Assessing Site Selection of College Student Housing : Commuting Efficiency across Time

Universities around the world are promoting walking for their students because it provides many health and environmental benefits at the personal as well as the community level. This paper aims to help universities, city planners and housing investors in the process of efficient site selection for future student housing projects, by analyzing off-campus students’ commuting habits and travel time preferences to and from the university campuses. An online survey is operated to collect responses of students (n= 527) from two Jordanian universities located within the city of Irbid (N-Jordan). Results indicate that the mean value for students’ longest preferred one-way walking duration is 17.04± 8.25 minutes for the whole sample. A statistically significant negative correlation is found between students’ longest preferred one-way walking duration and age. The percentage of students who would accept this duration was represented in a formula in order to calculate the accumulated walking potential of varied sites around university campuses. The paper presented a local scenario using GIS mapping where this process was implemented to evaluate prospect vacant sites' walking potential around Yarmouk University, Irbid, Jordan

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research

Assessment of Sentinel-2 and Landsat-8 OLI for Small-Scale Inland Water Quality Modeling and Monitoring Based on Handheld Hyperspectral Ground Truthing

This study investigates the best available methods for remote monitoring inland small-scale waterbodies, using remote sensing data from both Landsat-8 and Sentinel-2 satellites, utilizing a handheld hyperspectral device for ground truthing. Monitoring was conducted to evaluate water quality indicators: chlorophyll-a (Chl-a), colored dissolved organic matter (CDOM), and turbidity. Ground truthing was performed to select the most suitable atmospheric correction technique (ACT). Several ACT have been tested: dark spectrum fitting (DSF), dark object subtraction (DOS), atmospheric and topographic correction (ATCOR), and exponential extrapolation (EXP). Classical sampling was conducted first; then, the resulting concentrations were compared to those obtained using remote sensing analysis by the above-mentioned ACT. This research revealed that DOS and DSF achieved the best performance (an advantage ranging between 29% and 47%). Further, we demonstrated the appropriateness of the use of Sentinel-2 red and vegetation red edge reciprocal bands (1/(B4 X B6)) for estimating Chl-a (R2 = 0.82, RMSE = 14.52mg/m3). As for Landsat-8, red to near-infrared ratio (B4/B5) produced the best performing model (R2 = 0.71, RMSE = 39.88 mg/m3), but it did not perform as well as Sentinel-2. Regarding turbidity, the best model (with (R2 =0.85, RMSE = 0.87 NTU) obtained by Sentinel-2 utilized a single band (B4), while the best model (with R2 = 0.64, RMSE = 0.90 NTU) using Landsat-8 was performed by applying two bands (B1/B3). Mapping the water quality parameters using the best performance biooptical model showed the significant effect of the adjacent land on the boundary pixels compared to pixels of deeper water

Evaluation of the gulf of aqaba coastal water, Jordan

© 2020 by the authors. (1) Background: The Gulf of Aqaba (GoA) supports unique and diverse marine ecosystems. It is one of the highest anthropogenically impacted coasts in the Middle East region, where rapid human activities are likely to degrade these naturally diverse but stressed ecosystems. (2) Methods: Various water quality parameters were measured to assess the current status and conditions of GoA seawater including pH, total dissolved solids (TDS), total alkalinity (TA), Cl-, NO3-, SO42-, PO43-, NH4+, Ca2+, Mg2+, Na+, K+, Sr, Cd, Co, Cr, Cu, Fe, Mn, Pb, and Zn. (3) Results: The pH values indicated basic coastal waters. The elevated levels of TDS with an average of about 42 g/L indicated highly saline conditions. Relatively low levels of inorganic nutrients were observed consistent with the prevalence of oligotrophic conditions in GoA seawater. The concentrations of Ca2+, Mg2+, Na+, K+, Sr, Cl-, and SO42- in surface layer varied spatially from about 423-487, 2246-2356, 9542-12,647, 513-713, 9.2-10.4, 22,173-25,992, and 317-407 mg/L, respectively. The average levels of Cd, Co, Cr, Cu, Fe, Mn, Pb and Zn ranged from 0.51, 0.38, 1.44, 1.29, 0.88, 0.38, and 6.05 μg/L, respectively. (4) Conclusions: The prevailing saline conditions of high temperatures, high evaporation rates, the water stratification and intense dust storms are major contributing factors to the observed seawater chemistry. The surface distribution of water quality variables showed spatial variations with no specific patterns, except for metal contents which exhibited southward increasing trends, closed to the industrial complex. The vast majority of these quality parameters showed relatively higher values compared to those of other regions

Two Inferred Antique earthquakes recorded in the Roman theater of Beit-Ras / Capitolias (Jordan)

A Roman theater is recently being excavated at Beit-Ras/Capitolias in Jordan, which is one of the Decapolis cities, founded before 97/98 AD. This is an archaeoseismological study that aims to investigate temporal and intensity impacts on the existing structures. A rich set of Earthquake Archaeological Effects (EAEs) are identified, including deformed arches, tilted and collapsed walls, chipped corners of masonry blocks, and extensional gaps indicating a seismic intensity of VIII-IX. Contrary to the long lasting belief that the 749 AD event is the main candidate earthquake damaging most of the Decapolis cities, the study found that at least two major older earthquakes damaged the site and may have led to the abandonment of its major use as a theater at different periods. This is based on field observations of construction stratigraphy and damage features and on the assessment the observed destruction and on reports in literature. The date of the first event is bracketed between the establishment of the city (before 97/98 AD) and an inscription in the walled-up orchestra gate in 261 AD. This earthquake destroyed the external wall of the theater's external annular passageway (ambulatorium), the scaena, and its staircases. The most likely candidate earthquake is 233 AD or other event which is not mentioned in any catalogue. After restoration, another earthquake occurred between 261 AD and Late Roman-Early Byzantine times, when the scaena wall tilted and collapsed, rendering the building useless and beyond repair. It is probably 363 AD earthquake. Filled up with debris, the theater went out of use. The paper provides a rich discussion of potential causative earthquakes based on archaeoseismological, construction stratigraphy observations, and calibrated intensity of historical earthquake-based attenuation modelling. It identifies the potential phases and types of destruction and reuse. It is setting the grounds for future archaeological and seismological research on this site

Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition

Landslides often cause economic losses, property damage, and loss of lives. Monitoring landslides using high spatial and temporal resolution imagery and the ability to quickly identify landslide regions are the basis for emergency disaster management. This study presents a comprehensive system that uses unmanned aerial vehicles (UAVs) and Semi-Global dense Matching (SGM) techniques to identify and extract landslide scarp data. The selected study area is located along a major highway in a mountainous region in Jordan, and contains creeping landslides induced by heavy rainfall. Field observations across the slope body and a deformation analysis along the highway and existing gabions indicate that the slope is active and that scarp features across the slope will continue to open and develop new tension crack features, leading to the downward movement of rocks. The identification of landslide scarps in this study was performed via a dense 3D point cloud of topographic information generated from high-resolution images captured using a low-cost UAV and a target-based camera calibration procedure for a low-cost large-field-of-view camera. An automated approach was used to accurately detect and extract the landslide head scarps based on geomorphological factors: the ratio of normalized Eigenvalues (i.e., λ1/λ2 ≥ λ3) derived using principal component analysis, topographic surface roughness index values, and local-neighborhood slope measurements from the 3D image-based point cloud. Validation of the results was performed using root mean square error analysis and a confusion (error) matrix between manually digitized landslide scarps and the automated approaches. The experimental results using the fully automated 3D point-based analysis algorithms show that these approaches can effectively distinguish landslide scarps. The proposed algorithms can accurately identify and extract landslide scarps with centimeter-scale accuracy. In addition, the combination of UAV-based imagery, 3D scene reconstruction, and landslide scarp recognition/extraction algorithms can provide flexible and effective tool for monitoring landslide scarps and is acceptable for landslide mapping purposes

UAV-Based Digital Imaging System for the Derivation of 3D Point Cloud for Landslide Hazard Analysis

Emergency disaster response and analysis of landslides depend on accurate, rapid detection and extraction of a landslide area. Terrestrial laser scanning systems (TLS) are highly accurate and provide quick 3D point cloud data with high resolution, but suffer from occlusions, truncation, and orientation bias. This dissertation proposes an augmentation of TLS and an image-based point cloud generated from a semi-global matching (SGM) algorithm on an UAV platform outfitted with a low-cost action camera to overcome these limitations. The experimental results provided high quality measurements for the geotechnical discontinuity plane orientation parameters, increased safety, saved cost and time, and provided more accurate results compared to manual field measurements, TLS data only, and SGM data only. This dissertation developed a comprehensive system using UAVs and SGM techniques to accurately identify and extract landslide scarps within centimeter-scale accuracy through three automated approaches. These approaches accurately detected and extracted landslide scarps based on the ratio of the normalized Eigenvalues derived using principal component analysis, surface roughness index, and slope measurements from the 3D image-based point cloud. Experimental results using the fully automated 3D point-based analysis algorithms confirmed that these approaches can effectively distinguish landslide scarps. The developed algorithms are a flexible and effective tool for monitoring landslide scarps and are acceptable for landslide mapping purposes. A robust image-based registration method also was developed for the simultaneous evaluation and temporal monitoring of landslide dynamics from different epochs. This method includes the camera’s IOPs and EOPs of the involved images from all the available observation epochs via a bundle block adjustment with self-calibration. A SGM technique was implemented to generate 3D point clouds for each epoch using the images captured for each epoch separately. The accuracy of the co-registered surfaces was estimated by comparing the non-active patches within the monitored area of interest. Since non-active sub-areas are stationary, the computed normal distances theoretically should be close to zero. The quality control of the registration results showed an average normal distance of approximately 3.7 cm, which is within the noise level of the reconstructed surfaces. Overall, the registration approach proposed in this dissertation is low level

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research

A Novel Coating Method for Create Filter Media Capable to Remove Phosphate from Wastewater Effectively

Filtration materials coating with metallic oxides represented a good method for phosphate sorption. However, most of the researchers utilize chemicals as a source of metallic oxides and heating process to set the chemicals over the filtration materials. This study is aimed to introduce the furnace bottom ash FBA as a source of metallic oxides; it is available free because it is dumped as a waste material from power generation plants. The method of creating new filter media involves coating the limestone and sand by FBA, and the ordinary Portland cement OPC utilized as binder to binding the mixture materials. The water is the factor which is responsible for activating the OPC. All factors such as mixed materials ratio, water content and age of reaction have subjected to optimization process. The results revealed that the optimal mixture for phosphate removal consists of 40% FBA, 5% OPC from dry weight of supporting material, 35% water ratio from the total weight of FBA and OPC, and 14 days are enough to complete the materials reaction. Limestone-furnace bottom ash LFBA indicated high capacity for phosphate sorption and possibility  of  efficiency  regenerate.  This  study  demonstrates  a  new  method  for coating the filtration materials more convenient with sustainability approach.Validerad;2020;Nivå 1;2019-12-19 (johcin)</p

Flow Variation of the Major Tributaries of Tigris River Due to Climate Change

Iraq relies greatly  on  the  flow of  the  Euphrates  and  Tigris Rivers  and  their tributaries. Five tributaries namely Khabour, Greater Zab, Lesser Zab, AlAd- hiam  and  Daylia,  which  are  the  major  tributaries  of  Tigris  River,  sustain Northern  Iraq  Region,  a  semi-arid,  mainly  a  pastureland.  These  tributaries contribute about 24 km3  of water annually. The discharge in the tributaries, in recent  times,  has  been  suffering  increasing  variability  contributing  to  more severe droughts and floods apparently due to climate change. This is because there were no dams constructed outside Iraq previously. For an appropriate appreciation,  Soil  Water  Assessment Tool  (SWAT)  model  was used  to evaluate  the  impact  of  climate  change  on  their  discharge  for  a  half-centennial lead time to 2046-2064 and a centennial lead time to 2080-2100. The suitability of the model was first evaluated, and then, outputs from six GCMs were incorporated  to  evaluate  the  impacts  of  climate  change  on  water  resources under three emission scenarios: A1B, A2 and B1. The results showed that wa-ter resources are expected to decrease with time.Validerad;2020;Nivå 1;2019-12-19 (johcin)</p