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

Amplitude, an important electromagnetic wave attribute, is considered as a useful parameter to describe the energy attenuation of electromagnetic wave. In this study, SIR-3000 Radar Equipment was employed to investigate the amplitude of electromagnetic wave in medium sandstone with different water content and depth. Results suggest that, with same water content, the decreasing of electromagnetic wave

In this paper a new method of image smoothing and its applications in the field of remote sensing are presented. This method is based on the minimization of the iterated Laplace operator of an arbitrary degree in the Cartesian coordinate system. Using the method of finite differences, a linear combination is derived, which represents the solution of the minimization problem. For the special case of

In the past three-dimensional geological modeling process, only vertical geological data, i.e. borehole or profile drawn from borehole, was used as the modeling data source. However, the plane geological map either does not participate in the modeling at all, or only serves as a reference data in the modeling process, and its role is not fully played. In view of the appeal, this paper puts forward

Change detection (CD) is one of the most important application in remote sensing domain. The difference image (DI) generated by traditional change detection methods are sensitive to several factors, such as atmospheric condition changes, illumination variations, sensor calibration, and speckle noise, greatly affecting the detection performance. To avoid the aforementioned problem, in this paper, a

River canyons mapping plays an important role in water conservation project construction, tourism resource development, and analysis of fluvial processes. However, the extraction of river canyons via manual interpretation or semi-automatic methods is inefficient and expensive, especially at large spatial scales. Therefore, the objective of this study is to propose a novel method for automatic extraction

Shadows, in aerial and satellite high-resolution images of earth, are a common phenomenon. Shadow causes false-color image, loss of information in the image, and false image segmentation. This leads to incorrect outputs of many image processing applications. In this paper, we address the problem of shadow detection in aerial high-resolution images of earth. The paper presents a proposed method that

On September 6, 2018, an Mw 6.6 earthquake occurred in Hokkaido, Japan, triggering massive landslides. Based on the 0.3 m-resolution Pleiades-1 satellite image on the Google Earth platform, we constructed an updated co-seismic landslide inventory for this event, which permitted to map 12,586 landslides. These slope failures are featured by a large number, wide spread, large scales, and local dense

After a large-scale earthquake, it induces a large number of building collapses and casualties, especially in urban areas. In order to make prevention and response plans before earthquakes, various earthquake loss estimation systems have been developed. The commonly used units of analysis in those systems include grid and village (or administrative district). However, grids are not consistent with

Since the 1990s, the increase in the number of publications about spatial analysis has been exceptional, and spatial analysis has been incorporated into numerous research areas. However, the magnitude of this expansion can cause information overload for researchers since it hinders the selection of the most relevant texts and authors. To assess this scenario, a bibliometric analysis was performed of

The authors of the above published paper were notified by one of the authors referenced in their paper

Precipitation is one of the key components in the water cycle. To analyse the changes in precipitation at a specific location, it is necessary to identify the distribution that best fits the precipitation data. For this purpose, three distributions i.e. generalized extreme value (GEV), generalized Pareto (GPD), and generalized logistic (GLO) were fitted to the annual precipitation data collected from

Viewshed analysis based on the regular grid digital elevation model (DEM) is one of the basic functions of geographic information systems. Traditional viewshed analysis algorithms are mainly carried out in a geospatial coordinate system, that create complexities when it is necessary to accurately express a perspective relationship. Moreover, it can only reduce the amount of calculation by using approximation

One of the most dynamic components of the environment is land use land cover (LULC), which have been changing remarkably since after the industrial revolution at various scales. Frequent monitoring and quantifying LULC change dynamics provide a better understanding of the function and health of ecosystems. This study aimed at modelling the future changes of LULC for the Erbil governorate in the Kurdistan

Land change models are amongst the most widely developed tools for spatial decision support. Despite this progress, only a few models have been created thus far that simulate urban growth that incorporate two important aspects of uncertainty inherent to land use dynamics: fuzziness and roughness. Combining fuzziness and roughness into models will enhance the use of these tools for decision support

In recent years, with the rapid development of urbanization, the urban public emergency management faces increasing challenges, and the number of fire incidents has increased largely. For mitigating injury risk and reducing property loss, fire station locations need to be optimized to provide efficient fire emergency services. However, the locations of fire facilities in China are mainly determined

A number of methods are available for topographic correction of remote sensing data, and various approaches have been proposed for the evaluation of topographic correction effects. However, few studies have evaluated the topographic correction effects for images obtained under all possible sun elevation conditions. This study employed three correction methods, namely, Statistical-Empirical (SE), C-correction

Internet of Underwater Things (IoUTs) is completely embraced by acoustic sensor nodes that are commonly battery consumption. The sensor’s battery life is restricted and it is problematic while it needs to recharge. Moreover, these kinds of underwater sensor nodes may form the cluster to store the huge amount of energy. The cluster head formation is the main problem that the cluster head needs to use

Flood occurs as a result of high intensity and long-term rainfalls accompanied by snowmelt which flow out of the main river channel onto the flood prone areas and damage the buildings, roads, and facilities and cause life losses. This study aims to implement extreme gradient boosting (EGB) method for the first time in flood susceptibility modelling and compare its performance with three advanced benchmark

Lithology identification of geological beds in the subsurface is fundamental in reservoir characterization. Recently, automated log analysis has an increasing demand in reservoir research and the oil industry. In this context, Machine Learning (ML) techniques arise as a surrogate model to provide lithology identification in a fast way. However, to achieve suitable performance, ML techniques require

The Acknowledgments section of this article has been corrected.

We analyzed an extended time series of Schumann Resonance recordings with two multi-parametric statistical methods, the generalized linear Logistic Regression—LogReg and the non-linear Random Forest—RF, in order to test their potential for earthquake prediction within a narrow time-space-magnitude window of 48 h, 250 km from our observing site, and events higher than magnitude 4 of the Richter scale

Field data collection and geospatial map generation are critical aspects in different fields such as road asset management, urban planning, and geospatial applications. However, one of the primary impediments to data collection is the availability of spatial and attribute data. This issue is aggravated by the high cost of conventional data collection and data processing methods and by the lack of geospatial

With the explosive growth of geological data, considerable researches are focused on accurately retrieving specific information from massive data and fully exploiting the potential knowledge and information in unstructured data. Currently, the researches on unstructured content retrieval mostly ignore the association of semantics and knowledge or only consider the association of a singular granularity

Reasonable evaluation of the comprehensive effect of coordinated coal-water development is necessary for the sustainable development of ecologically vulnerable area. Taken Nalinhe mining area as the research area and focused on the thick coal seam mining, an evaluation index system of the comprehensive effect of coordinated coal -water development was proposed. The analytic hierarchy process modified

This paper addresses the problem of feature selection aiming to improve a flood forecasting model. The proposed model is carried out through a case study that uses 18 different time series of thirty-five years of hydrological data, forecasting the level of the Xingu River, in the Amazon rainforest in Brazil. We employ a Genetic Algorithm for the task of feature selection and exploit several different

This paper deals with the online offset detection in GPS time series recorded in volcanic areas. The interest for this problem lies in the fact that an offset can indicate the opening of eruptive fissures. A Change Point Detection algorithm is applied to carry out, in an online framework, the offset detection. Experimental results show that the algorithm is able to recognize the offset generated by

Crop classification based on object-based image analysis (OBIA) is increasingly reported. However, it is still challenging to produce high-quality crop type maps by using recent techniques. This article introduces a new object-based crop classification algorithm which contains 4 steps. First, a random forest (RF) classifier is trained by using the initial training set, which tends to have a relatively

Since the beginning of space exploration, the galaxy classification has been a vexing problem that has always muddled the astrophysicists. A number of techniques have proven their remarkable utility in the classification of galaxies, however, upon analysis, these methods revealed certain inefficiencies that cannot be overlooked. The traditional classification of galaxies in the universe contains a

NASA’s Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) carries a laser altimeter that fires 10,000 pulses per second towards Earth and records the travel time of individual photons to measure the elevation of the surface below. The volume of data produced by ICESat-2, nearly a TB per day, presents significant challenges for users wishing to efficiently explore the dataset. NASA’s National Snow

From the practice of tourism industry, many scenic spots emphasize emergency rescue and ignore risk prevention in safety management.From the perspective of research, a large number of literatures focus on the emergency management of scenic spots, and lack the concept and method of systematic risk management. This research puts forward the natural disaster risk assessment method in tourist area by the

A method to forecast air temperature TA in Elqui Valley (south of Chile’s Atacama Desert) using an artificial neural network (ANN) and meteorological time series data relevant to this zone, is proposed. This zone has one of the most sensitive climates in South America due to the influence of phenomena such as El Niño/La Niña, the Southeast Pacific Subtropical Anticyclone, Humboldt Current, and Madden–Julian

2D underground models that reflect the physical, mechanical and structural properties of the geological units below the ground are called geotechnical cross-sections. In order to visualize these cross-sections, geotechnical engineers record the measurements obtained from vertical electrical sounding, seismic refraction or drilling methods. The visualization process is done by hand and it may vary depending

A large number of georeferenced quantitative data about rock and geoscience surveys are buried in geological documents and remain unused. Data analytics and information extraction offer opportunities to use this data for improved understanding of ore forming processes and to enhance our knowledge. Extracting spatiotemporal and semantic information from a set of geological documents enables us to develop

The Curie point-depth, frequently related to the depth to the bottom of the magnetic source, is widely employed as an estimator of temperature at depth when borehole temperature data are not available. The Curie point-depth is calculated using the spectral analysis of the magnetic data derived from aeromagnetic or satellite surveys. In this paper, MATLAB user-friendly GUI are constructed to calculate

In this article we develop a new method to grid passive microwave data in the presence of spatial correlation patterns. Our proposal combines a Tychonov inverse method with a generalized cross validation procedure to grid the observations over a discrete retrieval grid. To build this grid, the study region is partitioned into objects following an object-based image analysis procedure. Then, this partition

Modeling the rate of penetration (ROP) plays a fundamental role in drilling optimization since the achievement of an optimum ROP can drastically reduce the overall cost of drilling activities. Evolved Extreme learning machine (ELM) with the evolutionary algorithms and multi-layer perceptron with Levenberg-Marquardt training algorithm (MLP-LMA) were proposed in this study to predict ROP. This paper

The accurate expression of terrain morphology is the essence of the urban terrain model construction. As the skeleton of urban terrain, urban road has special geometric and semantic characteristics. The road is a strip-shaped feature, which is flat in the horizontal direction and gently undulating in the vertical direction, and the roads are interlinked and connected. This research takes Jianye District

The purpose of this study was to investigate improve the utilization rate of water resources and using multi-objective optimization algorithms to prediction water demand for the next 30 years, then the swarm intelligence approach was used to analysis for the development and utilization of water resources. The results obtained in this study include built a group optimization intelligent algorithm and

Laser-induced breakdown spectroscopy (LIBS) is a powerful tool for qualitative analysis of chemical composition on planetary surface. Specifically, the quantitative compositional analysis method is a significant challenge for LIBS instrument onboard the Mars Science Laboratory (MSL) rover Curiosity ChemCam. Partial Least Squares (PLS) sub-model strategy is one of the outstanding multivariate analysis

3D geological modeling data can only be measured rarely or indirectly, as it is necessary to interpolate the sparse and uneven geological data in the study area. Given the problems in the interpolation of data from different sources, we have introduced stratum interpolation and visualization technology based on the moving least squares (MLS) method and Poisson surface reconstruction method. The MLS

This study is aimed to elucidate individual fault response and peculiar earthquake characteristics in complex seismotectonic environment of southern Pakistan (Balochistan, Sindh and frontal offshore areas). The southern Pakistan is a seismic-mélange wherein earthquake prone sources are diversified and closely associated with active plate margins. The spatial patterns of seismicity are significant in

We consider the challenging task of evaluating the commercial viability of hydrocarbon prospects based on limited information, and in limited time. We investigate purely data-driven approaches to predicting key reservoir parameters and obtain a negative result: the information that is typically available for prospect evaluation and is suitable for data-based methods, cannot be used for the required

In recent days, people in remote area suffer a lot due to variety of natural calamities such as flooding, earthquake and so on. It has been noted that people used to stay in top portions of their house when there is a flooding issue. Hence, it is very difficult for the rescue team to identify the location of a person by looking at the parts of a person such as hands, legs and partial image of a face

In this paper, we present the Pipeline for Observational Data Processing, Analysis, and Collaboration (PODPAC) software. PODPAC is an open-source Python library designed to enable widespread exploitation of NASA earth science data by enabling multi-scale and multi-windowed access, exploration, and integration of available earth science datasets to support analysis and analytics; automatic accounting

The data-driven index overlay technique is an amended version of the conventional index overlay method, which has been utilized for mineral potential modeling (MPM) in brown-fields exploration, whereby a data-driven way is utilized to determine the relative significance of both individual evidence maps and evidential values. Although this method evades exploration bias in the conventional index overlay