فصلنامه سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی
سال دهم شماره 2 (تابستان 1398)

Wetlands are one of the most important natural ecosystems that due to climate changes and recent droughts, their moisture levels have been reduced. The purpose of this study was to investigate the relationship between the Standardized precipitation, drought index  (SPI) and Standardized precipitation-evapotranspiration index (SPEI) with mean values of Modified normalized difference water index (MNDWI)in Meyghan wetland. For this purpose, Landsat multitemporal images and climatic data related to the Arak synoptic station were used for the period of 28-year (1990-2017). After applying the necessary preprocessing on satellite images, MNDWI and its average values were computed for each year. In order to investigate the relationship between drought indices and mean values of MNDWI, the scatter diagram between them was delineated and the coefficient of determination obtained from the bivariate regression model was calculated. The results showed that the drying trend in Meyghan wetland during the study period was growing so that the average surface moisture of the wetland decreased from 0.36 in the initial years to -0.04 in the final years the coefficient of determination obtained from the fitting of the regression model between the SPI and MNDWI and between SPEI and MNDWI was estimated 0.34 and 0.51, respectively. These results indicate that 34% and 51% of the moisture changes in Meyghan wetland are explained by the SPI and SPEI, respectively.

The effects of drought can be represented as water resources declinations, vegetation and consequently, reducing agricultural production. To study and monitor drought, it is necessary to quantify its effects using drought indices.  The purpose of this study was to analyze drought in Marivan city using Landsat images from 2000 to 2017. After preprocessing the images, vegetation drought index (VDI) and vegetation health index (VHI) were extracted. Assessment of the indices showed that agricultural drought in VDI index was not observed in any year, and the values of this index were close to 100 that it indicates normal and optimal conditions. So, from 2000 to 2004 the normal conditions and from 2008 to 2017 have been optimal conditions in the dominant region. The results of VHI also show the Conditions without drought in the region. According to this index, extreme drought, severe drought and moderate drought in the studied years did not occur. The largest area of mild drought in the eastern and southeastern parts of the region in 2000, 2001, 2003, and 2005 was 38.23, 38.28, 12.29 and 35.74 km2, respectively. In general, According to the main emphasis of this study, based on VDI and VHI indices, from 2000 to 2017 (with the exception of  2012), the results indicate the absence of agricultural drought in the Marivan city. Considering the benefits of satellite images such as broader coverage, higher temporal resolution, and lower cost, it is recommended to use the knowledge of remote sensing for drought study.

Spatial modelling of distribution in the plant communities apply for predicting potential habitat areas and protecting species and determining the factors affecting their distribution. The study purpose is to determine the potential distribution of mangroves in Iran under climate change. In this study, occurrence records for Avicenia marina as dominant species were collected and MaxEnt modeling was used to predict the distribution of mangrove forests. The result showed the most suitable areas for the mangrove distribution under current climatic conditions are the Oman Sea coasts and the eastern coast of the Persian Gulf from Gwadar Bay to the northern coasts of Qeshm Island and Nayband Bay in the southern part of Bushehr Province. In the year 2050, habitat suitability based on the RCP2.6 and RCP8.5 scenarios, on the eastern coasts of the Persian Gulf and the Oman Sea, will increase. Both current and future climatic conditions, the northern coasts of Bushehr Province and the coasts of Khuzestan Province were not defined as suitable habitats. The results can apply for the conservation plan and mangrove planting.

Management and planning, distributing the economic and social activities as well as clearing hidden capacities in terms of the land’s potential and needs are the main goals of Land use planning. MOLA was used in order to zoning and planning Gorgan and Aliabad cities in eight major Land-uses. The method of analytic hierarchy process (AHP) and analytic network process (ANP) and the experts’ experiences were used for weighting the three main factors including ecological, economic and social factors. Compare zoning based on two ways AHP and ANP weighting also was evaluated. The results showed that the integration of applications based on AHP and ANP different weighting methods. According to the results of the integration of applications based on ANP method compared to the AHP with respect to slope, height, density of vegetation, rainfall and erosion ability in general is more appropriate. The results showed that according to total Kappa values (0.9151), spatial Kappa (0.9524), standard Kappa (0.9323), and chance agreement (0.1111), MOLA based zoning based on AHP and ANP weights had a similarity A lot. But the difference in the use of the AHP and ANP was 88663 pixels (7979 ha). For this purpose, statistical data on slope, height, vegetation density, precipitation and erodibility were extracted based on the weight of the two methods of AHP and ANP. According to the results, the placement of land use based on the ANP method in comparison with AHP is more appropriate in general. This means that the method has better performance in the ANP have been weighted to land-uses. The results of this study, the relationship and the importance of all aspects of ecological, economic and social planning and land use planning notes.

Water as one of the most basic needs of our present life and the extent of our use in drinking, agriculture, industry, economic, social, and political-security politics make us to identify with minimal cost savings and time characteristics of the watersheds, rivers and water levels by various methods, including the use of satellite imagery. The purpose of this research was to evaluate the methods of detecting zones, water levels and rivers with indicators; Normalized difference vegetation index, Enhanced vegetation index, Soli  adjusted  vegetation index, Normalized difference water index, Modified normalized difference water index, Automated water extraction index, Automated water extraction index and Unsupervised IsoClusterc and supervised Maximum likelihood classification methods to identification waters basin and the Optimum factor index for identifying the quality of water in terms of salinity, as well as determination infiltrate tabs water entering the larger zones in the part of the basins of the Karun river, Jarahi-Zohreh in the southern province of Khuzestan, with Landsat-8 satellite Land Earth Observations sensor. The results of the study showed that the automatic indicators of the extraction of water in shadow and urban areas are more effective than other indicators because of the consideration of short-range infrared wavelengths in water identification. With the results of the Supervised classification method, they were Maximum likelihood to the Kappa coefficient of the same 94% and the same performance. The results of the Optimum factor Index indicator for the detection of salinity water and the determination infiltrate tab water Show the most useful information and remove duplicate image banding data the Landsat-8 satellite Earth Observation Sensor was 79.10% for the color combination RGB of 651.

Satellite-based precipitation dataset has been widely used to estimate precipitation, especially over regions with sparse rain gauge networks. However, the low spatial resolution of these datasets has limited their application in localized regions and watersheds. So, having an accurate estimation of precipitation by satellites along with the adequate spatial scale in hydrologic studies is the main goal of this study. In this research, Geographically weighted regression (GWR) method was investigated to downscale the Tropical Rainfall Measuring Mission (TRMM-3B42 Version 7) over the DEZ river basin in the southwest of IRAN for 2010-2011. Downscaling was performed based on the non-stationary relationships between the TRMM precipitation and the Digital elevation model (DEM) derived products, the Normalized difference vegetation index (NDVI), the Enhanced vegetation index (EVI) and the Land surface temperature (LST). The result shows that the downscale precipitation at 1 km spatial scale had significantly improved spatial resolution, and agreed well with data from the rain gauge stations. For the 16-day precipitation, Mean square root means square error (RMSE) and absolute mean error (MAE) values are 22.7 mm and 7.45 mm, respectively. However, the accuracy of the model varies in a different location and depends on the vegetation condition.

In this study, ecological conditions were investigated in five criteria; climatic, topography, geomorphology, soil and land use, with the defined sub-criteria in order to determine the most important factors in locating the capable dry farming lands and determining the priority areas for planting. Then a questionnaire was designed and completed by 10 experts to give score the criteria and sub-criteria. The results showed that among the main effective factors, the topography and the climate had the highest effects, respectively, with a weight of 0.43 and 0.26, and soil and land use factors are the next priorities. The geomorphologic factor has the lowest effect of 0.60 weights. After preparing the base maps, these layers and weights of the network analysis process model were combined together with GIS and the restore potential map was obtained in five classes. The results showed that 19165 hectares of low-yielding and abandoned dry-farming lands (35.32%) have the highest potential for restoration. The lowland area is 3445 hectares and 5.81 percent has very low potential. In general, according to the results, 75.54 percent of these lands have a medium to the high potential for restoration. This percentage represents higher capacity and efficiency of the region to range planting and rehabilitation of low yielding and abandoned dry-farming lands. Therefore, this method can be used in determining the most suitable dry-farming lands for restoration and forage planting and returning these lands to rangelands so that the success of the development projects of the dry-farming lands is further enhanced.