Raed Aldouri

Application of multitemporal Landsat data to monitor land cover changes in the Eastern Nile Delta region, Egypt

Due to the progressive increase in development of desert land in Egypt, the demand for efficient and accurate land cover change information is increasing. In this study, we apply the methodology of post‐classification change detection to map and monitor land cover change patterns related to agricultural development and urban expansion in the desert fringes of the Eastern Nile Delta region. Using a hybrid classification approach, we employ multitemporal Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images from 1984, 1990 and 2003 to produce three land cover/land‐use maps. Post‐classification comparison of these maps was used to obtain ‘from–to’ statistics and change detection maps. The change detection results show that agricultural development increased by 14% through the study period. The average annual rate of land reclamation during 1990–2003 (4511 ha a−1) was comparable to that during 1984–1990 (4644 ha a−1), reflecting a systematic national plan for desert reclamation that went into effect. We find that the increase in urbanization (by ca 21 300 ha) during 1990–2003 was predominantly due to encroachment into traditionally cultivated land at the fringes of urban centres. Our results accurately quantify the land cover changes and delineate their spatial patterns, demonstrating the utility of Landsat data in analysing landscape dynamics over time. Such information is critical for making efficient and sustainable policies for resource management.

No Safe Place: Environmental Hazards & Injustice along Mexico's Northern Border.

This article examines spatial relationships between environmental hazards (i.e., pork feed lots, brick kilns, final assembly plants and a rail line) and markers of social marginality in Ciudad Juárez, Mexico. Juárez represents an opportunity for researchers to test for patterns of injustice in a recently urbanizing metropolis of the Global South. We use spatial-econometric modeling to predict the four unique hazard variables and a composite hazard variable using socio-demographic variables at the neighborhood level. Lower class and higher percentages of children and migrants were statistically significant predictors of composite hazard density. These results align with previous studies in the North. However, disaggregating these results by hazard type reveals important and counterintuitive differences in groups at risk based on the market-orientation of the hazard (i.e., domestic vs. transnational) and its location within the urban structure.

Double exposure and the climate gap: changing demographics and extreme heat in Ciudad Juárez, Mexico

Scholars have recognised a climate gap, wherein poor communities face disproportionate impacts of climate change. Others have noted that climate change and economic globalisation may mutually affect a region or social group, leading to double exposure. This paper investigates how current and changing patterns of neighbourhood demographics are associated with extreme heat in the border city of Juárez, Mexico. Many Juárez neighbourhoods are at-risk to triple exposures, in which residents suffer due to the conjoined effects of the global recession, drug war violence, and extreme heat. Due to impacts of the recession on maquiladora employment and the explosion of drug violence (2008–2012), over 75% of neighbourhoods experienced decreasing population density between 2000 and 2010 and the average neighbourhood saw a 40% increase in the proportion of older adults. Neighbourhoods with greater drops in population density and increases in the proportion of older residents over the decade are at significantly higher risk to extreme heat, as are neighbourhoods with lower population density and lower levels of education. In this context, triple exposures are associated with a climate gap that most endangers lower socio-economic status and increasingly older-aged populations remaining in neighbourhoods from which high proportions of residents have departed.

Optimal Allocation of Emergency Response Service Units to Cover Critical Infrastructures with Time-Dependent Service Demand and Travel Time

Optimal deployment of limited emergency response service (ERS) units in a metropolitan area is of interest to public agencies. The limited emergency units not only have to respond to the demand for service by citizens and businesses but also have to cover critical infrastructures (CIs). The paper formulates an optimization model to allocate different types of ERS units among their candidate base stations. The allocation of units must ensure maximum coverage to CIs, subject to the capacities of the base stations, service standard in terms of time to reach the CIs, and the availability of the ERS units (when there are other competing demands for services). Unlike past models, the modeling approach here accounts for the fluctuation of travel time and demand frequency at different time periods of a typical day. The applicability of the model has been demonstrated in a case study in the city of El Paso, Texas, which allocates 45 firefighting units and 23 ambulances among 34 active fire stations to cover 138 critical transportation infrastructures, hospitals, and schools.

Optimal assignment of emergency response service units with time-dependent service demand and travel time

This article formulates an improved integer-programming model to assign multiple types of emergency response service units among their candidate base stations to maximize the coverage to the critical infrastructures, subject to station capacity, service time, and reliability constraints. Unlike past models, this new model formulation accounts for the fluctuation of travel time and demand frequency at different time periods of a day. The potential applications of the model have been illustrated via a case study of assigning firefighting units and ambulances in the city of El Paso, Texas. This article also demonstrates how the model can be modified for the selection of a new base station, increase in fleet size, station capacity expansion, or a combination of these.

Impact of Geospatial Classification Method on Interpretation of Intelligent Compaction Data

Intelligent compaction is an emerging technology in the management of pavement layers, more specifically, of unbound geomaterial layers. Different types of intelligent compaction measurement values (ICMVs) are available on the basis of the configuration of the roller, vibration mechanism, and data collection and reduction algorithms. The spatial distribution of the estimated ICMVs is usually displayed as a color-coded map, with the ICMVs categorized into a number of classes with specific color codes. The number of classes, as well as the values of the breaks between classes, significantly affect the perception of compaction quality during the quality management process. In this study, three sets of ICMV data collected as a part of a field investigation were subjected to geostatistical analyses to evaluate different classification scenarios and their impact on the interpretation of the data. The classification techniques were evaluated on the basis of the information theory concept of minimizing the information loss ratio. The effect of the ICMV distribution on the selection of the classification method was also studied. An optimization technique was developed to find the optimal class breaks that minimize the information loss ratio. The optimization algorithm returned the best results, followed by the natural breaks and quantile methods, which are suited to the skewness of the ICMV distribution. The identification of less-stiff areas by using the methods presented will assist highway agencies to improve process control approaches and further evaluate construction quality criteria. Although the concepts discussed can apply to any compacted geomaterial layer, the conclusions apply to the type of compacted soil in this particular test section.

Compaction Quality Monitoring of Lime-Stabilized Clayey Subgrade Using Intelligent Compaction Technology

This study presents the evaluation of the compaction process on a lime-stabilized clayey subgrade soil using the intelligent compaction (IC) technology. Two test beds with similar clayey subgrade soil were constructed with and without in-situ lime stabilization. These test beds were evaluated using several in situ nondestructive testing devices and an IC-equipped vibratory roller. The results from the study showed significant spatial variability in the in-situ test results and the roller measurements. In comparison to the untreated subgrade, the lime-stabilized test sections demonstrated a reduction in the variability of the roller measurements. The roller measurements on the stabilized section were influenced by the testing time and the underlying support conditions. The laboratory results and the field measurements using the roller and in-situ devices pointed to the improvement in the soil properties after stabilization. The moduli of the stabilized subgrade soil increased by almost two times. Statistical analyses demonstrated the influence of the underlying support condition, the moisture content and the lift thickness variations on the roller measurements.

Evaluation and Harmonization of Intelligent Compaction Systems

Intelligent compaction (IC) is an emerging technology for quality management of compacted pavement layers. Data collected by a vibration sensor and translated to a stiffness-based parameter is usually called the IC measurement value (ICMV). The ICMVs are coordinated with the global positioning system (GPS) data to assess the geospatial distribution of compacted layer properties. The IC rollers can be equipped with the original equipment manufacturer (OEM) systems that are provided by the vendors. However, with the recent introduction of the after-market or retrofit IC kits, it is possible to collect IC data with most regular vibratory rollers. Even though the use of the IC retrofit kits has been gaining popularity, its performance during the field operation has not been documented extensively. In this study, two dynamic vibratory rollers equipped with the OEM IC systems were employed along a test section. A retrofit kit was also installed on one of the rollers to collect the IC data during the same field operation simultaneously with the OEM system. The geospatial distribution of the ICMVs between the two types of systems for the most part was comparable. However, the magnitudes of the ICMVs among rollers and IC systems were somewhat different. These differences in the ICMVs were attributed to the differences in the vibration sensors and their installation as well as the data reduction algorithms among different systems. The reliability of the results from the OEM systems and retrofit kits seemed to be dependent on the proper installation of the vibration sensors as well as the accurate calibration of the GPS unit prior to the field data collection. A validation system and a standard protocol are needed to harmonize the performance of the IC rollers.

Gravity investigations of recent sinkholes and karst pits of Dahal Al-Hamam, State of Qatar

Gravity prospecting is a very useful geophysical technique for the investigation of karst subsurface features, in urban areas, which are a common natural hazard in several parts of the world. Gravity data were used to determine the subsurface conditions in central Qatar to map zones vulnerable to sinkhole formation in the vicinity of Dahel Al-Hamam area in the State of Qatar. Gravity modeling was a useful technique to map the spatial extension of the karts topography associated with these sinkholes. Clusters of closely spaced contours of low gravity values observed in the northeastern part of the studied area are indicative of relatively very low negative anomaly which points to missing mass due to karst processes. This was interpreted as either as an air-filled or water-filled sinkhole. The obtained video images of the subsurface features of the studied area confirmed that the existing subsurface caves are water filled. The extension of the sinkhole and associated openings are connected to the Arabian Gulf. To prevent the growth of associated underground cavities, the bibliographical research indicated that filling up the uppermost voids with stable grout mix is one of the appropriate treatment options to help reduce the macro-permeability of the rock and to prohibit the migration of the favorable conditions of cavity formation. The findings have both local and general applications. Locally, the findings delineate the subsurface extension of the karst topography, and it is generally demonstrated that non-invasive surveying methods constitute a useful tool to enhance knowledge on sinkhole phenomenon.