Showing 2 results for Spatial Pattern
A Soffianian, S Maleki Najafabadi, V Rahdari,
Volume 13, Issue 49 (10-2009)
Abstract
Landscape ecology as a modern interdisciplinary science offers new concepts, theories, and methods for land evaluation and management. One main part of landscape ecology is describing patterns in the landscape and interpreting the ecological effects of these patterns on flora, fauna, flow of energy and materials. Landscape studies require methods to identify and quantify spatial patterns of landscape. Quantification of spatial patterns is essential to understand landscape functions and processes. Landscape indices as diversity and naturalness can provide quantitative information about landscape pattern. Remote sensing and GIS techniques have high ability for landscape researchers to specify, map and analyze landscape patterns. The objectives of the research include mapping and quantifing diversity and naturalness indices for Mooteh wildlife refuge by land use/land cover map derived from remote sensing images. Finally, diversity and naturalness were classified in 4 and 6 classes, respectively. Results showed that the intermediate and high diversity classes (class 1 & 2) have occupied the largest area in the study area. Among naturalness classes, class 1 which represents the high level of naturalness has taken the largest area in Mooteh W.R.
H. Karimi, A. Fotovat, A. Lakzian, Gh. H. Haghnia, M. Shirani,
Volume 18, Issue 68 (9-2014)
Abstract
In recent years, due to the increased population, urbanization and changes in human consumption patterns, urban, industrial and agricultural soils have been exposed to various pollutants such as heavy metals. The objective of this research was to identify hotspots of Pb by using global and local Moran Indices in urban and suburban soils of Kashafrood catchment. A total of 261 surface soil samples (0-15 cm deep) were taken using irregular girding network method and their total Pb concentrations were measured. The positive Moran index at confidence level of more than 99 percent showed the spatial clusters between observations. On the basis of local Moran index results, 15 samples were introduced as hotspots (high-high value) located southeast of Mashhad plain. Exclusion of extreme values resulted in the addition of high-high cluster (hotspots) leading to the extension of these areas to the West of the Mashhad city.
These areas are introduced as hotspots due to the urban land use, the direction of prevailing wind, and the area being close to Mashhad airport.
