RESUMO
Accurate and up to date land use and land cover (LU/LC) changes information is the main source to understanding and assessing the environmental outcomes of such changes and is important for development plans. Thus, this study quantified the outlines of land cover variation of 10-years in the northwestern costal land of the Red Sea, Saudi Arabia. Two different supervised classification algorithms are visualized and evaluated to preparing a policy recommendation for the proper improvements towards better determining the tendency and the proportion of the vegetation cover changes. Firstly, to determine present vegetation structure of study area, 78 stands with a size of 50 × 50 m were analysed. Secondly, to obtain the vegetation dynamics in this area, two satellite images of temporal data sets were used; therefore, SPOT-5 images were obtained in 2004 and 2013. For each data set, four SPOT-5 scenes were placed into approximately 250-km intervals to cover the northwestern coastal land of the Red Sea. Both supervised and non-supervised cataloguing methods were attained towards organise the study area in 4-major land cover classes through using 5 various organizations algorithms. Approximately 900 points were evenly distributed within each SPOT-5 image and used for assessment accuracy. The floristic composition exhibits high diversity with 142 species and seven vegetation types were identified after multivariate analysis (VG I: Acacia tortilis-Acacia ehrenbergiana, VG II: Acacia tortilis-Stipagrostis plumosa, VG III: Zygophyllum coccineum-Zygophyllum simplex, VG IV: Acacia raddiana-Lycium shawii-Anabasis setifera, VG V: Tamarix aucheriana-Juncus rigidus, VG VI: Capparis decidua-Zygophyllum simplex and VG VII: Avicennia marina-Aristida adscensionis) and ranged between halophytic vegetation on the coast to xerophytic vegetation with scattered Acacia trees inland. The dynamic results showed rapid, imbalanced variations arises between 3-land cover classes (areas as urban, vegetation and desert). However, these findings shall serve as the baseline data for the design of rehabilitation programs that conserve biodiversity in arid regions and form treasured resources for an urban planner and decision makers to device bearable usage of land and environmental planning.
RESUMO
The ability of the native emergent macrophytes Typha domingensis for monitoring pollution with trace metals in Egyptian Lake Burullus was investigated through developing regression models for predicting their concentrations in the plant tissues. Plant samples (above-ground shoot and below-ground root and rhizome) as well as sediment samples were collected monthly during one growing season and analyzed. The association of trace metals concentration with several sediment characteristics (pH, organic matter, clay and silt) was also studied using the simple linear correlation coefficient (r). The concentration of some trace metals was significantly proportional to its values in the sediment such as Cd in the shoot, rhizome and root, Fe in the rhizome, and Ag in the root. There was positive relationship between the bioaccumulation factor (BAF) of Ag, Cd, Fe, Pb and Zn and sediment pH, organic matter and clay content. The developed regression models were significantly valid with high model efficiency and coefficient of determination, and low mean normalized average error. Trace metals were accumulated in the below-ground root and rhizome rather than in the shoot. Only Ag, Co and Ni provided bioaccumulation factor (BAF) < 1, while Ag was the only trace metal that could be transferred to some extend from the root to the rhizome and from there to the shoot [translocation factor (TF) 2.55 and 1.15, respectively]. Typha domingensis in Lake Burullus could be regarded as a bioindicator of trace metals pollution, and a good candidate as phytoremediator for Ag. The information on the phytoremediation capacity of T. domingensis certainly helps to solve contamination problems at Egyptian Lake Burullus region using this native plant.
