Monitoring of drought and vegetation change is one of the most important solutions for natural resource management. Nowadays, satellite images are used as a low-cost and fast method for vegetation study in different scales. Vegetation change is assessed using spectral characteristics. The aim of this study is to analyze and monitor the changes of vegetation cover in 4 rangelands and one forest type in in south of Esfahan and southeast of Chaharmahal and Bakhtiary in 1999-2009. To measure the vegetation change, 5 Landsat images were prepared in first half of Khordad.

Gavkhouni playa as a Quaternary heritage in Iran, has experienced various climate events and is geomorphologically an important region. It is the deepest area in the Zayanderood watershed in Esfahan province. Due to presence of Gavkhouni wetland and sand dunes in the playa, ecotourism is an important activity. It is clear that a healthy and watery lake can support a high density of vegetation cover and conserve groundwater levels in the coastal regions.

The study of desert dust, its entrainment, transport and deposition is an area of growing importance in investigations of global environmental change because dust storms have great significance for the physical environment and the world’s human inhabitants. Most dust events are generated by the erosion of surface materials in the world’s drylands. Dry, unprotected sediments in any environment can be blown into the atmosphere, but the main sources of soil-derived mineral dust are located in desert regions.

Continuous decline of groundwater quality for agricultural purposes has become a major concern in extensive arid and semi-arid regions; therefore, mapping the quality of groundwater in a broad scale is an essential step in land management. This study aimed to map spatial distribution of two importantant groundwater quality indices including EC and SAR in Isfahan province, Iran, using geostatistical techniques.

Abstract

Introduction

 City parks have high recreational values and can be a surrogate for nature for the low-income citizens. In this study the impacts of green space parameters (richness, diversity and density of woody species) on bird species richness and diversity was assessed in 25 city parks in Isfahan.

Material and methods

The increased populations in the world, the growing need for energy and the indiscriminate use of fossil fuels have entered deleterious effects on living organisms and their environments. Renewable energies that do not have a limited life can be considered to be an adequate replacement for fossil energy. Geothermal energy is considered as a kind of renewable energy can meet the needs of increasing demand for energy now and in the future due to its excellent advantages such as relative safety, helping to the environment and cheapness.

Desertification is one of the main environmental and also social and economic problems facing Iran. Seventeen out of 31 Iranian provinces, which are home to approximately 70% of the total population, are affected by Desertification. This study aimed to use GIS and fuzzy logic for mapping environmentally sensitive areas (ESAs) to desertification based on MEDALUS approach in Isfahan province, central Iran.

This study aimed to compare the performance of pixel-based (vegetation indices, VIs) and subpixel-based (spectral mixture analysis, SMA) methods in mapping rangeland vegetation cover in Semirom region, Isfahan Province. First, the 2009 Landsat TM data was geometrically and radiametrically corrected. Then, the percentage of canopy cover was determined using step-point technique in radial direction in 30 sampling sites.

Sand dunes of Gavkhouni (Varzaneh Erg) are active and semi – active dunes in the southeast of Isfahan province and west of Gavkhouni international wetland. They play key role in increasing dust storms and causing damages to roads in the region.

This study aimed to evaluate the performance of TM satellite data acquired in June 2009 to map soil salinity in southeastern area of Isfahan province. Ground salinity data (EC) was measured in samples collected within 9 pixels, covering an area of approximately 8100 m² using stratified random sampling technique at 53 sample sites. Spectral indices including TM bands, BI, SI1, SI2 and SI3, PC1, PC2, PC3 and also multiple linear regression modeling and maximum likelihood classification techniques were applied to the geometrically corrected image.