An integrated approach of morphometric and litho-structural studies for flood risk assessment of Ala River Basin (ARB) in Akure city, southwestern Nigeria aided by geospatial techniques was carried out. The Ala River Basin comprises of four sub-basins covering a total area of 427km2 with fourth stream order of dendritic and sub-trellis drainage patterns. The values obtained for the morphometric features

When 3D modeling of the geological body is carried out based on the section, problems such as unable to close the structural plane, slow rendering speed of the model and uneven and long and narrow section triangle network will occur due to the situation of super near point or too dense fold point. To solve the appealing problem, this paper proposes a section thinning-densification method based on the

The stability of rock slopes is a difficult problem in the field of geotechnical and geological engineering. Less than 20% of all landslides are predictable each year, so a simple, fast, reliable and low-cost method to predict the stability of slopes is urgently needed. This study investigates a new regularized online sequential extreme learning machine, incorporated with the variable forgetting factor

Spartina alterniflora is the main invasive vegetation in wetland ecosystems, and information on its chlorophyll content is important data for quantitative research on the key ecological functions of wetland ecosystems. The Dongtan wetland of the Yangtze River estuary was used as the experimental research area, and the artificial cultivation field of Eupatorium was taken as the research object. To prevent

Predictive mapping of environment is an important means for environment assessment and management. The selection of predictor variables (or environmental covariates) is the first and key step in predictive mapping. A number of machine learning and statistical models have been developed to select what and how many environmental covariates in a wide range of predictive mapping. Nevertheless, those models

Earth observation data have revolutionized Earth science and significantly enhanced the ability to forecast weather, climate and natural hazards. The storage format of the majority of Earth observation data can be classified into swath, grid or point structures. Earth science studies frequently involve resampling between swath, grid and point data when combining measurements from multiple instruments

This study was performed along the shorelines of Lake Salda in Turkey during the elapsed period from 1975 to 2019 in order to detect shoreline changes. Within this framework, geographic information system, digital shoreline analysis system, Modified Normalized Difference Water Index, and multi-temporal satellite images were utilized. The measurement of shoreline displacement was mainly divided into

Possible sunshine duration (PSD) determines the solar energy received by the surface of Earth. The objective of this research is to explore the spatial structure of PSD which is closely related to slope and PSD. We chose 40 sample areas representing diversified landforms in China and then computed the PSD by using the digital elevation models (DEMs) with a resolution of 30 m for the sample areas. We

Change Detection from remote sensing images is one of the most challenging and controversial topics among researchers in this field. Given the variety of types of surveyed areas and the data used, it cannot be claimed that there is a comprehensive way to identify different types of remote sensing data.This research aims to represent three robust and novel cost functions based on improving conventional

Soil moisture (SM) is a key variable in hydrological processes, bio-ecological processes, and biogeochemical processes. Long-term observations of soil moisture over large areas are critical to research on flooding and drought monitoring, water resource management, and crop yield forecasts. In this paper, Fengyun (FY3B and FY3C) SM products, Japan Aerospace Exploration Agency (JAXA) SM products from

In Earth science, original data elaboration is often very complex and the results are generally provided in the form of (computer-made) maps, a qualitative representation. The aim of this paper is to illustrate a graphic method of analysis that allows the reverse: tracing back, on scientific bases, quantitative data from computer-mapped information, by using widely-available graphic tools, including

Earth Observation (EO) data play an important role in our society today, but there is still tremendous opportunity to improve how these data are used to affect change. In this paper, we provide guidance to help data providers and intermediaries within the EO value chain (from data to applications) increase the societal value of the EO data, information, and data products that they work with. We first

In the big data era, high-resolution raster-based geocomputation has been widely employed in geospatial studies. The algorithms used in local map algebra operations are data-intensive and require a large memory space and massive computing power. Simply employing distributed computing framework such as Hadoop to serve such applications incurs storage and performance issues. In this paper, we present

The earthquake magnitude prediction is a task of utmost difficulty that has been addressed by using many different strategies, with no further transformation thus far. This work evaluates the Haskell based deterministic dendritic cell algorithm (hDCA)’s accuracy when used to predict earthquake magnitude in Sichuan and surroundings. First, eight seismicity indicators have been retrieved from the literature

Deterministic interpolation can be applied automatically by tuning only limited number of parameters. Although it is an easy way to use mapping, potential spatial relationships in a data set are widely omitted. To represent spatial relationships, a topological-index based interpolation (TIBI) has been introduced. The weighting-based smoothing uses graph theory and it numerically characterizes spatial

With the advancement of GIS technology since its inception in 1960’s, many educational institutions, government departments, public/ private sectors and individuals have started its use for the production and management of spatial data. Spatial Data Infrastructure (SDI) concept was introduced in the early1990’s and provides a set of technologies, standards, protocols, policies and guidelines on the

Terraces are important objects of soil and water conservation and land use surveys in the Loess Plateau and considerably impact soil erosion and agricultural production. Obtaining the spatial distribution of terraces has great significance for soil and water conservation research and government policy-making. A new method of terrace extraction was proposed in this study based on remote sensing images

The ability to access and search metadata for marine science data is both a key requirement for answering fundamental principles of data management (making data Findable, Accessible, Interoperable and Reusable) and also in meeting domain-specific, community defined standards and legislative requirements placed on data publishers. This paper describes a modular data model to answer the functional requirements

Partial unmixing categorizes each pixel based on a particular mineral while a pixel may contain several minerals. Hence, it seems that the full unmixing procedure is essential to make real results. In this study, at first, the hydrothermal alteration minerals have been mapped by directed matched filtering (DMF) algorithm as a partial unmixing method on the most important porphyry copper deposit in

In this study, a new strategy based on integrating geostatistical seismic inversion and optimized support vector regression (OSVR) will be utilized to transform multi seismic attributes to sand fraction log. In first step, owing to compatibility relation between acoustic impedance (AI) and sand fraction, a high resolution value of this important attribute was extracted through a geostatistical seismic

Soil erosion, rapid geomorphological change and vegetation degradation are major threats to the human and natural environment. Unmanned Aerial Systems (UAS) can be used as tools to provide detailed and accurate estimations of landscape change. The effect of flight strategy on the accuracy of UAS image data products, typically a digital surface model (DSM) and orthophoto, is unknown. Herein different

It is a good method to utilize the grain size distribution curves and cumulative frequency curves of marine or river sediments to estimate the hydrodynamic conditions, transportation processes and sedimentary environment. However, researchers can only rely on Excel or Grapher to plot the curves one by one at the present day. The manual plotting procedures are complicated, and calculating the truncation

Data are the foundation of urban storm and flood disaster management and research; therefore, the question of how to improve the efficiency of data management and service systems has become the central issue in the field of urban flood disasters. In this study, a data management framework for urban flood disasters was established on the basis of ontology engineering in order to analyze heterogeneous

State-of-the-art machine learning methods, such as (deep) neural networks and support vector classifiers, have been successfully applied to problems related to the prediction of natural hazard events. However, the effectiveness of those methods is, in general, obtained at the cost of a complex algorithmic architecture that requires fine-tuning of several parameters. Moreover, their current popularity

In this study a new method for predicting soybean yield over large spatial scales, overcoming the difficulties of scalability, is proposed. The method is based on the so-called “simplified triangle” remote sensing technique which is coupled with a crop prediction model of Doorenbos and Kassam 1979 (DK) and the climatological water balance model of Thornthwaite and Mather 1955 (ThM). In the method,

The coastline can be used as the demarcation line between the ocean and the continent, which plays a crucial role in the development of marine economy. The purpose of this paper is to achieve stitching of coastline images from different areas automatically and create panoramic coast images. To be specific, we proposed a multi-resolution image fusion method which is based on the optimal seam-line method

The Ganges deltaic coast of Bangladesh experiences an incessant movement over the time. Understanding the shoreline movement of this alluvial delta and a suitable method to calculate the rate of change poses a challenge for this highly dynamic coast having erosion and accretion. Using GIS and multi temporal LANDSAT images, the study investigated the positional change of the Ganges deltaic shoreline

Identification of groundwater recharge zones in an area is important to properly utilize and safeguard the groundwater resources. The objective of this study is to delineate the groundwater potential zones in the Chinnar River basin of Perambalur district, southern India, using remote sensing and GIS methods. Toposheets and satellite imageries were used to prepare various thematic maps such as geology

Lineaments whose dominant azimuth reflects the basic framework of regional structure are mainly related to faults, but their spatial morphology and characteristics are different at different scales. The changing characteristics of multi-scale lineaments extracted by wavelet edge detection are quantitatively analyzed through image characteristics, azimuth characteristics, histogram, box-plot and paired-samples

This paper contributes an artificial intelligence classifier for hyperspectral images by simultaneously employing spectral and spatial information in kernel functions and using the stochastic relaxation of spectral and spatial energy. The spectral and spatial features are integrated with the Consecutive Spectral-Spatial/Spatial-Spectral (CS2) kernel which exhibits great flexibility in the combination

The mechanism of landslide occurrence is complicated due to the dependency and nonlinear relationship of various physical factors. A promising prediction model, which can be used to locate the high-risk regions and a corresponding prevention strategy can be prepared to reduce the slide occurrence and its consequence, is therefore desired. To perform the landslide assessment for a large-scale slope

By experimental measurements and theoretical analyses, this paper investigates the variation of the Sun’s visual shape and figures out the reasons for the variation of its shape. First, the method of image processing, the method of moments and the least-square method are combined to perform experimental measurements and calculations, and the features of the Sun’s visual shape are extracted from the

Road blockage information extraction from a single-phase postdisaster image is difficult because roads are narrow and easily covered by vegetation. The traditional object-oriented image analysis method is restrictive, and its detection is slow. A deep learning algorithm, i.e., the convolution neural network (CNN), is applied to rapidly extract road blockage information. An algorithm for sample generation

We present a method for determining surface flows from solar images based upon optical flow techniques. We apply the method to sets of images obtained by a variety of solar imagers to assess its performance. The opflow3d procedure is shown to extract accurate velocity estimates when provided perfect test data and quickly generates results consistent with completely distinct methods when applied on

Linked Science is the practice of inter-connecting scientific assets by publishing, sharing and linking scientific data and processes in end-to-end loosely coupled workflows that allow the sharing and re-use of scientific data. Much of this data does not live in the cloud or on the Web, but rather in multi-institutional data centers that provide tools and add value through quality assurance, validation

Having a high-quality database is a necessary condition to study the climate variations in a location, in a nation or in a continent. The World Meteorological Organization, WMO, is aware of the importance of identifying the non-climate factors that can modify the recorded values of the meteorological variables. According to this, WMO wrote a set of guidelines recognizing the need for National Meteorological

After an earthquake, the goal of emergency rescue work is to minimize the number of casualties and save lives. The most important initial task is the rapid assessment of the number of earthquake casualties. At present, the rapid assessment of casualties relies primarily on census data rather than real-time population data in an earthquake area. Features of the census data, such as their low accuracy

The remote sensed satellite images are big repository of information and provide the coverage of large areas. However, these images may not be able to describe the finer details of area being covered. Satellite Image optimization is the process of augmenting the components of an image for better and effective interpretations from satellite images. In order to obtain better visibility properties to

Analyzing the GPS coordinate time series plays an important role in the crustal deformation monitoring and surface mass variation interpretations. In this paper, we present the results of detailed studies concerning the analysis of the long-term GPS coordinate time series. We show what the characteristics of all stations is monitored and how to keep track of the variations for both horizontal and vertical

The preparation processes of large earthquake may start several or dozens of days before its actual occurrence. As scholars have observed the links between stationary GPS measurements of ground deformation and the occurrence of large earthquake, the continuous GPS data can be used as tools to identify such preparation processes. A method based on Martingale theory is proposed to extract the anomalies

Because the ore-forming system in the crust of the Earth is a highly nonlinear system, geochemical anomaly classification is very important for improving the accuracy of metallogenic prediction. Further, since the distribution of the geochemical elements usually presents nonlinear characteristics due to the complexity and uncertainty of geology factors, the traditional linear data processing method

Field sampling is an essential step for digital soil mapping and various sampling strategies have been designed for achieving desirable mapping results. Some unpredictable complex circumstances in the field, however, often prevent some samples from being collected based on the pre-designed sampling strategies. Such circumstances include inaccessibility of some locations, change of land surface types

Disasters are cataclysmic events that cause significant loss of natural, human and financial resources. The repercussions are exaggerated by climate change making disaster management a hot topic for academic research. The exponential growth in the utilization of ICT (Information and Communication Technology) with other domains has motivated the scientific community to integrate it with disaster management

People prefer staying in neighborhoods with abundant green space, but crowded urban buildings insulate residents from experiencing nature. As people spend most of time indoors, it is necessary to measure the amount of perceived greenery from residents’ perspective. Therefore, measuring people-perceiving-greenery at floor-level is very important not only for the developing of urban landscape ecology

A common practice in spatial analysis, data fusing, and geophysical interpretation is the need to handle raster datasets of different spatial resolution. Often, raster data are resampled through interpolation for better spatial representation and feature identification at both local and regional scales, but interpolation can result in artifact such as fewer blocks or mosaics, boundary blurring, edge

Spatiotemporal data mining has many important applications in environmental modelling. This paper introduces a modified algorithm for spatiotemporal data mining based on density-based spatial clustering of applications with noise (DBSCAN). Based on the modified algorithm, a geographic information system (GIS) add-in was developed using ArcObjects and C#, and is freely available for download. Compared