Spatiotemporal trends of temperature extremes in Bangladesh under changing climate using multi-statistical techniques

Theoretical and Applied Climatology - The rise in the frequency and magnitude of extreme temperature phenomena across the globe has led to the recurrent incidence of global climate hazards, which...     

Selection of Optimal Object Features in Object-Based Image Analysis Using Filter-Based Algorithms

With the increase in spatial resolution of recent sensors, object-based image analysis (OBIA) has gained importance for producing detailed land use maps. One of the main advantages of OBIA is that a variety of spectral, spatial and textural features can be extracted for the segmented image objects that are later utilized in classification. However, using a large number of features not only increases the required computational time, but also requires a large number of ground samples, which is unavailable in most cases. For these reasons, feature selection (FS) has become an important research topic for OBIA based classification studies. In this study, three filter-based FS algorithms namely, Chi square, information gain and ReliefF were applied to determine the most effective object features that ensure high separability among landscape features. For this purpose, importance degree (i.e. ranks) of 110 input object features were firstly estimated by the algorithms, and correlation-based merit function was then applied to determine optimum feature subset size. Multi-resolution segmentation algorithm was applied for segmenting a WorldView-2 image. Support vector machine, random forest and nearest neighbour classifiers were all utilized to classify segmented image objects using the selected object features. Results revealed that the FS algorithms were effective for selecting the most relevant features. Also, the classifiers produced the highest performances with 24 out of 110 features selected by the information gain (IG) algorithm. Particularly, the support vector machine classifier produced the highest overall accuracy (92.00%) with 24 selected features determined by the IG algorithm. A significant improvement of about 4% was achieved by applying FS procedures that was found statistically significant in terms of Wilcoxon signed-ranks test.     

An Overview of the Use of Rockbolts as Support Tools in Mining Operations

Geotechnical and Geological Engineering - Historically, the idea of designing and installing rockbolts in rockmasses can be traced back to the construction of the Snowy Mountain hydroelectric...     

Environmental rethinking of wastewater drains to manage environmental pollution and alleviate water scarcity

Natural Hazards - The conservation of water resources in developed countries has become an increasing concern. In integrated water resource management, water quality indicators are critical. The...     

Two MASS photometry of open star clusters: King 13 and Berkeley 53

In the present work, we used the near-infrared JHK_s photometric data from the 2-Micron All Sky Survey (2MASS) to determine the morphological and photometric parameters for two rarely studied open star clusters; King 13 and Berkeley 53. Luminosity function, mass function and dynamical relaxation time have been determined for the two clusters. We estimated the distances of 2.11±0.25 Kpc and 3.51±0.21 Kpc for King 13 and Berkeley 53 respectively, and both clusters have the same age 1.00±0.12 Gyr at solar metallicity; z=0.019.     

Laboratory study of shear strength response of Chlef natural sand: Effect of saturation

Abstract

The study of the unsaturated soils is a very complex field to which several researches in laboratory and on site are directed these last years. An experimental study aims to quantify the influence of the Skempton coefficient B characterizing the degree of saturation on the behavior of the granular sand to the liquefaction resistance of sand. The study is based on undrained triaxial tests performed on natural Chlef sand carried out at an initial relative density Dr = 50% under a confining pressure of 50, 100 and 200?kPa for Skempton coefficient B?=?10 to 92%. The results of the tests show that an increase of confining pressure leads to an increase of the shear stress of the samples. For the lower value of the degree of saturation results of our findings indicate an increase of the resistance to liquefaction; our results are in good agreement with others observed in several research projects conducted with other sands. The increase of Skempton coefficient B induces an increase of pore water pressure and a decrease of the shear strength. The pore pressure (u) increases with an exponential manner with the increase of the degree of saturation; while the residual shear strength (Rs) decreases with logarithmic manner with the increase of degree of saturation (B).     

Modeling the Potential Distribution of Pine Forests Susceptible to Sirex Noctilio Infestations in Mpumalanga,South Africa

Reducing the impact of the siricid wasp, Sirex noctilio is crucial for the future productivity and sustainability of commercial pine resources in South Africa. In this study we present a machine learning model that serves as a spatial guide and allows forest managers to focus their existing detection and monitoring efforts on key areas and proactively adopt the most appropriate course of intervention. We implemented the random forest model within a spatial framework to determine which pine forests in Mpumalanga are highly susceptible to S. noctilio infestations. Results indicate that a majority (63%) of pine forest plantations located in Mpumalanga have a high susceptibility (>70%) to S. noctilio infestation. A KHAT value of 0.84 and F measures above 0.87 indicate that the random forest model is a robust classifier that produces accurate results. Additionally, the use of the backward variable selection method enabled us to simplify the random forest modeling process and identify the minimum number of explanatory variables that offer the best discriminatory power and help in the empirical interpretation of the final random forest model. Overall, the results show that pine forests that experience stress caused by evapotranspiration and evaporation followed by rainfalls, especially during the summer months are more susceptible to S. noctilio infestations.     

Assessing the oscillation of channel geometry and meander migration cardinality of Bhagirathi River,West Bengal,India

Journal of Geographical Sciences - Lateral migration of the Bhagirathi River temporally creates unavoidable geomorphic hazards in West Bengal, India. The Bhagirathi River flows SW for ~67.30 km...