فصلنامه سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی
سال نهم شماره 4 (زمستان 1397)

Estimation of quantitative forest attributes is important for its applications in order to understand the forest condition and performance. The aim of this study was the estimation of some quantitative forest attributes (stand volume, basal area, and tree stem density) using the RapidEye satellite data (2011) and non-parametric algorithms in the part of Hyrcanian forests in the Gorgan region. For this purpose, 418 plots each with an area of 1000m2 were established using a simple random sampling method. In each plot, information including a position of plot center, diameter at breast height of all trees and height of selected trees were recorded. Based on which the standing volume and basal area per ha were derived. A RapidEye image was processed by different synthetic bands derived from rationing, principal component analysis, texture analysis, and Tasseledcap, and the pixel gray values corresponding to the ground samples were extracted from spectral bands. These were further considered as the independent variables to predict the Quantitative characteristics. Modeling was carried out based on 75% of sample plots as training set using K-Nearest Neighbor, support vector machine, and random forest methods. The predictions were cross-validated using the left-out 25% samples. The results showed Random forest comparatively returned the best estimates for stand volume, basal area and tree stem density with root mean square error of 39.83%, 29.71%, and 50.11% and relative bias of 0.01, 1.69 and 2.11 as well, respectively. The results of this study also showed that due to the heterogeneity and density of Caspian forests, RapidEye satellite spectral data have a moderate ability to estimate the quantitative forest attributes.

The Aquifer of Naqadeh plain, located in the southwestern part of Urmia Lake, providing water supply of the area. In order to evaluate and classify water resources quality, 33 samples were taken from operational wells in June 2016. Hydrogeochemical characteristics and concentration of heavy metals, major and minor ions were measured by means of standard methods. Feasibility studies for various consumption of groundwater were investigated using graphical methods and quality criteria of Schuler (drinking), Wilcox (agriculture) and Langelier (industrial) classification. Based on the available information, the spatial distribution of the effective parameters using GIS and geostatistical interpolation method (Kriging) was applied to generate water quality zoning maps. In this regard, the final maps of quality, zoning were prepared after creating the raster layers of the effective parameters, classification, and integration. According to the results the hardness degree of drinking water of all samples was high, and also the concentration of some parameters was more than drinking (WHO) and agriculture (FAO) water standard, so inappropriate quality of these resources should be considered. The evaluation of industrial water quality showed scaling property of 61% and corrosive property of 39% of samples. In addition, the agricultural water quality illustrated that 46% and 39% of water samples were placed in good and average quality, respectively. Analyzing the quality, zoning maps with geological information, land use and distribution of industrial units were carried out in the plain and the results show that quality of groundwater is inappropriate mainly in the northern and eastern parts of the plain.

One of the most commonly used methods for generating resistance maps is reversing habitat suitability (HS). In this study, in order to prepare a cost map, local-scale habitat modeling was conducted in each of the Lashgardar-Golaprabad, Palangab, and Alvand- Chal Khatun- Rasvand areas using the MaxEnt model. At the same time, the results of performing in each area in a wider dimension were extended to a boundary that covers all of the areas. This led to the creation of three scenarios for the relocation of wild sheep. Scenario 1 is HS of Lashgardar-Golaprabad areas as cost map, scenario 2 is HS of Palangab area as cost map and scenario 3 is HS of Alvand- Chal Khatun and Rasvand areas as cost map. Corridor modeling was performed based least cost path method in ArcGIS. Density and suitability metrics of the corridor were investigated. Validation of the corridor and MaxEnt model were performed by the Area under curve (AUC). The adaptation of the designed corridors of each scenario with habitat suitability of different areas was investigated by Friedman test. Eventually, an average of the designed corridors in scenarios 3 was introduced as the main corridor between all areas under study. The results showed that the designed corridor in scenarios 1 and 2 based on AUC, are in well adapted to habitat suitability of the species in other areas; but Friedman's test revealed that the designed corridors in different scenarios have a significant difference (P-value<0.0001) in terms of adaptation to habitat suitability in other areas.

In the present study, vegetation changes in the Karaj watershed in 2006, 2011 and 2017 were investigated using the Normalized difference vegetation index (NDVI), the integration of land metrics and gradient analysis. After calculating the NDVI index, Then, two-section gradient analysis was designed in the direction of north-south and east-west. Then 6 metrics were calculated at two levels of class and landform using moving window design. The results of the comparison of the floor area showed that the highest increase in the area was done in lands with very good vegetation so that 5104 hectares (4%) have been enlarged. It is also the largest reduction in the area of excellent vegetation cover, which decreased by 4055 hectares (3%) during the studied period. The results of gradient analysis showed that the distribution pattern of vegetation in a three-year period is a cluster. The results of the analysis of both transects at the level of the land and the classes show that the average of mean distance from the nearest neighbor gradually increases during transects and the increase in total in 2017 compared to the initial year. This indicates an increase in the distance between the vertices of the same patch and the difficulty of communication between them, which is one of the signs of the disruption of the landscape.

The aim of this study, was to evaluate the effectiveness of different preprocessing methods and modeling techniques on the accuracy of aboveground carbon stock estimates in two forest stands with different degradation levels (Gahvareh forest and SarfiruzAbad), in Zagros forests in Kurdistan province. Comparison of different digital pre-processing methods on Landsat 8 images was carried out in different scenarios of radiometric, atmospheric, topographic and their combination. In each scenario, we used four modeling methods included linear regression, generalized additive model, random forest, and support vector machine. In most cases, radiometric correction with improved correction coefficient was 0.71 (R2adj =0.71) and the root means square error of 30% (RMSe% =0.30) was outperformed. Comparison of four modeling methods indicates the lower accuracy of estimates in the SarfiruzAbad area with more degradation severity (R2adj =0.58) compared to the less damaged Gahvareh area (RMSe% =0.74). The random forest method for Gahvareh area and linear regression and a generalized additive model for SarfiruzAbad provides better results, respectively. However, our findings showed that selection of suitable preprocessing and modeling method have a noticeable effect on the accuracies of characteristics estimates in forest ecosystems by Landsat imagery.

Salt domes are one of the most beautiful natural phenomena. Despite the outcrops of many salt domes in the Zagros region, but many of them are still buried and hidden. Due to active Zagros tectonics, the movement and ascending trend of salt domes do not stop. In this research, with the aim of the changes monitoring in the Earth's crust in the Zagros area, one of the new, hidden and ascending probabilistic salt domes, was identified using a radar interferometry method. For this purpose, ASAR radar images for the years 2007 and 2012 and SENTINEL-1 for the years 2014 and 2017 were used. In order to determine the amount of changes in the earth's crust, during the process of unwrapping on the images, the interference of each of the images was extracted. According to the results of the analysis of ASAR images, the growth rate of the salt dome was 1.6 centimeters per year between 2007 and 2012. While according to the interferometry images that obtained from SENTINEL-1 the rising speed of this salt dome increased between 2014 and 2017, reaching 2.9 centimeters per year. The result of this study shows that the probabilistic salt dome is active. Consequently, due to the importance of salt domes in various fields of natural resources, especially in the formation of oil reservoirs in the Zagros region, as well as more accurate identification of the subject, it is necessary to carry out special geophysical studies in this area.

Urban expansion and land use changes have a significant impact on land surface temperature (LST). According to the fact that the development of urban is currently one of the most important phenomena in global warming, it is possible to study and measure the temperature of the Earth's surface in urban areas in the shortest possible time with the rapid development of satellite technology. The purpose of this study was to investigate urban expansion and urban heat island (UHI) using remotely sensed data in Shahrekord city. In this study, Ratio vegetation index (RVI) and Normalized difference vegetation index (NDVI), and LST were calculated using multi-spectral and thermal bands of Landsat 7 and 8 satellite images. Land use map was extracted using the maximum-likelihood algorithm in TerrSet software. The overall kappa index was estimated at 0.82 and 0.93 for 2003 and 2016, respectively. By comparing two vegetation indexes (RVI and NDVI) and surface temperature during the 13 years (2003 to 2016), it was determined that with urban development, the surface temperature has increased to 2.210C (from 40.69 to 42.90 0C). The results showed that the correlation of NDVI index with the surface temperature map was negative but with positive RVI index. Moreover, these two vegetation indexes, RVI and NDVI, show a more significant relationship with LST in green areas than urban and bare lands. Due to, a significant effect of green areas on regulating LST we recommend that green areas should be expanded in accordance with the urban area expansion.

Distinguishing the susceptible areas to landslide using appropriate experimental models of landslide susceptibility mapping is one of the primitive and basic works to reduce probable damages and reduce risk in country's watersheds. In this research, thirteen factors, including altitude, slope, aspect, rainfall, plan curvature, profile curvature, Topographic Wetness Index (TWI), Stream power index (SPI), distance from the river, distance from road, distance from the fault, lithology, and land use are identified as effective parameters in landslide occurrence in the studied area. The landslide landslide distribution map was prepared using Landsat 2017 satellite imagery and Field studies (2017). Then, the landslide susceptibility mapping was performed with three methods, including frequency ratio, entropy and TOPSIS. The results were evaluated using receiver operating characteristic (ROC) curve. The area under the curve (AUC) of applied models shows the accuracy of 84, 87.7, and 91 percent for entropy frequency ratio and TOPSIS models, respectively. The results are indicative statistical models have a better accuracy in comparison with MCDM models and expert approaches. The results of the present study could be useful for better managing the flood affected areas and to reduce its damage.

Sustainable land use pattern relies on a precise assessment of ecological resources. Medicinal plants demand special environmental conditions, therefore, researchers and experts have special attention to land suitability evaluation and appropriately discover and assess ecological resources and finally, make feasibility studies for specific aims applying agricultural and ecological models. The present study aimed to identify effective climatological, topographic, and physical-chemical properties of soil on the habitat of the Ferula assafoetida medicinal herb, and zoning of suitable areas for cropping of these crops by means of Geographical Information System (GIS) in the Chatrod region of Kerman province. In the first step, the ecological requirements of Ferula assafoetida identified for determining scientific resources and thus, classified to provide thematic maps. Thematic maps also prepared and categorized by sampling the soil from the surface area at 14 points. The examined parameters included precipitation, temperature, altitude, sand, silt, clay, lime, pH, electrical conductivity, potassium, saturation, phosphorus, organic matter, and nitrogen. Finally, by integrating and matching the weighted maps in GIS software, the zoning of the habitat of the Ferula assafoetida extracted. The results of the zoning showed that Ferula assafoetida was in four zones (very suitable, suitable, moderate and poor) in terms of land suitability. Approximately 4826 hectares (16.9%) of the Chatrod region had highly suitable for growing the Ferula assafoetida herb. It is because of the specific characteristics of this area, such as low electrical conductivity, low acidity, high organic matter, and the height of 1900 to 2500 meters was. However, approximately 6819.6 hectares (23.8%) of the area of land evaluated as unsuitable zones because of low rainfall, high altitude and organic matter to grow of Ferula assafoetida.