Mahdi Gheitasi, David Serrano Giné, Nora Fagerholm and Yolanda Pérez Albert
Earth 2024, 5(3), 371-387; https://doi.org/10.3390/earth5030021 - 16 Aug 2024
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Petrochemical clusters are forms of industrialization that use compounds and polymers derived directly or indirectly from gas or crude oil for chemical applications. They pose a variety of short- and long-term risks to the environment and the people who live nearby. The aim
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Petrochemical clusters are forms of industrialization that use compounds and polymers derived directly or indirectly from gas or crude oil for chemical applications. They pose a variety of short- and long-term risks to the environment and the people who live nearby. The aim of this study is to determine whether there is a correlation between the degree of perceived technological risk and the emotional value generated by the contemplation of the petrochemical industry landscape in order to try to establish strategic lines of action to mitigate the perception of risk and improve the emotional well-being of the population. This study uses manipulated pictures and a Public Participation Geographic Information System (PPGIS) survey to assess changes in perception and emotional response in residents in Teheran (Iran). Key findings show an insignificant relationship between technological risk and landscape value perception in both original and manipulated pictures. However, taking into account that, in general, in manipulated pictures, there is a more significant relationship, designing the landscape could help to mitigate the technological risk perception. This study contributes to the broader discussion about industrialization and its environmental and social consequences. It emphasizes the importance of considering public perception when planning and developing industrial areas, so as to balance industrial functionality and environmental and aesthetic considerations for long-term urban development.
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Open AccessArticle
Blockchain Projects in Environmental Sector: Theoretical and Practical Analysis
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Matteo Vaccargiu and Roberto Tonelli
Earth 2024, 5(3), 354-370; https://doi.org/10.3390/earth5030020 - 14 Aug 2024
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The growing interest in environmental sustainability issues and, at the same time, the advantages offered by blockchain technology have strong connections to each other. This study explores the application of blockchain technology across various environmental domains, such as air quality, climate change impacts,
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The growing interest in environmental sustainability issues and, at the same time, the advantages offered by blockchain technology have strong connections to each other. This study explores the application of blockchain technology across various environmental domains, such as air quality, climate change impacts, and resource management. The research utilised a dual approach, combining a bibliometric analysis with VOSviewer and a topic analysis using BERT models to assess the discourse within both the scientific literature extracted from Scopus and practical blockchain projects obtained from GitHub. The findings reveal that food security, energy, and sustainable agriculture are predominant topics in academic discussions, with a noticeable increase in focus from 2017 onwards. Practical projects are focused on transparent tracking and decentralised management. The overlap between academic and practical spheres is evident in the shared focus on energy and environmental management, demonstrating blockchain’s growing role in addressing global environmental challenges. This study underscores the importance of integrating theoretical research with practical implementations to harness blockchain’s full potential in promoting sustainable environmental practices.
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Open AccessArticle
The Impact of Land Cover on Nest Occupancy of the White Stork (Ciconia ciconia (L.)): A Case Study of Kampinos Forest, 2006–2018
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Joanna Bihałowicz, Axel Schwerk, Izabela Dymitryszyn, Adam Olszewski and Jan Stefan Bihałowicz
Earth 2024, 5(3), 336-353; https://doi.org/10.3390/earth5030019 - 1 Aug 2024
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Land cover is one of the spatial factors influencing the ecological niche of animal populations. Some types of land cover predetermine a particular site as a habitat for certain species. One of the flagship species of agrocenosis is the white stork (Ciconia
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Land cover is one of the spatial factors influencing the ecological niche of animal populations. Some types of land cover predetermine a particular site as a habitat for certain species. One of the flagship species of agrocenosis is the white stork (Ciconia ciconia (L.)). This study focuses on the occupancy of 122 nests in the vicinity of Kampinos National Park in Poland. This area is a mixture of traditional agricultural settlements, forests, the Vistula valley, and the suburbs of Warsaw, Poland. This mix allows for the identification of land cover disturbances that affect the white stork’s nest occupancy. The current state of development and the efficiency of remote sensing-based land cover databases allows us to easily identify spatial factors affecting nest occupancy and to analyse them in a longer timeframe. The study analyses land cover in buffers of 1 to 5 km around white stork nests based on CORINE Land Cover (CLC) for the years 2006, 2012, and 2018. Although the white stork’s habitat is well studied, the CLC-based results provide significant new insights. The results show that nest occupancy increases with an increasing proportion of agricultural land, especially with significant natural vegetation, while the proportion of wetlands and water is not significant. This work provides a description of the ideal habitat for the white stork in terms of nest occupancy.
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Open AccessEditorial
Progress in the Earth Journal
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Charles Jones
Earth 2024, 5(3), 332-335; https://doi.org/10.3390/earth5030018 - 1 Aug 2024
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The Earth journal (ISSN 2673-4834) is an open-access international high-quality peer review venue that promotes multi-disciplinary research over a broad spectrum of natural, social and applied sciences [...]
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Open AccessEditor’s ChoiceArticle
Investigating Seismic Events along the Eurasian Plate between Greece and Turkey: 10 Years of Seismological Analysis and Implications
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Alexandra Moshou
Earth 2024, 5(3), 311-331; https://doi.org/10.3390/earth5030017 - 26 Jul 2024
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The North Aegean Sea region in Greece is located at the convergence of the Eurasian, African, and Anatolian tectonic plates. The region experiences frequent seismicity ranging from moderate to large-magnitude earthquakes. Tectonic interactions and seismic events in this area have far-reaching implications for
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The North Aegean Sea region in Greece is located at the convergence of the Eurasian, African, and Anatolian tectonic plates. The region experiences frequent seismicity ranging from moderate to large-magnitude earthquakes. Tectonic interactions and seismic events in this area have far-reaching implications for understanding the broader geological processes in the eastern Mediterranean region. This study aims to conduct a comprehensive investigation of the seismic activity of the North Aegean Sea region by employing advanced seismological techniques and data analyses. Data from onshore seismological networks were collected and analyzed to assess the characteristics of the earthquakes in the region. Seismicity patterns, focal mechanisms, and seismic moment calculations were performed to assess current seismic activity. The present study combined spatiotemporal analysis with the analysis of genesis mechanisms, and this resulted in more results than those of previous studies. Detailed analysis of the seismic data showed patterns in the occurrence of earthquakes over time, with periodic episodes of increased seismic activity compared to activities followed by quieter periods. Finally, this study proves that recent earthquakes in the study area (2017, 2020) highlight the complexity of seismicity as well as the consequences of strong earthquakes on people and buildings. Overall, these findings suggest that the North Aegean Sea is becoming increasingly seismically active and is a potential risk zone for adjacent regions.
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Open AccessArticle
DNA Takes Over on the Control of the Morphology of the Composite Self-Organized Structures of Barium and Calcium Silica–Carbonate Biomorphs, Implications for Prebiotic Chemistry on Earth
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Mayra Cuéllar-Cruz, Selene R. Islas and Abel Moreno
Earth 2024, 5(3), 293-310; https://doi.org/10.3390/earth5030016 - 24 Jul 2024
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The origin of life is associated with the existing environmental factors of the Precambrian Era of the Earth. The minerals rich in sodium silicates, in aluminum and in other chemical elements, such as kaolinite, were among the factors present at that time. Kaolinite
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The origin of life is associated with the existing environmental factors of the Precambrian Era of the Earth. The minerals rich in sodium silicates, in aluminum and in other chemical elements, such as kaolinite, were among the factors present at that time. Kaolinite is an abundant mineral on our planet, which indicates that it possibly had an essential role in the origin of the first blocks that constructed life on Earth. Evidence of this is the cherts, which are rocks with a high concentration of silica that retain the vestiges of the most ancient life on our planet. There are also inorganic structures called biomorphs that are like the cherts of the Precambrian, which take on a morphology and crystalline structure depending on the chemical molecules that make up the reaction mixture. To evaluate the interaction of kaolinite with DNA, the objective of this work is to synthesize biomorphs in the presence of kaolinite and genomic DNA that comes from a prokaryote and a eukaryote microorganism. Our results show that the difference between the prokaryote DNA and the eukaryote DNA favors the morphology and the crystalline phase of the calcium silica–carbonate biomorphs, while in the case of the barium silica–carbonate biomorphs, the environmental factors participate directly in the morphology but not in the crystalline phase. Results show that when a mineral such as kaolinite is present in genomic DNA, it is precisely the DNA that controls both the morphology and the crystalline phase as well as the chemical composition of the structure. This fact is relevant as it shows that, independently of the morphology or the of size of the organism, it is the genomic DNA that controls all the chemical elements toward the most stable structure, therefore allowing the perpetuation, conservation and maintenance of life on our planet (since the origin of the genomic DNA in the Precambrian Era to the present day).
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Open AccessArticle
Integration of UH SUH, HEC-RAS, and GIS in Flood Mitigation with Flood Forecasting and Early Warning System for Gilireng Watershed, Indonesia
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Muhammad Rifaldi Mustamin, Farouk Maricar, Rita Tahir Lopa and Riswal Karamma
Earth 2024, 5(3), 274-292; https://doi.org/10.3390/earth5030015 - 8 Jul 2024
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A flood forecasting and early warning system is critical for rivers that have a large flood potential, one of which is the Gilireng watershed, which floods every year and causes many losses in Wajo Regency, Indonesia. This research also introduces an integration model
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A flood forecasting and early warning system is critical for rivers that have a large flood potential, one of which is the Gilireng watershed, which floods every year and causes many losses in Wajo Regency, Indonesia. This research also introduces an integration model between UH SUH and HEC-RAS in flood impact analysis, as a reference for flood forecasting and early warning systems in anticipating the timing and occurrence of floods, as well as GIS in the spatial modeling of flood-prone areas. Broadly speaking, this research is divided into four stages, namely, a flood hydrological analysis using UH SUH, flood hydraulic tracing using a 2D HEC-RAS numerical model, the spatial modeling of flood-prone areas using GIS, and the preparation of flood forecasting and early warning systems. The results of the analysis of the flood forecasting and early warning systems obtained the flood travel time and critical time at the observation point, the total time required from the upstream observation point to level 3 at Gilireng Dam for 1 h 35 min, Mamminasae Bridge for 4 h 35 min, and Akkotengeng Bridge for 8 h 40 min. This is enough time for people living in flood-prone areas to evacuate to the 15 recommended evacuation centers.
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Open AccessArticle
Disaggregating Land Degradation Types for United Nations (UN) Land Degradation Neutrality (LDN) Analysis Using the State of Ohio (USA) as an Example
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Elena A. Mikhailova, Hamdi A. Zurqani, Lili Lin, Zhenbang Hao, Christopher J. Post, Mark A. Schlautman and Camryn E. Brown
Earth 2024, 5(2), 255-273; https://doi.org/10.3390/earth5020014 - 20 Jun 2024
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The United Nations (UN) Land Degradation Neutrality (LDN) evaluation stresses the need to account for different types of land degradation (LD) as part of the UN Sustainable Development Goal (SDG 15: Life on Land) and UN Convention to Combat Desertification (UNCCD). For example,
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The United Nations (UN) Land Degradation Neutrality (LDN) evaluation stresses the need to account for different types of land degradation (LD) as part of the UN Sustainable Development Goal (SDG 15: Life on Land) and UN Convention to Combat Desertification (UNCCD). For example, one of the indicators, 15.3.1 Proportion of land that is degraded over total land area, can be differentiated between different types of LD (e.g., urban development, agriculture, barren) when considering land use and land cover (LULC) change analysis. This study demonstrates that it is important to consider not only the overall anthropogenic LD status and trend over time, but also the type of LD to confirm LDN. This study’s innovation is that it leverages remote-sensing-based LULC change analysis to evaluate LDN by different types of LD using the state of Ohio (OH) as a case study. Almost 67% of land in OH experienced anthropogenic LD primarily due to agriculture (81%). All six soil orders were subject to various degrees of anthropogenic LD: Mollisols (88%), Alfisols (70%), Histosols (58%), Entisols (55%), Inceptisols (43%), and Ultisols (22%). All land developments in OH can be linked to damages from LD, with 10,116.3 km2 developed, resulting in midpoint losses of 1.4 × 1011 kg of total soil carbon (TSC) and a midpoint social cost of carbon dioxide emissions (SC-CO2) of $24B (where B = billion = 109, USD). Overall, the anthropogenic LD trend between 2001 and 2016 indicated LDN, however, during the same time, there was a six percent increase in developed area (577.6 km2), which represents a consumptive land conversion that likely caused the midpoint loss of 8.4 × 109 kg of TSC and a corresponding midpoint of $1.4B in SC-CO2. New developments occurred adjacent to current urban areas, near the capital city of Columbus, and other cities (e.g., Dayton, Cleveland). Developments negated OH’s overall LDN because of multiple types of damages: soil C loss, associated “realized” soil C social costs (SC-CO2), and loss of soil C sequestration potential. The state of OH has very limited potential land (1.2% of the total state area) for nature-based solutions (NBS) to compensate for the damages, which extend beyond the state’s boundaries because of the greenhouse gas emissions (GHG).
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Open AccessArticle
Combining Low-Cost UAV Imagery with Machine Learning Classifiers for Accurate Land Use/Land Cover Mapping
by
Spyridon E. Detsikas, George P. Petropoulos, Kleomenis Kalogeropoulos and Ioannis Faraslis
Earth 2024, 5(2), 244-254; https://doi.org/10.3390/earth5020013 - 19 Jun 2024
Abstract
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Land use/land cover (LULC) is a fundamental concept of the Earth’s system intimately connected to many phases of the human and physical environment. LULC mappings has been recently revolutionized by the use of high-resolution imagery from unmanned aerial vehicles (UAVs). The present study
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Land use/land cover (LULC) is a fundamental concept of the Earth’s system intimately connected to many phases of the human and physical environment. LULC mappings has been recently revolutionized by the use of high-resolution imagery from unmanned aerial vehicles (UAVs). The present study proposes an innovative approach for obtaining LULC maps using consumer-grade UAV imagery combined with two machine learning classification techniques, namely RF and SVM. The methodology presented herein is tested at a Mediterranean agricultural site located in Greece. The emphasis has been placed on the use of a commercially available, low-cost RGB camera which is a typical consumer’s option available today almost worldwide. The results evidenced the capability of the SVM when combined with low-cost UAV data in obtaining LULC maps at very high spatial resolution. Such information can be of practical value to both farmers and decision-makers in reaching the most appropriate decisions in this regard.
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Open AccessArticle
Using Google Earth Engine to Assess the Current State of Thermokarst Terrain on Arga Island (the Lena Delta)
by
Andrei Kartoziia
Earth 2024, 5(2), 228-243; https://doi.org/10.3390/earth5020012 - 12 Jun 2024
Abstract
The mapping of thermokarst landscapes and the assessment of their conditions are becoming increasingly important in light of a rising global temperature. Land cover maps provide a basis for quantifying changes in landscapes and identifying areas that are vulnerable to permafrost degradation. The
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The mapping of thermokarst landscapes and the assessment of their conditions are becoming increasingly important in light of a rising global temperature. Land cover maps provide a basis for quantifying changes in landscapes and identifying areas that are vulnerable to permafrost degradation. The study is devoted to assessing the current state of thermokarst terrain on Arga Island. We applied a random forests algorithm using the capabilities of the Google Earth Engine cloud platform for the supervised classification of the composite image. The analyzed composite consists of a Sentinel-2 image and a set of calculated indices. The study found that thermokarst-affected terrains occupy 35% of the total area, and stable terrains cover 29% at the time of image acquisition. The classifier has also mapped water bodies, slopes, and blowouts. The accuracy assessment revealed that the overall accuracy for all the different land cover classes was 98.34%. A set of other accuracy metrics also demonstrated a high level of performance. This study presents significant findings for assessing landscape changes in a region with unique environmental features. It also provides a potential basis for future interdisciplinary research and for predicting future thermokarst landscape changes in the Lena Delta area.
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(This article belongs to the Topic Effects of Climate Change on Geomorphology, Water Geochemistry and Pollution)
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