Since climate has a major impact on dust generation, hence, it is essential to identify the climatic parameters affecting this phenomenon. In this study, climatic parameters including temperature, relative humidity, rainfall, maximum wind speed and direction were selected and their relationships with visibility data and also dust storm days (recorded at meteorological stations) were analyzed in monthly and yearly scales using multivariable linear regression. Results showed that the number of dust storm days has reached to 366 days in last five years.

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Modeling and prediction of land use/cover changes is an essential need for planning sustainable use of land in country like Iran with its high level of changes in land uses and land covers. This study aimed to analyze the capability of CA Markov prediction model and Landsat satellite images for land use/cover change detection within the framework of “Iran at 1404 prospective” in Esfarayen region, North Khorasan province for year 2025. The results of CA Markov modeling showed a reduction about 5000 and 400 ha in irrigated agricultural lands and rangeland class in 2025, respectively.

One of the major indirect effects of artificial watering points in a grazed landscape is the development around them of a zone of extreme degradation called a piosphere.

Vegetation indices are widely used for assessing and monitoring ecological variables such as vegetation cover, above-ground biomass and leaf area index.

According to the studies conducted in northern Khorasan province, land use changes is one of the most effective factors in desertification of the region. In this province, lack of accurate and updated information for land use mapping and change detection analysis is a major issue. Therefore, the aim of this study was to map and monitor land use changes in Esfarayen region, northern Khorasan province over 36 years. For this purpose, Landsat satellite images of two periods including 1973 and 2009 were selected, geometric and radiometric corrections were applied.

Satellite images are currently used as a fast and low-cost solution for rangeland assessment. In this study, 10 vegetation indices from different groups were calculated using spectral bands. The correlation of these vegetation indices with canopy cover was then measured for three vegetation types in Semirom region, Isfahan. The percentage of canopy cover and other earth surface components such as litter, rock, gravel, stone and bare ground was determined using step-point method.

Functionality of rangeland landscape determines the ability of ecosystem to conserve or lose vital resources such as water, soil and organic matter. Therefore, the functionality of rangeland is highly related to its vegetation cover. This study aimed to analyse the applicability of a Cover Directional Leakiness Index, CDLI, in rangeland functionality assessment of a Steppe zone, using satellite imagery in a case study in Soh region, Isfahan, Iran.

This study aimed to use a remotely-sensed spectral diversity index called Moving Standard Deviation Index (MSDI) for identifying and assessment of degraded and non-degraded rangelands based on landscape heterogeneity. According to the utilization of rangelands, three sites including reference site (Sarygol National Park), medium grazed site, and over-grazed site with a sampling area of 100 pixels and with similar vegetation, soil type and landform were selected in North Khorasan province.

Vegetation indices are widely used for assessing and monitoring ecological variables such as vegetation cover, above-ground biomass and leaf area index.