Multi-temporal landsat images based on eco-environmental change analysis in and around Chah Nimeh reservoir,Balochestan (Iran)

Chah Nimeh reservoirs have served as a water storage facility, especially during droughts over the last three decades. It is also an important wintering site for migratory birds. In this study, thematic mapper time-series data were derived from Landsat images for prolonged droughts that occurred in two satellite images (2002 and 2011). The data derived from these images were used for the detection of changes in land cover and water storage in the reservoirs. First, a vegetation cover map was produced using soil-adjusted vegetation index and field sampling. Subsequently, land use/cover maps were generated using supervised and hybrid image classification method. Using the spatial change detector (SCD v1.0) software extension, the layers were combined and the change map was generated. The overall accuracy of the produced thematic images was assessed in regards to quantity and allocation disagreements. A total of five classes were defined in this investigation: deep water, shallow water, vegetation, salt land and bare land. The results showed that during the period of study, water volume reduced and vegetation cover increased, especially around the reservoirs that are important as shelter for wintering migratory birds. Comparison of land use/cover maps showed the increase in total available surface of shallow water, which indicated an increase in the habitats for surface feeding and diving birds.     

Evaluating Boolean,AHP and WLC methods for the selection of waste landfill sites using GIS and satellite images

The city of Saqqez has a population of 140,000 people, making it one of the largest cities in Iran. Population growth, consumerism, and change in eating habits, such as the increased use of packaged products, is causing the accumulation of waste in this city to increase. In this study, the selection of a waste landfill site for Saqqez focused on 13 layers of geography information that was used by the IDRISI and Arc GIS software. Different models of the analytic multi-criteria decision-making process, such as an analytical hierarchy process (AHP), weighted linear combination (WLC), and Boolean logic, were used to manage layers to establish specific databases for urban waste landfills. Satellite images (Landsat ETM⁺ and SPOT 5), proposed sites and a land use map of the study area were also used. The results of this study indicated that two methods (AHP and WLC) in the early stages had better decision-making powers for locating landfill sites when compared to Boolean logic. Overlapping and compounding the similarities between these models in Arc GIS software, a 74-ha site was found. This site will be able to accept 130 tons of waste per day for the next 20 years.     

A geospatial model for the optimization grazing management in semi-arid rangeland of Iran

Extensive livestock grazing even in unsuitable land has increasingly grown in most parts of semi-arid rangeland. Therefore, it is of paramount importance to identify suitable land for livestock grazing for optimum utilization while causing minimum impact to the environment. This paper adapted the schematic model based on the concepts presented by the Food and Agriculture Organization of suitability analysis for optimal grazing management in semi-arid rangeland in Iran. Factors affecting extensive grazing were determined and incorporated into the model. Semi-arid rangeland with variable such as climate and other agents were examined for common types of animal grazing and the advantages and limitations were elicited. Many ecosystem components affect land suitability for livestock grazing but due to time and funding restrictions, the most important and feasible elements were investigated. Within the model parameters, three submodels including water accessibility source, forage production, and erosion sensitivity were considered. Suitable areas at four levels of suitability were determined using geographic information systems. This suitability modeling approach was adopted due to its simplicity and the minimal time required for transforming and analyzing datasets. The most important reducing factors in model suitability were found to be: (a) land use and vegetation cover (in relation to soil erosion sensitivity), (b) the amount of the available forage in comparison with the total production, and (c) the existence of less palatability plants among the pasture plant species (forage production suitability). The results of the study would be beneficial to rangeland managers in devising measures more wisely to cope with the limitations and enhance the health and productivity of the rangelands.     

Monitoring rangeland ground cover vegetation using multitemporal MODIS data

The aim of the present research is to monitor changes in herbage production during the grazing season in the Semirom and Brojen regions, Iran, using multitemporal Moderate Resolution Imaging Spectroradiometer (MODIS) data. At first, various preprocessing steps were applied to a topography map. The atmospheric and topographic corrections were applied using subtraction of the dark object method and the Lambert method. Image processing, including false-color composite, principal component analysis, and vegetation indices were employed to produce land use and pasture production maps. Vegetation sampling was carried out over a period of 4 months during June–September 2008, using a stratified random sampling method. Twenty random sampling points were selected, and herbage production was estimated and verified with the double-checking method. Four MODIS data sets were used in this study. The models for image processing and integrating ground data with satellite images were processed, and the resulting images were categorized into seven classes. Finally, the land covers were verified for accuracy. A postclassification analysis was carried out to verify the seven class change detections. The results confirmed that Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) maps had a close relationship with the field data. The indices produced with shortwave infrared bands had a close relationship with field data where the ground cover and yields were high. The R ² value observed was 0.85. The changes in the pasture vegetation were high during the growing season in more than 90 % of the pastures. During the growing season, most changes in the pastures belonged to class 5 and 2 in the NDVI and SAVI index maps, respectively.     

Transverse oscillations in solar spicules induced by propagating Alfvénic pulses

The excitation of Alfvénic waves in solar spicules by localized Alfvénic pulses is investigated. A set of incompressible MHD equations in the two-dimensional x–z plane with steady flows and sheared magnetic fields is solved. Stratification due to gravity and transition region between chromosphere and corona is taken into account. An initially localized Alfvénic pulse launched below the transition region can penetrate from transition region into the corona. We show that the period of the transversal oscillations is in agreement with those observed in spicules. Moreover, it is found that the excited Alfvénic waves spread during propagation along the spicule length, and suffer efficient damping of the oscillations amplitude. The damping time of the transverse oscillations increased with decreasing k _b values.