Journal of RS and GIS for Natural Resources
Year:2017 | Volume:8 | Issue:2 (27)|Papers Count:8

Vulnerability assessment and vulnerability mapping, is an important strategy for management of karst water resources. Due to the geomorphology of developed karst in Dalahoo karst aquifers and in other natural conditions of the area, the spread of contamination in these karstic sources is rapid and extensive. Therefore, the purpose of this study was to provide a Dalahoo karstic aquifer vulnerability map in Kermanshah province against surface contamination using the COP model. According to the aforementioned approach, the COP method considers three factors to assess the resource vulnerability: Overlying layers (O), Concentration of flow (C) and Precipitation regime (P). After calculating three factors C, O, P and preparing their vulnerability map, these layers were multiplied and the final map of the vulnerability of the Dalaho karstic aquifer was calculated. The results show that 32.83%, 14.32%, 22.22%, 14.34% and 16.47% of the area are located in the very high, high, moderate, low and very low vulnerable zones and this classes have been 2222.88, 97.2, 147.49, 97.38 and 11.82 km2 of this area, respectively. Also, the results of vulnerability classes and their area indicate that 69.2% of the total area are located in the very high, high and moderate vulnerabilities, which indicates the high vulnerability of Dalahoo aquifer to contamination. The very high vulnerability zone with 222.88 Km2, has the largest area of the region.

Degradation model is a method for environmental impact assessment and it has been widely applied for accumulative impact assessment of human activities. In addition, landscape indicators have been widely used in landscape planning as quantitative tools.One important application of landscape metrics is their contribution to landscape degradation model. The goal of this research was to assess landscape degradation in Jajrood protected area. In doing so, landscape indicators were calculated using a land use/cover map of Jajrood protected area for 16 sub basins. For land use/cover mapping, Landsat satellite image was firstly pre-processed, and then, hybrid classification approach was undertaken to categorize the image into different land use/cover categories. According to landscape degradation model, ecological vulnerability and the severity of activities as well as the degradation degree were calculated for the targeted landscape. The results of this research indicated that sub basin 5 with a value of 31 had the highest level of landscape degradation and sub basins 1, 13 and 15 with values 25, 25 and 22, respectively, were on the next orders in Jajrood protected area. In addition, sub basins 16, 7 and 4 with values 3.5, 3.25 and 3.25, respectively, were least degraded and these sub basins had the least level of fragmentation. The results show that 68% of the area was outlined to be potential for development or further development, only 17% of the area is suitable for protection. Approximately 13% of the area should be considered for rehabilitation that demonstrated natural land cover change and degradation in the protected area.

In this research, artificial neural network, maximum likelihood and minimum distance classification methods for analysis of land use changes, during 1989 to 2015, were evaluated and compared images from three Landsat satellite sensors in Sari. After geometric and atmospheric corrections, images of 1989, 2002, and 2015 were categorized under three artificial neural network algorithms, maximum likelihood and minimum distance in five land use classes. After assessing the accuracy of the methods, the Kappa coefficients were calculated for maximum likelihood, artificial neural network and minimum distance of 1989 were 92%, 87% and 65% in 2002, were 89%, 87% and 60%, and in 2015 were 91% %, 90% and 73%, respectively. These coefficients indicate the superiority of the maximum likelihood method in comparison with the other two methods in 1989. Also, the results of land use change over the whole period of the survey (from 1989 to 2015), showed that the areas of residential and irrigated lands were increased by 3615 and 575 hectares, but bare lands, gardens and forests were decreased to 1791, 1127 and 1272 hectares, respectively. According to the results, the two methods of maximum likelihood and neural network were more suitable for land use classification. The maximum likelihood method was better than the neural network method with a difference of 5% in 1989 and 2% in 2002 and 1% in 2015 in the Kappa coefficient.

Prosopis cinerariais a native species in the south of Iran and it include of compatible species in this area. This species contains has been a wide distribution but discrete in the past, but it's limited regions in now. This research done in investigating possibility of plantation development for Mesquite (Prosopis cineraria) in Rahmatabad watershed of Rigan county, the East Kerman province. The aim of this study was to site location and identify suitable land for development and implementation of the ecological requirements of the species, according to the ecological characteristics of the study area in the East of the province. For this purpose, the method of multi-criteria evaluation has been based on Analytical Hierarchy Process. During this process were identified the natural characteristics and specific requirements of Mesquite and then calculate the weight of each characteristic by weighted analytic hierarchy process (AHP), the final map of the habitat area was prepared for the development of Mesquite trees. The results showed that the total area of 37286 ha, about 3423 ha of the land where good capability, 13521 ha the average capability, 17343 ha low capability and 2999 ha for the plantation of Mesquite has without capability. Using the results of this study can recognized prone areas of Mesquite using the MCE method in GIS and for the plantation of this species in places with good habitat can be planned in the future.

Population increase and excessive use of different water resources, has led to special attention to groundwater resources. In this study, the efficiency of frequency ratio model in groundwater potential mapping in Azna-Aligoudarz plain, Lorestan was investigated.The 11 effective groundwater potential factors, (altitude, lithology, curvature, slope, aspect, land use, distance from rivers, drainage density, fault distance, fault density, pedology, topographic wetness index; TWI) were prepared using GIS. The location of 370 wells in the study area with discharge more than 11 (m3/h) was choosed and were divided in two groups of training (70%) and validation (30%) wells. Then the layers of environmental variables were classified and based on the density of wells and frequency ratio model, the weight of each class was determined. Finally, the groundwater potential map was prepared based on the frequency ratio model. Validation of final map was performed using relative operating characteristic (ROC) method. The result shows that the generated groundwater potential map using frequency ratio with 72.1% accuracy value, showed the high ability of this model in groundwater potential mapping. The groundwater potential map of the region showed that classes with a low, moderate, high and very high potential have been estimated to be 210.79, 210.24, 210.29 and 209.24 km2, respectively.

Deforestation affects watershed processes and biochemical cycles and lead to soil erosion and lack of water in the catchment areas. This study is aimed to investigate the changes in forest land in the Chaloorood watershed on the west of Mazandaran province using Geomod. In this study, maps of forest in the years of 1987 and 2015 were prepared using satellite images. Then the suitability forest map was produced by making a regression equation between suitability criteria maps and forest changes map in the period of 1987-2015. Finally, by using forest map in 1987, forest suitability map and the number of modified pixels in forest land between 1987 and 2015, Forecast of the forest map for 2043 was done using Geomod. Also, by using the Validate function and classified forest map 2015, as a reference map, and the forecasting forest map 2015, as a comparative map, the validity of the production map was evaluated. The results showed that the area of forest land in 1987, 2015, and 2043 was 38683.65, 2464.354 and 15227.25 hectares, respectively. The extent of forest changes in the last 28 years and the next 28 years is 35.72% and 38.76% respectively. Forest changes in the period between 1987 and 2015 under the influence of factors such as distance from the road, forest cover density, distance from the village, slope and elevation above sea level, respectively. The Pseudo R2 and ROC coefficients are 0.29 and 0.85 respectively, which indicates the proper ability of the model to estimate forest changes over the past 28 years and the relative agreement of the model with the real changes. In this study the accuracy of resulting land use maps was 96%, which represent the appropriate capability of Geomod in land use changes modeling in Chaloosrood watershed.

Oak is the dominant forest species in the Zagros mountains, it is seen as a semi dense forest in western provinces. Multiple droughts, development of cities and villages, land use change from forest to farmland, are the main causes of forest destruction in Ilam.The purpose of this research is to determine the change detection of forest land to other land uses, using multi temporal TM sensor images (April 1986) and OLI (April 2015). In object-based classification, the data segmentation as initial phenomena, with appropriate scale and compression parameters for each image, was performed. Two classifying phenomena, nearest neighbor method and fuzzy functions were used. Land use classes were prepared by specifying training points and using the normalized difference vegetation index (NDVI). The Overall accuracy of the TM image was 88% and OLI image 94%, and the kappa coefficient for the TM and OLI image was calculated 84% and 91%, respectively. By post classification comparison method, the change matrix for each districts and changes forest to other uses was formed. The results showed that all districts faced with the phenomenon of deforestation and forest wide change (-42%) have been made.

According to the concept of desertification, which is land degradation in dry areas, the semi-arid, and dry sub-humid due to many factors such as climate change and human activities, this phenomenon has long been known as a serious problem in terms of economic, social, and environmental in many countries. In this study, by using a MEDALUS model the severity of land desertification in the western regions of Ahvaz was evaluated. Climate, vegetation, soil, and land use data are used as effective criteria in determining the severity of desertification. According to the MEDALUS model, each criterion entered the GIS environment as an information layer and after the data is processed, these criteria are weighted. By combining these criteria in raster formats, using geometric averaging, the Environmentally Sensitive Areas Index (ESAI) of the area is obtained. The results show that based on the MEDALUS model the area of the study contains four divisions; (C1) low, (C2) moderate, (C3) high, and (C4) very high critical. The results also showed that 11% of the area was in a low critical class, 30% in the moderate, 25% in high, and 29% of the very high critical class. A climate criterion with the index value of 2.6 has the greatest impact, which is due to strong winds and increasing number of storms and dusty days. Land use criterion with the index value of 1.5 has the minimal impact, which is due to inappropriate land use and implementation of desertification projects in the region.