Automatic detection of potential buried archaeological sites in Saruq Al-Hadid, United Arab Emirates

The use of remote sensing in archaeological research allows the prospection of sub-surfaces in arid regions non- intrusively before the on-site investigation and excavation. While the actual detection method of expected buried archaeological structures is based on visual interpretation, this work provides a supporting archaeological guidance using remote sensing. The aim is to detect potential archaeological remains underneath the sand. This paper focuses on Saruq Al-Hadid surroundings, which is an archaeologist site discovered in 2002, located about 50 km south-east of Dubai, as archaeologists believe that other archaeological sites are potentially buried in the surroundings. The input data is derived from a combination of wavelength L-band Synthetic Aperture Radar (ALOS PALSAR), which is able to penetrate the sand, and multispectral optical images (Landsat 7). This paper develops a new strategy to help in the detection of suspected buried structures. The data fusion of surface roughness and spectral indices enables tackling the well-known limitation of SAR images and offers a set of pixels having an archaeological signature different from the manmade structures. The potential buried sites are then classified by performing a pixel-level unsupervised classification algorithm such as K-means cluster analysis. To test the performance of the proposed method, the results are compared with those obtained by visual interpretation

Spatial and temporal analysis of dust storms in Saudi Arabia and associated impacts, using Geographic Information Systems and remote sensing

Dust storm events occur in arid and semi-arid areas around the world. These result from strong surface winds and blow dust and sand from loose, dry soil surfaces into the atmosphere. Such events can have damaging effects on human health, environment, infrastructure and transport. In the first section of this PhD dissertation, focus on the suitability of the existing of five different MODIS-based methods for detecting airborne dust over the Arabian Peninsula are examined. These are the: (a) Normalized Difference Dust Index (NDDI); (b) Brightness Temperature Difference (BTD) (Band 31–32); (c) BTD (Band 20–31); (d) Middle East Dust Index (MEDI) and (e) Reflective Solar Band (RSB). This work also develops dust detection thresholds for each index by comparing observed values for ‘dust-present’ versus ‘dust-free’ conditions, taking into account various land cover settings and analysing associated temporal trends. The results suggest the most suitable indices for identifying dust storms over different land cover types across the Arabian Peninsula are BTD31–32 and the RSB index. Methods such as NDDI and BTD20 – 31 have limitations in detecting dust over multiple land-cover types. In addition, MEDI was found to be an unsuccessful index for detecting dust storms over all types of land cover in the study area. Furthermore, this thesis explores the spatial and temporal variations of dust storms by using monthly meteorological data from 27 observation stations across Saudi Arabia during the period (2000–2016), considering the associations between dust storm frequency and temperature, precipitation and wind variables. In terms of the frequency of dust in Saudi Arabia, the results show significant spatial, seasonal and inter-annual. In the eastern part of the study area, for example, dust storm events have increased over time, especially in Al-Ahsa. There are evident relationships (p < 0.005) between dust storm occurrence and wind speed, wind direction and precipitation. This thesis also describes the impact of dust on health, and specifically on respiratory admissions to King Fahad Medical City (KFMC) for the period (February 2015 – January 2016).This study uses dust data from the World Meteorological Or-ganization (WMO) for comparing and analysing the daily weather conditions and hospital admissions. The findings indicate that the total number of emergency respiratory admissions during dust events was higher than background levels by 36% per day on average. Numbers of admissions during ‘widespread dust’ events were 19.62% per day higher than during periods of ‘blowing dust’ activity. The average number of hospital admissions for lower respiratory tract infections (LRTI) was 11.62 per day during widespread dust events and 10.36 per day during blowing dust. The average number of hospital admissions for upper respiratory tract infections (URTI) was 10.25 per day during widespread dust events and 7.87 per day during blowing dust ones. I found clear seasonal variability with a peak in the number of emergency admissions during the months of February to April. Furthermore, qualitative evidence suggests that there is a significant impact on hospital operations due to the increase in patients and pressure on staffing and hospital consumables in this period. Taken together, these findings suggest the (BTD 31–32) and (RSB) are the most suitable indices of the five different MODIS-based methods for detecting airborne dust over the Arabian Peninsula and over different land cover. There are important spatial and temporal pattern variations, as well as seasonal and inter-annual variability, in the occurrence of dust storms in Saudi Arabia. There is also a seasonal pat-tern to the number of hospital admissions during dust events. This is research in-tended to fill the knowledge gap in the dust detection filed. Here I address the knowledge gap by evaluating the identified dust methods over the whole Arabian Peninsula and by considering different land cover. To my knowledge, this is the first study analysed the temporal trends in indices values considering dust and dust-free conditions. Previous work has only focused on 13 stations for analysing dust storms over Saudi Arabia. Therefore, this study has analysed the seasonal and inter-annual and spatial variation by using data from 27 observations in Saudi Arabia. This study addresses the relationship between dust storm frequency and the three meteorological factors (i.e. temperature, precipitation and wind variables) which have not yet been clarified in previous studies. In addition, this research fills the gap in the literature by investigating the correlation between different types of dust events such as (wide-spread dust and blowing dust) and their effects on the hospital admissions for upper and lower respiratory tract issues for pediatric in Riyadh city

Abstracting GIS Layers from Hyperspectral Imagery

Modern warfare methods in the urban environment necessitates the use of multiple layers of sensors to manage the battle space. Hyperspectral imagers are one possible sensor modality to provide remotely sensed images that can be converted into Geographic Information Systems (GIS) layers. GIS layers abstract knowledge of roads, buildings, and scene content and contain shape files that outline and highlight scene features. Creating shape files is a labor-intensive and time-consuming process. The availability of shape files that reflect the current configuration of an area of interest significantly enhances Intelligence Preparation of the Battlespace (IPB). The solution presented in this thesis is a novel process to automate the creation of shape files by exploiting the spectral-spatial relationship of a hyperspectral image cube. It is assumed that “a-priori” endmember spectra, a spectral database, or specific scene knowledge is not available. The topological neighborhood of a Self Organizing Map (SOM) is segmented and used as a spectral filter to produce six initial object maps that are spatially processed with logical and morphological operations. A novel road finding algorithm connects road segments under significantly tree-occluded roadways into a contiguous road network. The manual abstraction of GIS shape files is improved into a semi-automated process. The resulting shape files are not susceptible to deviation from orthorectified imagery as they are produced directly from the hyperspectral imagery. The results are eight separate high-quality GIS layers (Vegetation, Non-Tree Vegetation, Trees, Fields, Buildings, Major Buildings, Roadways, and Parking Areas) that follow the terrain of the hyperspectral image and are separately and automatically labeled. Spatial processing improves layer accuracy from 85% to 94%. Significant layer accuracies include the “road network” at 93%, “buildings” at 97%, and “major buildings” at 98%

Staple Economies and Social Integration in Northeast China: Regional Organization in Zhangwu, Liaoning, China

The emergence of specialized mobile herding is long been thought to have taken place in Northeast China during the Late Bronze Age (1200 to 600 BCE). It is theorized that the interaction between specialized herders and sedentary farmers was the catalyst for increased social complexity in the region. However, in Northeast China there is little direct settlement and subsistence evidence which appears to indicate the emergence of mobile pastoralism. Therefore, theories based on the interaction between herders and farmers remain tenuous. This research is designed to answer two questions. Did reliance on grazing animals and residential mobility increase in some Late Bronze Age communities located in areas where such subsistence strategies would have been attractive alternatives to grain cultivation under warming and drying conditions? Does such a subsistence shift, if documented, show the artifactual evidence and settlement patterning consistent with economic complementarity? This dissertation outlines the changes in settlement patterns of 173 square kilometer region from 4500 BCE to 1200 CE. The Early and Late Bronze Age (2000 to 1200 BCE and 1200 to 600 BCE) is given special attention because this is when this substantial economic change is thought to have taken place. During the Bronze Age locational evidence and use-wear evidence is taken in concert to evaluate the notion of Late Bronze Age specialized mobile herders either dominating the landscape or part of a settlement system which includes sedentary farmers. Results from this study call into question the emergence of specialized herders during the Late Bronze Age. Despite environmental conditions that would be conducive to herding economies and a warmer and dryer climate from the Early to Late Bronze Age, this dissertation finds evidence that local communities favored a mixed economy throughout the Bronze Age. The local environmental conditions tempered the degree to which communities carried out certain economic practices. However, economic specialization, which was previously thought to have characterized the region, does not appear to be at all consistent with the evidence

Urban-Rural-Partnerships

This is a reprint of the Special Issue “Urban-Rural-Partnerships: Sustainable and Resilient” in Land, which, based on the URP2020 objectives, invited original contributions dealing with interactions in regional systems, particularly between urban and rural actors, institutions and projects to tackle great societal challenges. The 16 contributions published included conceptual and methodological papers, as well as case studies dedicated to striking examples and providing transferable knowledge and solutions. The guest editors hope that the contributions will stimulate learning processes on various levels, i.e. cross- and transdisciplinary as well as from the local level to entire regions to the broader European and international levels, in order to foster an understanding of integrated regional and urban–rural development

Perception of Aquifer Depletion and the Effects of Land Use Change Across the Madaba Plain, Jordan

In Jordan, demand for water for agricultural purposes has put a high strain on aquifer resources. Water mining, erosion, and desertification have all increased as global temperatures rise. This along with fragmentation of the landscape have altered the environment in a profound way. The Madaba Plain was chosen for this study due to the agricultural activities that take place there, as well as the proximity to a number of population centers. The purpose of the study is to examine how fragmentation of irrigated landscape has affected the aquifers underneath, while taking into account perceptions of risk of the local population. Data for the study was acquired through a number of sources. Demographic and Likert Scale data were obtained by distributing written surveys that participants completed and returned. Remotely-sensed data were obtained from the USGS through the glovis.gov website for the years of 1991, 1998, 2002, and 2006. Finally, groundwater data were obtained from the Ministry of Water and Irrigation in Amman. The results of the study showed some surprising and unanticipated trends. Generally, the Likert scale answers had a low mean, and showed that respondents did not have much awareness about any of the hazards put before them. The awareness levels did demonstrate a geographic trend, where awareness generally increased from north to south. While landuse between the four time periods did not change significantly, depth to water measurements showed high variability. Analysis of continuity index for the study showed no significant relationships between fragmentation and water depth

Assessing the Emerging Environmental Concerns from Bio-originated Organic Pollutants in Cropping Systems

Agriculture plays a significant role in achieving the goal of carbon neutrality and emission reduction through practices such as crop residue management. Crop residues can be utilized to produce biodegradable mulches (BMs), which can increase crop production and carbon sequestration potential. However, agricultural health and safety are facing new challenges, particularly concerning bio-originated organic pollutants in cropping systems, including biogenic volatile organic compounds (BVOCs) and biodegradable microplastics (BMPs). The main purpose of the research presented in this dissertation is to assess these emerging environmental concerns, including the appropriate assessment of BVOC emissions and the degradation and fragmentation of BMs. BVOC emissions were generally influenced by various factors, including temperature, drought, solar radiation, humidity, nutrient availability, carbon dioxide (CO2), ozone (O3), etc. Among these factors, growth length, air temperature, solar radiation, and leafage were found to be the most important variables affecting the spatial-temporal variations of methanol (MeOH) emissions from spring wheat during the growing period in a Canadian province. The seasonality of MeOH emissions was positively correlated with concentrations of carbon monoxide (CO), filterable particulate matter (FPM), and coarse particulate matter (PM10), but negatively related to nitrogen dioxide (NO2) and O3. Compared with paper mulch, bioplastic mulch contributed a higher amount of aromatic structure-containing chemicals and carboxylic acids, to the water environment, but released fewer and smaller plastic particles. After entering the soil-water environment, the rough microstructure and oxygenated functional groups on BMP surfaces played a crucial role in the adsorption of aromatic compounds and heavy metals from soils. Scientometric analysis can provide researchers with an in-depth understanding of BVOC emission mechanisms, while also offering decision-makers insights into emission mitigation and environmental management. The newly developed BVOC assessment approach, designed to evaluate the biogenic MeOH emitted from crops during growing seasons, can help uncover the relationships between BVOC emissions and key influencing factors. The characterization and quantification of BMPs in cropping systems focused on examining the fragmentation and degradation of BMPs under UV irradiation using visual inspection and quantitative analysis. This dissertation offers scientific support for researching and further developing the impact of BVOC emissions and BMP generation on environmental management