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Floods are considered as one of the most lethal natural disasters having the potential to cause havoc to entire communities. Pakistan is the land of wide topographic and climatic variations which make it vulnerable to floods. The purpose of this paper is to identify flood susceptible zones in the Panjkora Basin using frequency ratio model.

A total of seven parameters or flood conditioning factors were considered, and weights were assigned according to the frequency ratio technique. For the preparation of layers, satellite imageries and digital elevation model data were used. Frequency ratio was calculated using correlation between these parameters and flood. Flood susceptibility index map was divided into five zones through quantile method in ArcMap.

Findings of the study reveal that near half of the area (43%) is located in the very high susceptible zone, while only 20% area is classified as low to very low susceptible.

This paper is entirely based on original research. The approach used in this study has not been applied to the study area before.

Scholars mainly propose and establish theoretical models of cumulative fatigue damage for their research fields. This review aims to select the applicable model from many fatigue damage models according to the actual situation. However, relatively few models can be generally accepted and widely used.

This review introduces the development of cumulative damage theory. Then, several typical models are selected from linear and nonlinear cumulative damage models to perform data analyses and obtain the fatigue life for the metal.

Considering the energy law and strength degradation, the nonlinear fatigue cumulative damage model can better reflect the fatigue damage under constant and multi-stage variable amplitude loading. In the following research, the complex uncertainty of the model in the fatigue damage process can be considered, as well as the combination of advanced machine learning techniques to reduce the prediction error.

This review compares the advantages and disadvantages of various mainstream cumulative damage research methods. It provides a reference for further research into the theories of cumulative fatigue damage.

In a tropical country like Malaysia, forest fire is a very common natural and man‐made disaster that prevails in the whole South East Asian region throughout the year. Recently, the haze problem in Malaysia has created a lot of awareness among the government and eco‐tourism sectors. Therefore, detection of the hotspot is very important to delineate the forest fire susceptibility mapping. In this study, remote sensing and geographical information systems (GIS) have been used to evaluate forest fire susceptibility at Sungai Karang and Raja Muda Musa Forest Reserve, Selangor, Malaysia. Frequency ratio model has been applied for the delineation of forest fire mapping for the study area.

Forest fire locations were identified in the study area from historical hotspots data from year 2000 to 2005 using AVHRR NOAA 12 and NOAA 16 satellite images. Various other supported data such as soil map, topographic data, and agro climate were collected and created using GIS. These data were constructed into a spatial database using GIS. The factors that influence fire occurrence, such as fuel type and Normalized Differential Vegetation Index (NDVI), were extracted from classified Landsat‐7 ETM imagery. Slope and aspect of topography were calculated from topographic database. Soil type was extracted from soil database and dry month code from agroclimate data. Forest fire susceptibility was analyzed using the forest fire occurrence factors by likelihood ratio method.

A new statistical method has been applied for the forest fire susceptibility mapping. The results of the analysis were verified using forest fire location data with the help of a newly written programming code. The validation results show satisfactory agreement between the susceptibility map and the existing data on forest fire location. The GIS was used to analyze the vast amount efficiently, and statistical programs were used to maintain the specificity and accuracy. The result can be used for early warning, fire suppression resources planning and allocation.

All data used in this study are original. The forest fire susceptibility mapping has been done in this study area for the first time. A new program has been coded to cross‐verify the susceptibility map. The results were also verified with field data and other supporting weather data.

The present study aims to construct ensemble machine learning (EML) algorithms for groundwater potentiality mapping (GPM) in the Teesta River basin of Bangladesh, including random forest (RF) and random subspace (RSS).

The RF and RSS models have been implemented for integrating 14 selected groundwater condition parametres with groundwater inventories for generating GPMs. The GPM were then validated using the empirical and bionormal receiver operating characteristics (ROC) curve.

The very high (831–1200 km²) and high groundwater potential areas (521–680 km²) were predicted using EML algorithms. The RSS (AUC-0.892) model outperformed RF model based on ROC's area under curve (AUC).

Two new EML models have been constructed for GPM. These findings will aid in proposing sustainable water resource management plans.

The purpose of this research is to produce the landslide susceptibility map of Fraser's Hill and its surroundings in Pahang (Malaysia), utilizing remote sensing data and Geographic Information System (GIS) as a way to monitor sustainable highland development.

Ancillary data are collected, processed, and constructed into a spatial database in a GIS platform to produce the satellite image. The factors chosen that influence landslide occurrence are land cover, vegetation index (NDVI), precipitation, and geology. Landslide‐hazardous areas are analyzed and mapped using the landslide‐occurrence factors through the heuristic approach Analytic Hierarchy Process (AHP).

It is demonstrated that the integration of remote sensing data and GIS database is of assistance in managing land‐use planning of sustainable development. The verification with the existing landslides record shows a noteworthy accuracy.

The list of data/maps reflects a considerable understanding of the basic cartographic information that is needed to effectively deal with the landslide problem.

This approach indicates a potential long‐term application of remote sensing and GIS in managing sustainable highland development by monitoring the hazard‐susceptibility area.

The value of the work is in its integration and utilization of remote sensing and GIS to provide sustainable development which can be developed to aid landslide warning systems.

The study aimed to use geographic information system (GIS) based multi-criteria decision making analysis (GIS-MCDA) to select areas suitable for siting landfills in Ashanti region. It also sought to ascertain variables most sensitive to the siting of landfill in the region.

This study utilized GIS-based Multi-criteria decision making analysis –AHP to model and select areas most suitable to siting landfills within the region. Overall, 16 variables including wind speed and hydraulic conductivity (which were previously neglected in landfill siting in Ghana) were identified through comprehensive literature review. These variables were weighted using AHP method and integrated using the weighted linear combination (WLC) in GIS environment to develop five sub-models: the physical environmental, sociocultural, economic/technical, climatic and hydrogeological sub-models. These sub-models were further weighted and then integrated to derive the final suitability model.

Results show that 13% (3,067 km²) of the region was identified as most suitable to siting engineered landfills. The study also identified 11 sites which are considered most suitable for situating landfills. On a sensitivity angle, hydrogeological (R² = 0.5923; p = 0.003) and physical environmental sub-model (R² = 0.254; p = 0.034) significantly predicted the final suitability model developed.

Ghana's Landfill Guidelines seeks to optimize site selection and ancillary services that culminate into achieving sanitary landfills by 2020. Evidence still abounds on the unsuitability of existing and in some cases, new landfill sites presenting environmental and social negative impacts. The comprehensive evaluation of most crucial variables – social and environmental factors that determine an optimal landfill location – will be of immense help to policy planners like the Environmental Protection Agency (EPA) towards upgraded landfills. The authors hope that, concerned agencies will adopt the model in the study and integrate into their existing landfill suitability modeling techniques to provide a more grounded framework that optimizes landfill site selection within the study area.

This study is the first attempt to consider a regional-level waste collection site selection in Ghana using comprehensive sets of social and environmental factors and will therefore contribute immensely to EPA's goal of achieving upgraded landfills by 2022.

The objective of the work is to have an insight into the degree of the contemporary concept of greening the organization through human resource management (HRM) and to attempt to bridge the gap toward environmental awareness, as well as to observe the dimensions of green HRM (GHRM) practices and its impression toward environmental sustainability by using analytical hierarchy process (AHP) and FAHP.

The research was carried out in two phases; multi-method was employed. The first phase mainly includes a systematic review to convene comprehensive knowledge of widespread GHRM practices to leverage environmental sustainability. In the second phase, the AHP and fuzzy AHP (FAHP) were employed to examine the influence of the respective dimension of GHRM practices toward environmental sustainability.

This study emphasizes the status of GHRM practices such as green recruitment and green selection, green performance management, green training and development, green compensation and rewards, green welfare aspects as a way to aid environmental issues. The findings suggest that these initiatives help to leverage environmental sustainability. Further, this paper reveals that green compensation and rewards have the highest impact on leveraging environmental sustainability. However, this study also emphasizes the comparative study of GHRM dimensions through AHP and FAHP.

As existing studies reveal, there is least research carried on this field of study and no study was conducted using AHP and FAHP in this field. Thus, this study reveals the necessity to discover the degree of concern toward GHRM practices in context to India.

Recently, there has been a shift toward the embodied energy assessment of buildings. However, the impact of material service life on the life-cycle embodied energy has received little attention. We aimed to address this knowledge gap, particularly in the context of the UAE and investigated the embodied energy associated with the use of concrete and other materials commonly used in residential buildings in the hot desert climate of the UAE.

Using input–output based hybrid analysis, we quantified the life-cycle embodied energy of a villa in the UAE with over 50 years of building life using the average, minimum, and maximum material service life values. Mathematical calculations were performed using MS Excel, and a detailed bill of quantities with >170 building materials and components of the villa were used for investigation.

For the base case, the initial embodied energy was 57% (7390.5 GJ), whereas the recurrent embodied energy was 43% (5,690 GJ) of the life-cycle embodied energy based on average material service life values. The proportion of the recurrent embodied energy with minimum material service life values was increased to 68% of the life-cycle embodied energy, while it dropped to 15% with maximum material service life values.

The findings provide new data to guide building construction in the UAE and show that recurrent embodied energy contributes significantly to life-cycle energy demand. Further, the study of material service life variations provides deeper insights into future building material specifications and management considerations for building maintenance.

This paper aims to simplify a new frequency-independent model to calculate vertical vibration of rigid circular foundation resting on homogenous half-space and subjected to vertical harmonic excitation is presented in this paper.

The proposed model is an oscillator of single degree of freedom, which comprises a mass, a spring and a dashpot. In addition, a fictitious mass is added to the foundation. All coefficients are frequency-independent. The spring is equal to the static stiffness. Damping coefficient and fictitious mass are first calculated at resonance frequency where the response is maximal. Then, using a curve fitting technique the general formulas of damping and fictitious mass frequency-independent are established.

The validity of the proposed method is checked by comparing the predicted response with those obtained by the half-space theory. The dynamic responses of the new simplified model are also compared with those obtained by some existing lumped-parameter models.

Using this new method, to calculate the dynamic response of foundations, the engineer only needs the geometrical and mechanical characteristics of the foundation (mass and radius) and the soil (density, shear modulus and the Poisson’s ratio) using just a simple calculator. Impedance functions will no longer be needed in this new simplified method. The methodology used for the development of the new simplified model can be applied for the resolution of other problems in dynamics of soil and foundation (superficial and embedded foundations of arbitrary shape, other modes of vibration and foundations resting on non-homogeneous soil).

This study examines the value relevance of recognised and disclosed revaluations of land and buildings for a large sample of Australian firms from 1993 through 1997. In contrast to prior research, we control for risk and cyclical effects and find no difference between recognised and disclosed revaluations, using yearly‐cross‐sectional and pooled regressions and using both market and non‐market dependent variables. We also find only weak evidence that revaluations of recognised and disclosed land and buildings are value relevant.