Bathymetry is a knowledge of water depth calculation, which is of great importance in many environmental management applications. The objective of this study is to improve the accuracy of the traditional ratio model as a widely used experimental bathymetry method. Therefore, firstly hybrid methods were proposed, which combined principal component analysis (PCA) and image fusion methods, to obtain more

In recent years, a large amount of data has been accumulated, such as those recorded in geological journals and report literature, which contain a wealth of information, but these data have not been fully exploited or mined. Automatic information extraction offers an effective way to achieve new discoveries and pursue further analysis, which is of great significance for users, researchers or decision

Precise point positioning (PPP) with ambiguity resolution (AR) has been proved to be an effective method to improve the positioning accuracy and shorten the convergence time, which plays an important role in geodetic and geodynamic applications. In this study, the performance achieved based on the BeiDou Navigation Satellite System (BDS-2 and BDS-3) joint PPP-AR with high rate data was considered and

With the development of urbanization, global warming, rain island effect and other factors, cities around the world are facing more frequent and intense flood events. In order to deal with the damage caused by urban flood effectively, it is increasingly important to accurately predict and characterize the information of the flood in cities. In recent years, the rise of machine learning methods provides

Groundwater plays a key role in supplying water for drinking water, irrigation water, and industry water in the northern China. Recently, the availability and quality of groundwater resources in the eastern Loess Plateau (Shanxi province) have a serious impact on the agriculture, industry, and domestic sectors. This paper investigates the spatiotemporal variations of chemical and stable isotope composition

The major problem to be overcome in mapping of coral reef ecosystem using remote sensing imagery is the confusion arises between optically similar spectral characteristics of different end-members which are to be used as input for various classification techniques. This work attempts to study in detail the possibilities of identifying the specific wavelength regions for separating optically similar

Geo-environmental information is an important basis for geohazard analysis and the integration of geo-environmental data is crucial in the construction of urban emergency management systems. In existing urban spatial information systems, the integration of geo-environmental data is neither intuitive nor efficient enough to support the analysis of geohazards well. On the basis of Web virtual globe,

The mineable coal seam at Qidong coal mine, Huaibei coalfield, is adjacent to the overlying unconsolidated confined aquifer, which may induce water inrush hazards threatening the safe mining. This study presents an information value model (IVM) for the risk assessment of water inrush based on the information value and the geographic information system (GIS). In contrast to the general risk assessment

Support Vector Regression (SVR) combined with Invasive Weeds Optimization (IWO), standalone SVR, and Radial Basis Function Neural Networks are applied to estimate channel sinuosity in perennial rivers. With this aim, a dataset with 132 sinuosity data and related geomorphologic data, corresponding to 119 perennial streams, is considered. Bayesian Mutual Information theory is used to determine the parameters

Comprehensive preview of flow characteristics and bedforms in rivers is one of the imperative purposes of river restoration projects. This study aimed to assess the application of double averaged technique for estimating the flow velocity and shear velocity in gravel bedforms by field research throughout the Babolroud River in north of Iran. Also, quadrant analysis carried out to investigate the turbulence

Commutative encryption and watermarking (CEW) can provide comprehensive protection for vector data in geographical information system (GIS) by integrating encryption and watermarking. However, the existing CEW methods for image or video are not suitable for GIS vector data. These CEW methods are still unable to ensure independence between encryption and watermarking for GIS vector data. To solve this

The hyperspectral image consists of a high number of bands with low bandwidth which gives the advantage in the identification and detection of the features in the level of mineral and chemical composition. But the availability of hyperspectral data is very less and is highly expensive when compared to multispectral data. Simulation of hyperspectral data with the existing hyperspectral and multispectral

The preparation of accurate LULC is of great importance as it is used in various studies ranging from change detection to geospatial modelling. Literature offers studies comparing different classification algorithms/approaches to prepare LULC maps. However, still there is a lack of studies that can provide a comprehensive analysis on widely used classification algorithms. Hence, in the present study

The present study proposes a novel optimization framework of the reservoir operation in terms of optimizing storage benefits while alleviating downstream environmental impacts. We utilized adaptive neuro fuzzy inference system as the habitat model to assess physical habitat loss at downstream of the reservoir. Furthermore, we applied metaheuristic algorithms including genetic algorithm, particle swarm

The increase of toxic concentration leads environmental pollution. Soil pollution has become the most important problem of current scenario due to the rapid growth of industries. The pollution level can be measured based on the concentration of heavy metals in soil. This work focus on the level of heavy metal concentration in Soil because of water pollution in Tirupur District, Tamilnadu, India, known

Copper is an essential material for electrical conductivity and is a good conductor for heat. The porphyry copper deposits (PCD) are one of the most important resources of copper, where the determination of copper grade is one of the most important issues. The finding complex relationship between copper grade and kind of rocks is a major change for modelers. This study employed the adaptive neuro-fuzzy

During the imaging process, the image will be polluted by noise due to the influence of the earth's atmosphere fog. Noise pollution directly affects the processing of feature extraction, image segmentation, and pattern recognition. Therefore, the purpose of image defogging is to eliminate noise from foggy images to improve image quality. When dealing with uneven fog density in the same image, most

There is a necessity for new methods and technology for several agricultural applications and decision support systems. Technological development at the global, national, and regional level has shown a path for the application of spaceborne remote sensing for agriculture purposes. Remote sensing technology eases to detect areas within the plots for a reliable data supply to analyze the data. Spaceborne

Volunteered geographic information (VGI) is a large and up-to-date data source, which is available to the public easily. VGI enables public participation by leveraging scientific research and ease of data entry. OpenStreetMap (OSM) is one of the most popular examples of a volunteered geographic information project that has turned into a major source as the substitution of geographical data over the

In this study, for the first time in Iran and especially in the northern regions of the country, risk assessment was performed in oil transmission lines. For this purpose, a combined approach based on the analytical hierarchy process (AHP) and fuzzy methods were used. Based on this and in the first stage, eight main criteria of distance from the oil transmission line, distance from faults, distance

The land surface temperature (LST) in permafrost regions in the Northeast permafrost on March 22 (spring), June 24 (summer), September 21 (autumn), and December 24 (winter) in 2019 were retrieved based on the AMSR2 brightness temperature data. An in-depth analysis of the temperature retrieval accuracy between different types of frozen ground, vegetation cover, and during the four seasons of the day

It is crucial to keep an eye on the water levels in reservoirs in order for them to perform at peak, as they are one of the, if not, the most vital part in water resource management. The water stored is essential in providing water supply, generating hydropower as well as preventing overlasting droughts. Thus, efficient forecasting models are essential in overcoming the issues revolving around hydropower

The present paper highlights the classification, change detection and future prediction of Sundarban reserve forest using multi-spectral satellite data over last 43 years (1975–2018). The remote sensing data are classified using back-propagation neural network algorithm which are healthy vegetation, unhealthy vegetation, wet land, and water bodies. The classification result demonstrates that the net

Electromagnetic radiation (EMR) and acoustic emission (AE) are popular geophysical methods for monitoring and providing early warnings about coal rock burst disasters. In the underground mining process, personnel activities and electromechanical equipment produce EMR and AE interference signals that affect the accuracy of EMR and AE monitoring. Currently, these signals are usually identified and filtered

In order to study the dominant seepage channel of the third member of Weizhou formation (Ew3) in Weizhou 12-X oilfield, Weixinan Sag, Beibu Gulf Basin, and tap the potential of remaining oil. The distribution and causes of the anomalously high permeability zones in Weizhou Formation were studied by using conventional core physical property analysis, scanning electron microscope, laser particle size

Water level prediction is vital in developing a sustainable conceptual design of water infrastructures, providing flood and drought control measures, etc. However, due to the complexity and many other inter-related influencing factors within a catchment, water level prediction remains a challenging task. A reliable method that is able to extract the non-linear behaviors of various parameters effectively

We estimated shoreline changes over the last five decades in a part of the southeast coast of India at Cuddalore by using multitemporal satellite images from six different time-windows (i.e. 1972, 1980, 1990, 2000, 2010 and 2020) and the digital shoreline analysis system tool (DSAS 5.0). The linear regression rate and end point rate quantified the maximum erosion at rates of 6.8–7.2 m/year and the

In-depth quantitative studies regarding the nonlinear development laws of a region and the calculation of construction land area (CLA) and weight coefficients of different influencing factors are of great significance for establishing the developmental change model of a region. In this study, a novel calculation method using correlation coefficients was introduced. First, models of three neural network

The grain size distribution (GSD) of a river bed is fundamental information required for studies of fluvial, morphological, and ecological processes. To achieve higher efficiency, numerous efforts have been devoted to developing the techniques of automated grain sizing. These techniques can be categorized as the image-based or topography-based approach according to the input data used. Each category

The performance of multi-GNSS (GPS/Galileo) Single-Frequency Precise Point Positioning (SF-PPP) is studied for both static and kinematic PPP users. In the underlying multi-epoch model, the user ambiguities are assumed constant in time, while the positioning parameters are treated as constant (the static case) and fully unlinked in time (the kinematic case). To demonstrate the quality of single-frequency

Accurate recognition of rock fractures is an important problem in rock engineering because fractures greatly influence the mechanical and hydraulic properties of rock structures. However, existing image segmentation methods for identifying rock fractures tend to be limited to handling only very simple fracture images, despite many real cases containing interfering objects or features such as dark surfaces

The AVIRIS-NG hyperspectral data consists of continuous spectral bands with low bandwidth, Sentinel-2 multispectral image has less number of bands with higher bandwidth. Several studies are carried out to calculate the Normalized Difference Vegetative Index (NDVI) of hyperspectral data. The studies considered a single band in the red and NIR region of hyperspectral data. In this present study, NDVI

Building patterns analysis is critical for landscape evaluation, social analysis, and urban planning. Quantitative evaluation of building patterns is a challenging task because both the complex morphological properties and the spatial similarity relations/degree of the building groups must be considered on a global scale. The existing methods focus on the building pattern indicators (e.g., density)

The visualization systems are proved particularly useful in representing dynamic data and greatly enhance the ability to analyze drilling complexities such severe vibrations during drilling operation which have always been a challenge for the drilling industry as it is considered as the most significant factors limiting the rate of penetration. The current research is directed towards the visualization

In order to study and prevent water hazards in coal mines under thick loose strata, we need to make correct assessments of their water abundance levels based on the limited borehole data. According to the multi-source information composite principle, five main influencing factors of water abundance are chosen, and they are: the aquifer thickness, the thickness ratio between sandy and clayey layers

What the dominant influencing factors are and how changes have occurred over different historical periods in Yellow River Basin are unclear. This study aims to retrieve the annual soil erosion modulus of the Yellow River Basin and utilizes the LMDI model and Geodetector model to identify the dominant driving factors of soil erosion evolution in different historical periods and regions at a pixel scale

Accurate prediction of the water level will help prevent overexploiting groundwater and help control water resources. On the other hand, water level predicting is a highly dynamic and non-linear process dependent on complex factors. Therefore, developing models to predict water levels to optimize water resources management in the reservoir is essential. Thus, this work recommends various supervised

Curiosity of the human mind and the possibility of settlement in other planets to decrease the likelihood of human extinction have acted as a catalyst in the colonization mission of the planet Mars. Exploration, colonization and human missions to the planet are being supported by many public space agencies. Although there are several factors like toxic soil, low gravity, radiation exposures etc. that

In this paper, for the first time, the scour pattern around twin bridge piers was predicted using an optimized hybrid algorithm. The hybrid algorithm (ANFIS-FA) was developed through the combination of the Adaptive Neuro-Fuzzy Inference System (ANFIS) as well as the Firefly algorithm (FA). After that, four ANFIS and ANFIS-FA models were developed by implementing the parameters influencing the scour

The z-test and t-test have been applied for testing the hypothesis that the population mean is equal to the specified mean value. In this paper, we will introduce the modification of the z-test and t-test using the double sampling scheme. We will present the operational process to implement the proposed tests. The power of the proposed test will be calculated for normal distribution, the Weibull distribution

Landslide susceptibility analysis is beneficial information for a wide range of applications, including land use management plans. The present attempt has shed light on an efficient landslide susceptibility mapping framework that involves an adaptive neural-fuzzy inference system (ANFIS), which incorporates three metaheuristic methods including grey wolf optimization (GWO), particle swarm optimization

Urban flood models that use Digital Elevation Models (DEMs) to simulate extent and depth of flood inundation rely on the accuracy of DEMs for predicting flood events. Despite recent advances in developing vegetation corrected DEMs, the effect of building height and density errors in global DEMs in urban areas are still poorly understood, and their correction remains a challenge. In this research we

In the image processing as well as analysis field, Content-Based Satellites Image Retrieval (CBSIR) is a vitalissue. Though there are numerousprevailing Image Retrieval (IR) methods, they still need improvement in the retrieval accuracy along with computational intricacy.Thus, this paper proposed an efficient CBSIR system utilizingWeighted Brownian Motion-based Monarch Butterfly Optimizations(WBMMBO)

Recently, one of the most frequent natural hazards around several regions in the world is the landslide events. The area of Jabal Farasan in the northwest Jeddah of Saudi Arabia suffers from landslide events. The main cause of these events was identified due to the anthropogenic activities represented by mining activities. In this work, different machine learning algorithms (MLA), Random Forest (RF)

The present study uses Landsat satellite images of 1990, 2000 and 2018 to identify the land-use changes. Multilayer perceptron-neural network based land change modelling (LCM) has been applied to model future land-use/land cover (LULC). The prediction model has been validated using simulated and classified LULC maps of 2018 which resulted into an overall accuracy of 88%. The results indicate 389.27%

The risk assessment for the human health of airborne mineral fibres, including asbestos minerals, is a complex task. WebFPTI is a browser-based software written in Python that allows users to calculate an index of toxicity and pathogenicity potential of mineral fibres based on their crystal-chemical-physical properties. WebFPTI can be a powerful tool for both academy and environmental/health institutions

Exploiting the reflected signals from the surface of the Earth to provide information about the reflecting surface is the primary concept of GNSS Interferometric Reflectometry (GNSS-IR). One of the most common usages of GNSS-IR is the estimation of the absolute vertical distance from a GNSS antenna to the reflective surface. In this work, the authors present a developed MATLAB-based GNSS software,

The Atmospheric Radiation Measurement (ARM) user facility is a US Department of Energy Office of Science user facility that is managed and operated through a collaborative effort led by nine US Department of Energy national laboratories. The ARM Data Center, located at Oak Ridge National Laboratory, is responsible for the timely collection, processing, and delivery of data products to the scientific

In this study, the magnitude of an earthquake in the East Anatolian Fault (EAF) of Turkey are predicted based on previous earthquakes whose magnitudes are four or more by two-time series methods, namely autoregressive integrated moving average (ARIMA) and singular spectrum analysis (SSA). These methods are quite new in seismology despite being successful techniques in other branches of science. We

Urban Structure Types (USTs) stand for areas with homogeneous appearance over the urban matrix. The use of spatial metrics rises as a convenient alternative to quantify the homogeneity of areas on a specific scale. Remote sensing imagery is largely used to assess and study the urban environment, and its classification is a way to recreate the Earth’s surface digitally, both natural and urban spaces

The present paper reports a rigorous study of the Indian Summer Monsoon Rainfall (ISMR) through Multifractal Detrended Fluctuation Analysis (MF-DFA). It has been observed that the ISMR is characterized by multifractality and Hurst Exponent above 0.5. It has been interpreted from the Hurst Exponent value that the ISMR time series is characterized by long term positive auto-correlation. Studying the

Instantaneous complex attributes that rely on conventional Hilbert transformation are normally susceptible to random noise and abrupt frequency variations in seismic signals. Moreover, conventional filtering methods diminish the spectral bandwidth needed to suppress noise when estimating seismic attributes. This has a significant impact on the resolution in thin-bed layers, which demand wide-band data

We present context-aware benchmarking and performance engineering of a mature TByte-scale air quality database system which was created by the Tropospheric Ozone Assessment Report (TOAR) and contains one of the world’s largest collections of near-surface air quality measurements. A special feature of our data service https://join.fz-juelich.de is on-demand processing of several air quality metrics

The term super-resolution (SR) refers to the applications of enhancing the resolution of an image from low-resolution (LR) to high-resolution (HR). However, for compression purposes, we can intentionally down-sample the image during encoding and then up-sample it with a super-resolution technique at the decoder. Integrating this processing in a compression scheme will allow us to perform improvements

Reasonable classification of aurora is of great significance to the study of the generation mechanism of aurora and the dynamic process of the magnetosphere boundary layer. Previous aurora classification studies, both manual and automatic, rely on experts’ visual inspection and manual labeling of part or all of the data. However, there is currently no consensus on aurora classification schemes. In

Offshore wind energy resources are not fully exploited renewable energy resources until now and could play a crucial role in mitigating the impacts of climate change by the generation of renewable electricity. Planning processes such as technical, social, environmental, various agents, and political concerns are necessary for the development of offshore wind energy projects. The objective of this study

The influence of the detection direction on the quality of spectral data was not taken into account, which is catastrophic for some samples where the reflectivity direction was very different. To explore the directional characteristics of mixed pixels reflectivity, we used an ASD FieldSpec3 spectroradiometer to carry out multi-angle spectral measurement experiments in the laboratory, and the direction

The paper reports a study on the air quality over Kolkata, India during the transition period from post-monsoon to winter. A fuzzy binary relation based approach is implemented to O3, N O2 and P M2 5 and the overall air quality index (AQI). Individual pollutants have been converted to fuzzy sets based on their concentrations as elements of the universe of discourse with appropriate fuzzy membership

The present paper aims to determine the best spectral index for extraction of surface water bodies and considerable variation in water surface area during the period between 1990 and 2018. Five spectral indices are tested using Landsat series (1990, 2000, 2009 and 2018) and their performance in delineating surface water are assessed. The results of each algorithm have been matched and verified by Pearson

Knowledge of detailed urban land-use patterns is essential in urban management, economic analysis, and policy-making aimed at sustainable urban development. To extract this information, previous studies relied on either the physical features extracted from remote sensing images or human activity patterns analyzed from social sensing data, but seldom on both of them. In this study, we proposed a framework