Journal of RS and GIS for Natural Resources
Year:2012 | Volume:3 | Issue:3|Papers Count:9

Fakhrabad plain mainly affected by the phenomenon of desertification is caused by wind erosion. Physiographie’s situation caused the plain to become a wind channel and with restricted to zonal winds, region became focus of wind erosion. This study has been done in plain Fakhrabad aimed to determine the current status of desertification with emphasis on criteria of wind erosion. Since the wind erosion factors in MICD model define with more appropriate indices, therefore, this method was chosen. First, the working unit’s map to the region was prepared as the base map by combining information on topographic maps, geology, aerial photographs and field visits based upon this method. Then the current state of desertification was prepared with used of adding some indexes to each user and modify the model, assessment indicators of wind erosion and to collect points and use the table that maps. The result showed that 81.4% of the region (32061.58 ha) was in the middle class of desertification, 2.94% (1168.97 ha) in low, 15.1% (5962.4 ha) in an intensive class and 0.46% (180.75 ha) was in very comprehensive class.

Nowadays, air pollution is the main environmental challenge in metropolises. Therefore, it is essential to monitor and forecast air quality parameters in urban areas. It depends upon various factors, including topography, climate, population and transportation network. The relationship between these special factors has been considered as a dynamic, the nonlinear and ambiguous phenomenon. In this study, an adaptive Neuro –fuzzy system and GIS have been used to extract knowledge of environment from data, in terms of fuzzy rules. These rules were used to predict and model carbon monoxide (CO) pollutant concentration. Tehran has been selected as the case study. The data gathered from six meteorological stations, for four consecutive years in summer, in this city were used separately to train the neural network. Fuzzy rules (Sugeno and Mamdani) were extracted for each station and then, using these rules; pollutant concentration was estimated. Having concentration predictions at station points, log- Kriging was used to model the spatial concentration in the area selected as the case study. The results showed that average RMSE of all stations using Sugeno rules is 1.445 and using Mamdani rules is 1.374.

In this research, the effect of different grazing intensities has been done in steppe rangelands of Saveh, Markazi province by FAO method. Three sub-models, including forage production, water resources and soil erodibility were considered as the main components of the final model. This research has been done in steppe rangelands of Saveh, Markazi province, Iran. Four sites with the same ecological condition were selected. This research was done by FAO method. According to the results of the model sensitivity to erosion, studied ranges were classified in class S2 (Except in steep areas). The model of water resources, Nemati rangeland (moderate grazing intensity) and Sherali Baglu rangeland (high grazing intensity) were classified in class S1 Chaganeh rangeland (grazing intensity is relatively high) is located in S2. However, results from the production model showed excessive grazing and the presence of unpalatable plants and low production of rangeland in Sherali Baglu makes production suitability located in S3. These factors affect on final suitability so rangeland suitability located in S3. However, in Chaganeh rangeland each of the three factors was affected on rangeland suitability approximately the same. However high distance some parts within the range from the only source of water were causes low suitability of this part of the pasture. In Nemati, rangeland were not limited in favor of forage production and source of water. Utilization of rangeland based on grazing capacity, ranges over readiness and rehabilitation of degraded areas can improve the suitability of steppe rangelands.

Albedo is determined in new and old method based on SEBAL algorithm. In the new method that has been used since 2004, the extracting albedo was based on the experimental models. To determine the albedo of the object to the surface in large-scale and with consideration of the varied topography at the surface, the measurement of object’s albedo was impossible, thus they should use remote sensing methods. In this research, the surface albedo was determined by use of ETM+ and MODIS images and tries to compare the obtained results from these two devices in various land uses. To determine the abode, we used the following programs, ERDAS® 9.1 and ArcGIS® 10.1. The result of study shows the average albedo in agricultural land extracted from ETM+ and MODIS images are 0.186 and 0.344, respectively, that the lowest, between all land use categories the highest albedo belonged to watercourse land use with the 0.242.  Furthermore, the minimum albedo in follow agriculture in the ETM+ and MODIS image was 0.088, 0.274 and 0.374, 0.464 relatively. By determining albedo in different land use, we can determine the difference between net received energy and use it as one of the factors in determining the evapotranspiration with using the METRIC or SEBAL remote sensing algorithm.

The purpose of this study: It is to use Spatial Multi Criteria Method (SMCM) in the classification of the pollution in the environs of the Bander Imam Petrochemical Company (B.I.P.C) which it’s located vicinity of the Persian Gulf. For this purpose, physico-chemical parameters, organic matter and biodiversity indices sampling was performed in eight sites in the Mosa Creek in the warm and cold season, in September and February 2008. The distribution of pollution of the sites was evaluated by using SMCM and GIS tools. The result indicated that: Shannon’ s-weaver index has been significant correlate with dissolved oxygen (DO) and organic matter (OM). In addition, in a station near of the swage pollution biodiversity index, water quality and DO decrease and organic matter increased. However, very heavy pollution was observed according to the biodiversity index value in both seasons. The results of pollution division showed that in both seasons 1, 2, 3 and 5 stations (which are located at the sewage output) in pollutant confine, four stations in moderate confine and 6, 7, 8 stations located within a pollutant class. Furthermore, the results of water quality determine the base of Welch’s index indicated that 1, 2, 5 stations in both seasons, 362.95 ha (%7) and other stations in moderate pollution load, 4885.73 ha (%93) located in high and moderate pollution load, respectively.

The main aim of this study was the evaluation of the Forest Canopy Density Model for prediction of forest canopy density, using Landsat-7 ETM+. The study area was the eastern part of Marivan city that situated in Kurdistan province. A Landsat image was geo-referenced with sub pixel accuracy. First, all bands (1-5 of ETM+ imagery) except band 6 was normalized and then four main indices of FCD Model, including Advanced Vegetation Index, Bare soil Index, Shadow Index and thermal Index was calculated, and the forest canopy density map was derived finally. Forest’s canopy densities according to 6, 4 and three classes were classified. To assess the accuracy of classified maps, a ground truth map using aerial photos with the scale 1: 20000 was produced. The overall accuracy and kappa coefficient for classification 6 and four classes were obtained equal to 52%, 0.29 and 53%, 0.30, respectively. Spectral similarity between open density classes and irradiance of background soil in these classes reduced the accuracy as the result. Actually, in the dense forest, the result will be more accurate. According to the results, this method could be relatively desired for Zagro’s forests.

Karkheh reservoir dam as the biggest earth dam on the Middle East has influenced positively on its district in terms of plantation area and in addition has controlled devastating floods. This paper tries to evaluate the construction effects of this dam in the area by employing RS and GIS techniques and on this, basis presents some suggestions to economically improve the district. To reach this goal, three satellite images, which are dated to the periods of pre and post construction on the dam were acquired for the 1991, 2002 and 2008. Fusion, optimization and Geo referencing techniques were used and a normalized difference vegetation index (NDVI) was computed. Unsupervised classifications were utilized on the images two times to clarify the vegetation cover. In order to build a land use map in the downstream side of the dam, unsupervised classifications were also used in the method of maximum similarity. Finally, with utilizing the GIS software capabilities, the amount and the type of changes were calculated. The results have shown that agricultural areas in 2008 have increased about 390 km2 in comparison to 1991. The 50 percent decline in bare land, river land and sand dunes have also seen. Furthermore, in vegetated, residential and industrial areas increase of over 100 percent is observed. These results clearly reveal type, rate and manner of changes to the area with dam construction.

Industrial development, the possible environmental issues, sustainable and efficient use of land area’s all facilities, in order to be optimal to locate and the ecological potential within the region is one of the important issues that has been attention to the environment management. Therefore, present study attempts to suitable zoning for industrial developing according to the features and environmental conditions in order to regional planning balance and building the capabilities and environmental conditions. In this study, the weighting factors with using the paired comparison (AHP) after determination the ecological parameters that required during the analysis were done. Then at first stage of research, 15 information layers) soil texture, soil erosion, soil depth, climate, slope, aspect, elevation, mother rock, wells, reservoirs of water transfers, rivers, Fault, vegetation density, protected areas, land use) overlaying in GIS bases, on the other hand, protected areas and current land use throughout the study region were removed. The results showed that the East Azerbaijan has relative limits to industrial development and hasn’ t talent level 1 to industrial developing, while 21 percent include 9843 square kilometers of the province has the potential to develop category 2 and in the rest of province, 79% of the region, existent ecological and physiographical restrictions that should be considered in province planning.