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

Feed Forward Neural Network (FFNN), Adaptive Neuro-fuzzy Inference System (ANFIS), and Support Vector Regression (SVR) were applied for rainfall-runoff modeling of the Gilgel Abay catchment, Blue Nile basin, Ethiopia. Daily precipitations from satellite sources and rain gauge stations and outlet discharge were used. The dominant inputs were selected by non-linear sensitivity analysis. The study was

One of the adverse effects of population growth and urbanization in developing countries is air pollution. Due to which more than 4.2 million deaths occur every year. Therefore, prediction of air quality is a subject worth in-depth research and has received substantial interest in the recent years from academic units and the government. Feature selection methods are applied before prediction to identify

A novel and effective change detection method based on manifold regularized joint non-negative matrix factorization (MJNMF) framework is proposed in this paper, which detects the changes that occurred in multi-temporal remote sensing images. Most change detection methods, including dictionary learning, principal component analysis (PCA), etc., do not consider the non-negativity among image pixels.

Alluvial fans are among the principal geomorphological features that have an influence on the development of human societies, particularly in arid regions. In view of the salience of these triangular-shaped deposits to environmental management, an accurate mapping of alluvial fans within a specific region could prove significantly advantageous. This study proposes a method for semi-automated detection

This paper deals with the classification of volcanic activity into three classes, referred to as Quite, Strombolian and Paroxysm. The main purpose is to give a measure of the reliability with which such a classification, typically carried out by experts, can be performed by Machine Learning algorithms, by using the volcanic tremor as a feature. Both supervised and unsupervised methods are considered

Tight oil reservoirs are key research targets of petroleum geological exploration. Due to their strong heterogeneity, reservoir classification is fuzzy and efficiency is low, which affects reservoir evaluation accuracy. This study aims to improve the accuracy of the evaluation of microscopic pore throats of tight reservoir. Tight oil reservoir is classified on the basis of microscopic pore-throat grading

Monitoring urban land through satellite images has rapidly developed with the advent of modern technologies, and the increasing number of satellites plays a contributing role. While optical images have a high capability in urban monitoring, they still have some limitations, including their dependence on climatic conditions and spectral information, which lead to difficulty in making a distinction between

Filling damaged pixels in satellite images is a key task present in many Remote Sensing applications. As a representative example of image restoration issue, we can refer to the failure of the Scan Line Corrector (SLC) on board the Landsat Enhanced Thematic Mapper Plus (ETM +) sensor, in which 22% of the scanned pixels in the SLC-off images were missed, thus creating unexpected stipe-type gaps in the

Groundwater quality is affected by various indexes, and the influence of each index on groundwater quality is fuzzy. Therefore, adopting a reasonable evaluation method can make the groundwater quality evaluation more accurate. Although fuzzy comprehensive evaluation method has great advantages in analyzing fuzzy problems, it has shortcomings in solving problems like weight calculation. The fuzzy comprehensive

Distance anomaly factors (DAFs) were defined for each cell of the unit cell population in a study area to represent mineral potential of the cell. A DAF of a cell is a formula for the total distance from the cell to all other cells in the study area. The distance between two cells can be expressed as the Manhattan distance, Canberra distance, Euclidean distance, and kernel Euclidean distance. The kernels

Multi-Input Multi-Output (MIMO) telecommunication systems with Orthogonal Frequency Division Modulation (OFDM) scheme support high rate data exchange which can be efficiently applied to the fast-growing networks of Internet of Things (IoT). In the case of Underwater IoT (UIoT) where the strength of electromagnetic waves rapidly falls off, the MIMO network can be effectively implemented by substitute

One of the most challenging topics in analyzing multi-dimensional geo-spatial data such as geophysical data-sets is detecting outlier data. The issue mainly originates from the difficulty in describing “normality” or “abnormality” due to the complexity of the relationships between the data elements. Considerable number of methods have been proposed and applied for detecting outliers whether they are

As one of the most critical points of Iran, Lake Urmia has always been subjected to ecosystem changes due to severe water level drops. Many basins serve to feed the lake, e.g. the Shaharchay River basin, located west of the lake. In this paper, a new learning machine named “Weighted Regularization Extreme Learning Machine (WRELM)” is integrated with the Wavelet Transform (WT) (W-WRELM) to predict

Total organic carbon content (TOC) is an important parameter for shale gas resource evaluation. Among the existing TOC prediction methods, ΔlgR method is the most widely used. There are two main problems in this method: 1) assuming a linear relationship between ΔlgR and TOC; 2) manually determining the baseline and introducing human error. Due to the frequent alternating changes in the sedimentary

The spatial interpolation of meteorological data have important applications in ecological environment monitoring, such as soil erosion, ecological vulnerability evaluation. However, there are significant differences in the interpolation accuracy of climatic elements under different topographic and geomorphic conditions. Based on data of 810 meteorological stations across the country, five typical

The weight percent SiO2 of rocks is a basic parameter for the classification of geological bodies and the analysis of genetic evolution, therefore, lots of rocks are collected in the field and analyzed to obtain their weight percent SiO2 in the laboratory. This method has always been one of the main working means for basic geological research and mineral exploration. Aiming at the disadvantages of

The Indian plate’s western boundary is extremely tilted towards the direction of convergence between Asia and India signifying an exceptional example of massive scale oblique continent-continent collision. This transform boundary motion is sinistral in nature and Digital Elevation Model (DEM) based geomorphometry permits the investigation of 3-D characteristics of the regional topography. This technique

The importance of land surface temperature (LST) is increasingly recognized, and various methodologies have been proposed for the retrieval of LST using space-borne thermal infrared data. However, the selection of LST retrieval from Thermal Infrared Sensor (TIRS) of Landsat-8 based on different methods and the readily available MODIS LST products is still a challenging topic for local and global environmental

Quantifying the structure and composition of quasi-circular vegetation patches (QVPs) is key in identifying ecosystem function, which will help create a cost-effective nature-based solution for restoring the degraded wetland ecosystem in the Yellow River Delta (YRD), China. However, research on mapping plant communities of QVPs using remotely sensed data has not been conducted. In this study, we found

Today, satellite altimetry is capable of observing the instantaneous sea level and is regarded as a standard tool in the study of waters level variations on both regional and global scales. In this research, we have introduced a software package under MATLAB called ATSAT, which is used to process the satellite altimetry data. ATSAT is able to process the observations of five satellites, namely Jason-1

This study sets out to simulate various hydrological responses to climate change. The semi-distributed hydrologic model of the Soil and Water Assessment Tool, SWAT, was used to simulate different parts of the hydrological cycles. The comprehensive assessment of the effect of climate change on runoff, crop yield, and water balance in Siminehroud and Zarrinehroud watersheds is the novelty of this research

Image well logging is an intuitive approach to identify fractures of reservoir for oil and gas exploration. However, these logging images are rare and nonannotated. A method of unsupervised segmentation network based on convolutional neural network is adopted to automatically extract pixels pertaining to fracture information in this paper. We propose a modified model to accomplish domain adaptation

In areas covered by vegetation, large-scale topographic mapping by UAV oblique photogrammetry normally obtain elevations from vegetation instead of ground points, resulting in lower elevation precision. This study developed an precision improvement grid algorithm and associated SOP for large-scale topographic surveying and mapping in vegetation coverage areas by UAV oblique photogrammetry. The procedures

The main objective of the article is to propose an advanced architecture and workflow based on Apache Hadoop and Apache Spark big data platforms. The primary purpose of the presented architecture is collecting, storing, processing, and analysing intensive data from social media streams. This paper presents how the proposed architecture and data workflow can be applied to analyse Tweets with a specific

This study appraises different types of conventional (e.g., GRNN, RBNN, & MLPNN) and modern neural networks (e.g., integrative, inclusive, hybrid, & recurrent) in forecasting daily flow in the Thames River located in the United Kingdom. The models are mathematically, statistically, and diagnostically compared based on the forecasted results for ten different time-series assortments. The results indicate

Image transformation techniques such as Principal Component Analysis, Minimum Noise Fraction and Independent Component Analysis were used for extracting information from the satellite image in various fields, but its application in landform mapping seems to be very less. The objective of the study is to demonstrate the viability of less explored image transformation techniques for delineating coastal

Over the years, a large amount of temporal data needs to be shared and exchanged on the Web. Resource Description Framework (RDF) has been widely accepted and has rapidly gained popularity to al RDF) model as mentioned in represent and share data in many application domains (e.g., the Data of Web, Linked Data, and Knowledge Graph). Accordingly, efficient management of temporal data based on RDF is

A Free Windows software has been programmed by Visual Basic-2012 under the Windows platform. The program allows users to calculate the zircon crystallization temperature. The designed program employs a simple scoring algorithm to measure the zircon crystallization temperature based on the function of titanium-in-zircon thermometry (Watson and Harrison, 2005). During data entry, the input data option

Borehole logs are important geospatial data for understanding subsurface geological and geotechnical conditions. Recently, many borehole logs in urban areas have been open to the public on the Internet in machine-readable file format. However, a few simple methods allow us to construct a voxel model of geological and geotechnical characteristics with high objectivity of the modeling process. Our work

The present study aims to exploit the thermal inertia model to assess the shallow groundwater level distribution, as an attempt to address agricultural water shortage and ecological degradation in arid and semi-arid regions. Apparent thermal inertia (ATI) model is one of the most commonly used and successfully implemented models, whereas in some cases, the scales of the results achieved on different

Zigong City, Sichuan Province, is a typical hilly area, and relatively rough land leveling was carried out in the pre-development of its aviation industrial park, which has caused some damage to the ecological environment. In this study, the Delphi method was used to determine the degree of influence of four ecological factors, namely elevation, slope, woodland and surface water, on the site. Based

Recently, there has been a great demand for 3D building models in several applications including cartography and planning applications in urban areas. This led to the development of automated algorithms to extract such models since they reduce the time and cost when compared to manually onscreen digitizing. Most algorithms are built to solve the proposed problem from either LiDAR datasets or aerial

Fractal dimension is a parameter that quantitatively describes the complexity of fractal set. In order to understand the spatial variation characteristics of soil fractal dimension and its influencing factors, different geomorphic units in a typical basin of the North China plain were selected for sampling. And the grain size distribution of 180 soil samples were measured by laser diffraction. Fractal

This study firstly applies ant colony algorithm to optimize the classification index formulas and comprehensive index formulas related to the environmental benefits of ecological mining areas and builds an environmental benefits evaluation model. Then taking the ecological mining area of China Pingmei Shenma Energy Chemical Group as an example, the simulation software MATLAB is used to evaluate the

Building detection from the satellite image is a computer vision, Photogrammetry, and remote sensing task that has significant importance in geographical information system (GIS) based applications. In this study, a novel framework is developed for the automatic detection of different types of buildings in the complex environment of the satellite images. The framework consists of fuzzy-based pre-segmentation

An investigation is presented in this paper to predict Groundwater Level (GWL) by Inclusive Multiple Modelling (IMM) practices, introduced recently by the authors, as a strategy by organising multiple models at three hierarchical levels: Artificial Neural Networks (ANNs), Sugeno Fuzzy Logic (SFL), Neuro-Fuzzy (NF), Support Vector Machine (SVM) and Gene Expression Programming (GEP). The IMM novelty

Rockfall is a natural hazard in mountainous areas not to be underestimated. Mass activities differing in rock volume may cause considerable economic damage. Accomplishing qualitative appraisal of high-potential zones for rockfall is a first step towards implementing mitigation strategies. Nowadays, Geographical Information Systems (GIS) are the state-of-the-art tool for a fast and economic approach

One of the most important topics in operational applications of precipitation forecasts is their improvement by bias correction methods. In this study, the ensemble precipitation forecasts of six numerical models from the TIGGE (THORPEX Interactive Grand Global Ensemble) database, associated with four basins in Iran for 2008–2018, were extracted and bias-corrected by the Quantile Mapping (QM) and Random

Metadata descriptions are typically monolithic data structures and their denormalized, text-based nature yields shortcomings such as inconsistencies and heterogeneities. Moreover, fluidity of research environments, coupled with single-tenancy of metadata descriptions, impedes enforcing authority on the related datasets effectively. We propose a novel paradigm for metadata articulation, delegation,

In arid and semi-arid, due to the lack of surface water, groundwater plays key role in people survival. Therefore, assessing groundwater potential zones is vital to conserve and manage this resource properly. The main object of this study was to compare two methods of AHP and entropy for delineating groundwater potential zone in arid region of Iran. For this regard, withdraw in groundwater level in

This paper presents the construction of prediction intervals (PIs) associated with the Emotional Artificial Neural Network (EANN) via the Lower Upper Bound Estimation method (LUBE) and the classic Bootstrap method for the Suspended Sediment Load (SSL) modeling. As point prediction conveys no information about modeling reliability, PIs were applied. The constructed PIs via the EANN were also compared

Different kinds of observations feature different strengths, e.g. visible-infrared imagery for clouds and radar for precipitation, and, when integrated, better constrain scientific models and hypotheses. Even critical, fundamental operations such as cross-calibrations of related sensors operating on different platforms or orbits, e.g. spacecraft and aircraft, are integrative analyses. The great variety

Since sediment concentration is an effective factor on increasing debris flood’s peak flow and damages from floods, developing new models to predict the sediment concentration of debris floods has crucial importance. In this study, a hybrid SVR-PSO model was proposed to predict the concentration of sediment in typical and debris floods, and it was examined in three basins located in Gilan, Mazandaran

The Prediction of the reservoir characteristics from seismic amplitude data is a main challenge. Especially in the Nile Delta Basin, where the subsurface geology is complex and the reservoirs are highly heterogeneous. Modern seismic reservoir characterization methodologies are spanning around attributes analysis, deterministic and stochastic inversion methods, Amplitude Variation with Offset (AVO)

GeoGateway (http://geo-gateway.org) is a web-based interface for analysis and modeling of geodetic imaging data and to support response to related disasters. Geodetic imaging data product currently supported by GeoGateway include Global Navigation Satellite System (GNSS) daily position time series and derived velocities and displacements and airborne Interferometric Synthetic Aperture Radar (InSAR)

In China, the upstream Hangjing River (HJR) is an important surface water source for the South-to-North Water Transfer Project (SNWTP) because it has abundant water and better quality, which plays a crucial part in national drinking water safety and ecological sustainable development in China. This work was aimed at comprehensively studying the pollution status of heavy metals in sediments upstream

Galileo navigation system has significantly expanded satellite constellation over the last few years and now serves with 22 satellites in three orbital planes. The development of the Galileo is not only limited to the number of satellites in the space segment, but also the quality of the IGS MGEX products produced by different Analysis Centers has increased gradually and brought up the topic of investigation

The current research reports a univariate analysis of 2 important climatological parameters surface air temperature and rainfall over North East India over annual scale characterized by various degrees of non-linearity. An Autocorrelation study reveals that although the surface air temperature is characterized by an approximate sinusoidal pattern, the rainfall has no apparent pattern. As both the time

Land cover classification is essential for environmental monitoring, sustainable development goals assessment and other fields. Traditionally, it often takes much time and labor costs to copy and pre-process remote sensing images for performing land cover classification with desktop software, which must be installed and licensed. Google Earth Engine (GEE), as a cloud computing platform, provides a

Access to information about the occurrence of past geological events and their chronology is crucial to cognize the evolution of subsurface structures. We refer to such tasks as Event Sequence Interpretation (ESI). The sequence of events describes the process of structural evolution and is the basis for structural interpretation and structural geological modeling. ESI has not been highly automated

Obtaining surface albedo of high accuracy and analyzing spatial and temporal characteristics are essential for detecting change mechanism and influencing factors of surface albedo in deserts. Surface albedo from the Operational Land Imager (OLI) was assimilated into black-sky short-wave albedo (BSA) with an ensemble Kalman filter (EnKF) algorithm, to retrieve the surface albedo of high accuracy in

Regional economic development describes the total social and economic activities in a given time and space. An objective understanding of the real regional economy is beneficial for healthy, sustainable societal development. Generally speaking, the understanding of the regional economy is mainly based on social surveying, which incurs time and energy costs and lacks objectivity. Therefore, this study

The effect of volume of shale different calculation methods on reservoir petrophysical parameters was analytically modelled and evaluated using ‘PETRARCAL.’ It is essential to characterize the hydrocarbon reservoir as precisely as possible in other to calculate petrophysical properties of interest in the region and to decide the most effective way of recovering as much of the hydrocarbon as economically

A 3D geological structural model is an approximation of an actual geological phenomenon. Various uncertainty factors in modeling reduce the accuracy of the model; hence, it is necessary to assess the uncertainty of the model. To ensure the credibility of an uncertainty assessment, the comprehensive impacts of multi-source uncertainties should be considered. We propose a method to assess the comprehensive

A travel or transport path reflects the settlement pattern and the spread of civilization. Travel simulations of the pre-Qin period of the Central Plains of China can deepen our understanding of the origin and development of Chinese civilization. Here, based on the idea of swarm intelligence, an ant colony optimization algorithm based on gradient descent and variable-neighborhood search (GD-VNSACO)

Forest fires are significant catastrophic events that affect the landscape and vegetation in forested lands. They cause loss of biodiversity, land degradation & ecological imbalance. As the forest fires cause extreme damage to the habitat, it is of utmost necessity to assess the impact of fire on canopy/vegetation. Post-fire assessment is an essential element for finding the effects of fire on vegetation

Most previous studies of homegardens have used labor-intensive boots-on-the-ground plant surveys, owner questionnaires, and interviews, limiting them to at most a few hundred homegardens. We show that automated analysis of publicly available imagery can enable surveys of much greater scale that can augment these traditional data sources. Specifically, we demonstrate the feasibility of using the high-resolution