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Showing 3 results for Principal Components Analysis
Factors Affecting Establishment of Four Halophytic Species in Northern Gavkhoony Habitat Using Ordination Method
S. A. Maybodi, A. R. Amini Hajiabadi, J. Khajeddin,
Volume 6, Issue 2 (7-2002)
Abstract

A number of halophytic species as Salicornia europea, Halocnemum strobilaceum, Aeluropus lagopoides, and Aeluropus littoralis were found to occupy a significant portion of the total vegetation of the surrounding area at the Zayande-Roud inlet to Gavkhoony wetland. However, their ecological demands and bioenvironmental factors by which vegetation community composition has been affected is not undestood. A compehensive knowledge of the establishment is essential for future improvements in using the above species on salanized regions. In this paper, using the ordination method. The establishment pattern of  these four species in a range of varied habitats is evaluated based on the recongition of the relative  significance of habitat soil chemical properties and vegetion crown cover to the establishment of the four species. For this purpose, 48 plants meansurements were taken along a transect, having more species variation in term of vegetation cover percentage. Furthermore, 48 soil samples were taken from the plot along the same transect in a one-year period in 1999. The soil samples were analysed for PH, EC, available Na, K, Ca and Mg as well as clay, and silt contents. The ground and field vegetation data were analysed using the Principlas Components Analysis (PCA), and Canonical Correspondence Analysis (CCA) to produce summary vectors (PCA axes) of both the soil chemistry and habitat vegetation structure datasets. The summary of ordination method quantified the degree to which soil variables and species cover were related to variability in ground vegetation composition. variation in community composition (type and percentage) was significantly related to gradient of the aforementioned soil factors. Generally, the vegatation community composition in this experiment could be considered as a key component to expand the growth and development patterns of these species to similar salinised regions. 


Determintion of Effective Wells to Monitor the Ground Water Level Using the Principal Components Analysis
Mohammad Hossein Noori Gheidari,
Volume 17, Issue 64 (9-2013)
Abstract
In order to monitor the changing water table in the field, determination of the main sampling points is very important to reduce sites and save time and cost. Principal Component Analysis (PCA) is one of the data reduction techniques used to extract the important components that explain the variance of a system. In this paper, the PCA was used to identify the effective wells of Qheidar Aqufer, Zanjan, to determine the groundwater level and remove the less important ones. From the study region which an area of about 920 km2, 48 wells (sites) were investigated. Using PCA, the relative importance of each well was calculated between 0 (for completely ineffective well) to 1 (for the very effective wells). The study showed the elimination of wells whose relative importance was less than 0.5 (i.e. half the total number of wells), coefficient of variation of groundwater level relative to the use of all wells did not greatly increase, and the error to determine the level of groundwater was less than 13 percent.
Investigating the Effect of Soil Properties on Soil Erosion at Suborder Level Using PCA (A Case Study: Ardabil Plain)
Sh. Ahmadi-Qolidaraq, A. Abbasi-Kalo, A. Esmali-0uri,
Volume 23, Issue 4 (12-2019)
Abstract
Soil is one of the most important natural resources of countries in which erosion occurs. In this research, the effect of soil characteristics on the amount of erosion at the suborder level was studied. For this purpose, 77 soil samples (0-30 cm) were prepared and the parameters were determined in the laboratory. The semi-variograms of soil parameters and their spatial distribution maps were prepared with GS+ and GIS, respectively. The study area was divided into work units by combining land use and geology maps and water erosion was estimated at each unit by the EPM method. By drilling profiles in different parts of study area, soil suborders were determined by Soil Taxonomy and the average values of parameters in each suborder was estimated. The principle components analysis (PCA) was then used for data analysis. The results showed that three parameters of silt, organic carbon and electrical conductivity could account for 30.384% as the first main component; clay, sand and vegetation could explain 11.189% as the second main component; and slope and height covered 15.330% as the third main component; in total, 63.805% percent of erosion variation could be justified by three main components. The lowest and highest amounts of erosion (69.12 and 343.57 m3/km2, respectively) were estimated in Xeralfs and Fluvents suborders. The erosion class of suborders at the study area was determined to be “few” and “medium”.

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