Use of remote sensing data in assessment land cover changes, land use patterns and land capabilities in AL-Qassim region, Saudi Arabia

© 2017 by International Journal of Ecology & Development. The Qassim region of central Saudi Arabia is one of the most important agricultural regions in the country especially for date cultivation. In the present study, Land sat TM and ETM+ data for the period 1999-2013 are used to study the land use, land cover changes in the area. Satellite images from path/row 168/042 constitute the study area. Three major land use/land cover classes are considered: hilly areas (364,407 ha), vegetated land (1,776,698 ha), and sand dunes (1,523,669 ha). The vegetated land constitutes the class 1, which is comprised of the wades mainly devoted used for for date production. Sand dunes are designated the class 11 and covered a large portion of the study area whereas the Hilly areas are unproductive and constitute as class 111.The vegetative land are surrounded by sand dune which is the most fragile system of the area and leads to damage some productive lands in the area. It is necessitates to study the area for suitable land management practices and for possible approach to stop the sand drifting or sand encroachment in the area. The land use capabilities classification of the study area includes three main classes: LUC I, LUCII, and LUC III. Slopes ranging between 0°and 20°correspond to areas that areflat, gently undulating, undulating, rolling, strongly rolling, moderately steep and steep, respectively. The slope categories dictate the usage patterns of the lands in the study area, which range from suitable to unsuitable to productive lands

Suprasubduction-zone origin of the podiform chromitites of the Bir Tuluhah ophiolite, Saudi Arabia, during Neoproterozoic assembly of the Arabian Shield

The ultramafic section of a dismembered ophiolite is exposed at Bir Tuluhah, in the north-central part of the Arabian Shield. It is penetratively serpentinized and locally carbonate-altered to talc‑carbonate and quartz‑carbonate rocks (listvenite) along shear zones and fault planes. Despite the high degree of mineral replacement, preserved mesh and bastite textures and fresh relics of primary Cr-spinel and olivine show that the protoliths were mainly harzburgite with minor dunite, with sparse massive chromitite bodies of various forms and sizes. Olivine inclusions in the chromitite lenses have higher forsterite content and NiO concentrations than fresh olivine relics in the host harzburgites and dunites, due to subsolidus re-equilibration. Cr-spinels in the chromitites have higher Cr# (0.74–0.82) than those hosted in dunite (0.72–0.76) or harzburgite (0.55–0.66). The scarce Cr-spinel crystals in harzburgite that have Cr# < 0.6 are interpreted to represent the population least affected by melt-rock interaction. The chromitite bodies are interpreted to have formed just below the contact between the oceanic crust and mantle sections (i.e., the petrologic Moho). The primary olivine (high Fo and Ni content) and Cr-spinel core compositions (high Cr# and low TiO2 content) of the Bir Tuluhah serpentinized peridotite are typical of modern supra-subduction zone (SSZ) fore-arc peridotites and consistent with crystallization from boninitic magma. The multistage petrogenesis leading to the chromitite bodies begins with moderate to high degrees of melt extraction from the protoliths of the serpentinized harzburgites, followed by reaction with melt compositions that evolved from tholeiite to boninite and left dunite residues. The massive Cr-rich chromitites in the Bir Tuluhah ophiolite are most probably the residues of such interaction between depleted harzburgite and ascending melts; mixtures of the reacted melts formed boninites, which became saturated with chrome-rich spinel and crystallized chromite pods before ascending past the Moho. We offer a novel thermodynamic model of this mixing and reaction process that quantifies the yield of Cr-spinel

Risk assessment through evaluation of potentially toxic metals in the surface soils of the Qassim area, Central Saudi Arabia

© Società Geologica Italiana, Roma 2016. Metal pollution is an increasing environmental problem worldwide, especially in regions undergoing rapid development. The present work highlights the extent of metal pollution in the central part of Saudi Arabia, which is currently experiencing significant agricultural development. The study determined concentrations of Hg, Cd, Zn, As, Mo, Cu, Pb and Cr in surface soils, assessing the level of pollution and potential ecological risks using soil quality guidelines, the geo-accumulation index (Igeo), the Hakanson potential ecological risk index (RI) and standard statistical analysis methods. Overall, the mean potential ecological risk values of metals in the surveyed soils display the following decreasing trend: H

Vegetation trends and dynamics in Shada Mountain, Saudi Arabia, (1984–2023): insights from Google Earth Engine and R analysis

This research analyses the long-term vegetation trends in Shada Mountain across six elevation zones, utilizing Landsat 5, 7, 8, and 9 imageries processed via Google Earth Engine and R. The study managed differences in images resolution through meticulous calibration and image processing techniques. The study is structured around two objectives: examining the relationship between vegetation and its proximity to streams and land surface temperature and analyzing trends in the Normalized Difference Vegetation Index (NDVI). Regression analysis revealed a negative correlation between vegetation and proximity to streams in lower zones (1–3), with no significant effect in higher zones (4–6). NDVI trend analysis indicated an overall increase in vegetation across most zones, with the exception of zone 5, which displayed a negative trend (slope −0.0025). The findings reveal that the decline is particularly pronounced among key tree species such as Ficus cordata subsp. salicifolia and Acacia asak, suggesting potential impacts from climate change and land use alterations. These zone-specific insights deepen our understanding of the dynamic ecological processes in semi-arid environments and guide targeted environmental management and conservation efforts

Assessment of Heavy Metal Contamination in the Soils of the Gulf of Aqaba (Northwestern Saudi Arabia): Integration of Geochemical, Remote Sensing, GIS, and Statistical Data

Ghrefat, H.; Zaman, H.; Batayneh, A.; El Waheidi, M.M.; Qaysi, S.; Al-Taani, A.; Jallouli, C., and Badhris, O., 2021. Assessment of heavy metal contamination in the soils of the Gulf of Aqaba (Northwestern Saudi Arabia): Integration of geochemical, remote sensing, GIS, and statistical data. Journal of Coastal Research, 37(4), 864872. Coconut Creek (Florida), ISSN 0749-0208. Rock and soil sample geochemical analysis was conducted to investigate the extent and causes of soil contamination in the Gulf of Aqaba region in NW Saudi Arabia. The inductively coupled plasma mass spectrometry was used to determine the concentrations of Pb, Zn, Cu, Co, Cr, Mn, Fe, Hg, Mo, and Cd in 23 soil samples and 25 samples from granitic and Cenozoic marine sedimentary formations. The geochemical results have been integrated with remote sensing, GIS, and statistical analysis to assess the severity of soil pollution in the area. The concentrations of heavy metals (ppm) in the collected soil samples were as follows: Fe (2259.70), Mn (101.85), Zn (20.15), Pb (10.74), Cr (8.67), Cu (6.10), Co (1.35), Mo (0.69), Hg (0.30), and Cd (0.17). A significant variation in the mean metal concentrations was observed for the rock samples. The correlation analysis results showed that different degrees of positive and negative relationships exist among different metals in the area. Two factors (PC1 and PC2) were identified using the principal component analysis (PCA) and were responsible for about 60% of the total variance in the data. The studied metals were separated and classified into two factors based on their geochemical features and source. In contrast, the hierarchical cluster analysis grouped the identified metals into different groups based on the similarity of their characteristics. The principal component (PC2) applied to the Sentinel-2A image classified the land cover in the area into three classes: vegetation, barren rocks, and urban area. The enrichment factor shows a relatively higher percentage of enriched Mo; however, the indices of geo-accumulation and potential ecological risk generally reveal no substantial metallic contamination in the study area. The main sources of soil contamination with metals are rock-weathering processes and various agricultural works that are widely practiced in the area

Delineation of Copper Mineralization Zones at Wadi Ham, Northern Oman Mountains, United Arab Emirates Using Multispectral Landsat 8 (OLI) Data

© Copyright © 2020 Howari, Ghrefat, Nazzal, Galmed, Abdelghany, Fowler, Sharma, AlAydaroos and Xavier. Copper deposits in the ultramafic rocks of the Semail ophiolite massifs is found to be enormous in the region of northern Oman Mountains, United Arab Emirates. For this study, samples of copper were gathered from 14 different sites in the investigation area and were analyzed in the laboratory using the X-ray diffraction, GER 3700 spectroradiometer, and Inductively Coupled Plasma-Mass Spectrometer. Detection and mapping of copper-bearing mineralized zones were carried out using different image processing approaches of minimum noise fraction, principal component analysis, decorrelation stretch, and band ratio which were applied on Landsat 8 (OLI) data. The spectra of malachite and azurite samples were characterized by broad absorption features in the visible and near infrared region (0.6–1.0 µm). The results obtained from the principal component analysis, minimum noise fraction, band ratio, decorrelation stretch, spectral reflectance analyses, and mineralogical and chemical analyses were found to be similar. Thus, it can be concluded that multispectral Landsat 8 data are useful in the detection iron ore deposits in arid and semi-arid regions

Multivariate statistical analysis of urban soil contamination by heavy metals at selected industrial locations in the Greater Toronto area, Canada

A good understanding of urban soil contamination with metals and the location of pollution sources due to industrialization and urbanization is important for addressing many environmental problems. The results are reported here of an analysis of the metals content in urban soils samples next toindustrial locations in the Greater Toronto Area (GTA) in Ontario, Canada. Theanalyzed metals are Cr, Mn, Fe, Ni, Cu, Zn, and Pb. Multivariate geostatistcalanalysis (correlation matrix, cluster analysis, principal component analysis) is used to estimate soil chemical content variability. The correlation matrix exhibits a positive correlation with Mn, Fe, Cu, Zn, Cd, and Pb. The principal component analysis (PCA) displays two components. The first component explains the major part of the total variance and is loaded heavily with Cr, Mn, Fe, Zn,and Pb, and the sources are industrial activities and traffic flows. The second component is loaded with Ni, and Cd, and the sources could be lithology andtraffic flow. The results of the cluster analysis demonstrate three major clusters: 1) Mn-Zn, 2) Pb-Cd-Cu and Cr, 3) Fe-Ni. The geo-accumulation index and the pollution load index are determined and show the main I geovalues to be in the range of 0-1.67; the values indicate that the soil samples studied for industrial locations in the GTA are slightly to moderately contaminated with Cr, Fe, Cu, Zn, and Cd, and moderately contaminated with Pb,while Ni, and Mn fall in class "0". Regarding the pollution load ingindex (PLI), the lowest values are observed at stations 6, 7, 9, 10, 11, 12,25, 27 and 28, while the highest values are recorded for stations 1, 5, 6, 13,14, 16, 17, 18, 20, 22 and 24, and very high PLI readings are seen for stations 5, 13, 16, 17, 18, 22 and 24. These data confirm that the type of industries, especially metallurgical and chemical related ones, in the study area, in addition to high traffic flows, are the main sources for soil pollution in the GTA

Hyperspectral and multispectral studies of evaporite minerals at White Sands, New Mexico

Most multispectral sensors such as Landsat 7 ETM+, ASTER, and ALI measure reflected energy in a few and separated wavelength bands and are thereby referred to as multispectral. In contrast, hyperspectral imaging spectrometers have a sufficient amount of continuous spectral channels to resolve the spectral variability of the earth\u27s surface. This study focuses on uncovering the spectral complexity of Alkali Flat and Lake Lucero, White Sands. They are remnants of Lake Otero and together form the primary source of gypsum that forms the dune field of the White Sands. One of the goals of this study was to compare the information dimensionality limits of Landsat 7 ETM+, ASTER and ALI data with high spectral resolution, low signal-to-noise Hyperion data, using AVIRIS data as a high spectral resolution, high signal-to-noise standard. Information dimensionality thresholds constrain the number of evaporite mineral and textural endmembers that can be detected, mapped, or unmixed using standard image processing methods. In this case, eigen analysis of the Minimum Noise Fraction (MNF) transformation and Principle Component Analysis (PCA) results were used to uncover the information dimensionality limits of all these datasets. The Pixel Purity Index (PPI), and n-D Visualization were used to identify spectrally distinct endmember classes, and along with ground truth and field spectra provide insights into the origin of the spectral variability uncovered in all of the datasets. The results confirm that AVIRIS and Hyperion data have higher information dimensionality thresholds exceeding the number of available bands of Landsat 7 ETM+, ASTER, and ALI data. AVIRIS has higher information dimensionality thresholds than Hyperion because of its 410x increase in signal-to-noise over Hyperion. Much of the information dimensionality uncovered by AVIRIS and Hyperion datasets can be due differences in vegetation landcover, grain size variations, and moisture contents as opposed to mineral compositional variations. These endmember components uncovered at Alkali Flat and Lake Lucero include: (1) dry gypsum, (2) wet gypsum, (3) water, (4) vegetation, and (5) clastic sediment dominated by ferric iron and calcite. The spectral signatures of these endmembers at the resolution of AVIRIS, Hyperion, ALI, ASTER, and Landsat 7 ETM+ agreed with field and laboratory spectral analysis. (Abstract shortened by UMI.

Reflectance spectroscopy and ASTER mapping of aeolian dunes of Shaqra and Tharmada Provinces, Saudi Arabia: Field validation and laboratory confirmation

Spatial variability of grain sizes and mapping of aeolian dunes is important to study the sand erosion, transport, and dune movement and to understand the dune encroachment and land degradation. This study examines the grain size statistical parameters and mineralogical composition of 68 sand samples collected from 17 crescentic dunes and assesses the source and depositional environment of these dunes. The analyses of samples for grain sizes resulted that the sands are characteristics to fine with an average size of 2.28 Φ and classified as moderately well-sorted(0.59 Φ), mesokurtic (0.97 Φ), and fine to coarsely skewed (0.14 Φ). X-Ray Diffraction shows that the dunes are deposited mainly by quartz, calcite, and haematite. The occurrence of absorption features near 0.5, 0.9, and 2.22 μm confirm the presence of such iron and aluminosilicate minerals in the dunes. The dunes of the provinces were mapped using TIR bands of ASTER satellite data by Carbonate index (CI) and Quartz index (QI). A good agreement among the results of grain size analyses, spectral measurements, mineralogical studies, and mapping of dunes with the field observations suggests that the sand deposits in the study area have a diversity of sources in the aeolian environment.This project was supported by King Saud University, Deanship of Scientific Research, College of Science Research Center