interpolation

Unplanned urbanization is growing at an alarming rate in developing countries. This growth has created challenges for development planning and urban risk management. The substantial growing urban population leads to a rise in urban dangers. Consequently, when confronted with natural hazards, these often result in recurring calamities. Risk assessment, as one of the basic tools of risk management, analyzes risk and vulnerability. This tool is used to study the possible and existing risk factors of disasters that can occur and provides the basis for planning and implementing measures to reduce the risks and effects of disasters. In this thesis, considering the potential of flooding in the dry river basin of Shiraz, an evaluation and urban risk management (with regard to urban floods in Shiraz) has been investigated. The purpose of this study is to determine the suitable places for the establishment of temporary centers for the flood-affected population in Shiraz city. It is a descriptive-analytical research method by using which the required criteria and indicators were selected and according to the analysis results by crisis management experts, they were measured as layers in the Arc GIS software. Then, according to the weight given to each of the layers and using the hierarchical analysis process model, places with more compatibility with suitable and very suitable areas have been selected. The results show that the southern, central, and part of the eastern regions are among the regions with high potential for the construction of suitable areas for emergency and temporary accommodation during the occurrence of geomorphic hazards in the dry river basin of Shiraz. In general, the assessment and management of urban risks can be seen as an important step in the risk management process by which available resources can be used to deal with disasters and risks.

One of the important and fundamental needs in order to develop the capabilities and capabilities of tourism in a region is the suitable climate for tourism. The use of tourism capabilities and capacities requires the recognition and evaluation of comfort climate using accepted scientific methods to systematically determine the effect of climatic elements on the activities of tourists. Based on this necessity, in the current research, the spatial-temporal distribution of tourism climate conditions in Mazandaran province has been investigated using the Beach Climate Index in the ArcGIS software environment. In order to implement this index and achieve the goals of the research, the daily time series data of the meteorological stations of Mazandaran province during the years 1980 to 2018 were used. According to the needs of the model and method used, climate elements (on average) including relative humidity, wind speed, sunny hours, monthly precipitation, average daily and monthly temperature, cloudiness and number of foggy days have been used. After calculating the values of the CPI index in the J environment. Oh you. S, interpolation methods were used to prepare tourism activity zoning maps with the least amount of error in interpolation. The results of the coastal tourism climate index at the level of Mazandaran province on a monthly scale indicate that between the coastal and mountainous areas Different patterns prevail in terms of tourism comfort index at different times of the year. In autumn and spring, in the coastal parts of the province, especially the parts of the eastern coast, the quality of beach rest is in a better condition. Meanwhile, in the same period, cold stress prevails in the mountainous parts and reduces the quality of the climatic comfort index compared to the coastal areas. But in the summer months, due to the rule of heat stress in the coasts, the mountainous areas have a more suitable climatic comfort quality according to the BCI index.

Assessments of water quality have recently developed and now include surface and groundwater pollution issues. Permanent changes occurring in the quality of groundwater, especially those affecting drinking water and salinization of water sources, are considered to be a serious threat to rural development. Unfortunately, many people lack enough knowledge about the importance of groundwater and the harmful effects of environmental pollution on these valuable resources. The present study has investigated the quality of potable groundwater in the rural parts of central Ardabil County using multi-criteria decision-making models and geostatistical analysis in GIS environment. Parameters such as EC, PH, SO4-, Cl-, Na and TH (in terms of CaCo3) have been used to create an overall picture of the quality of potable groundwater resources in Ardabil County based on which related zoning map was developed in geographic information system. The kriging interpolation method was also used to obtain the spatial distribution of the parameters and the simple additive weighting method was used to weigh and rank the layers. According to the final map of water quality, approximately 36% of the central Ardabil County (around 88 square kilometers, mainly in the southern part of the study area) has access to optimal quality of drinking water. On the other hand, low quality of drinking water is observed in the northern and northeastern parts which cover 46% of the study area (112 square kilometers). Moreover, a direct relationship is observed between the population density and the density of deep and semi-deep wells and the decrease in the quality of water.            

The present study has applied library research and field study methods. Rstudio and Arc GIS 10 software were also used to perform related analyses. Study Area Case study area includes 243 square kilometers of the central Ardabil County consisting of three cities and nineteen villages as illustrated in Figure 1. The following methods were used in this research:1- Direct rating 2- Kriging interpolation 3- Standardization method 4- Simple weighing method 5- Fuzzification of the final data The following parameters have also been used to assess the quality of drinking water:1- Electrical conductivity (EC) 2- Chlorine level (Cl-) 3-The amount of sulfate (SO4+) 4- The amount of nitrate (Na) 5 Total water hardness(TH) 6- Water acidity level (PH)

Groundwater chemical quality is primarily assessed using parameters such as changes in the amount of dissolved salts, and limitations on various uses of water especially water used for drinking. Table 1 shows different types of conventional kriging methods selected through the method test for the parameters. These can be obtained using the mutual evaluation method and RMS error. Factors affecting the quality of drinking water are then ranked and weighted according to the expert opinions. The final quality map is thus prepared. Layers are then standardized in accordance with data description and the results are presented in Table 1. It also exhibits maximum permissible and desirable level of non-toxic chemicals in drinking water in accordance with the Iranian Standards and Industrial Research Institute (ISIRI) and the World Health Organization (WHO) standard, along with the maximum permissible level of mineral substances in drinking water. Semivariograms used for kriging interpolation are also presented. Table 2 shows the RMS and RMSE errors as well as the average standard error of the water quality parameters in the study area. The interpolated primary layers are presented in Figure 3. The final map prepared for the quality of potable water in the study area indicates that the quality of groundwater in the northern part and a little section of the central part (46% or 112 square kilometers of the study area) is unfavorable. This includes 8 villages of the County. 6 villages have access to drinking water with semi-optimal quality and 5 villages are located in the optimal area of water quality. Accordingly, the quality of potable groundwater decreases drastically as we move towards the northern and northeastern parts of the study area, and the lowest quality of groundwater is observed in the most northerly part of the study area (covering 46% of the study area). Figure 4 shows the density of deep and semi-deep wells, the amount of annual harvest from rivers in the central part of Ardabil (in thousand cubic meters per year), the population density and industrial areas in this region. A direct relationship is therefore observed between population density, the density of existing wells, the level of water extraction from rivers and the sharp drop in the quality of groundwater. According to the reports prepared by Ardabil Regional Water Company, around 32 million cubic meters of water is annually needed to meet the drinking requirements of urban and rural uses, which can seriously damage the quality of underground water in the area.

According to the final map of groundwater quality, only 36% of the study area (88 square kilometers) has access to drinking water with favorable quality which can be a great concern for planners and managers. Finally, it is suggested to use geostatistical methods and geographic information system as a useful tool to assess the quality of underground water. These methods can gradually replace the old methods and thus prepare more accurate statistics, increase the efficiency of water-related projects, and reduce their cost.

Air pollution as one of the most important factors affecting the environment, especially in large cities has caused many problems for residents. On the other hand, green spaces as one of the emphasized elements in urban ecology, play an important role in reducing air pollution. Therefore, studying the type and intensity of the relationship between urban green space and air pollution can show the extent of the impact of urban greenery on pollutants.

Goal:

The main purpose of this study is to analyze the relationship between green space and changes in air pollutants by regions in the metropolis of Tehran with an emphasis on urban ecology.

This research is descriptive-analytical by nature and applied in terms of results and mixed (quantitative-qualitative) in terms of methodology. In this research, the method of interpolation functions in ArcMap 10.7 software and regression analysis in SPSS 21 software have been used. To integrate the current situation of the variables with regression relationship and determine the priority of action by regions, qualitative coding has been done at four levels from high to low.

Geographical area of research:

A case study of the research is the metropolis of Tehran.

The findings indicate that there is an inverse and significant relationship between green space and CO, SO2 and PM2.5 pollutants. With 95% confidence level, the impact of green space on CO, SO2 and PM2.5 pollutants based on Beta coefficient is -0.500, -0.508 and -0.452, respectively. The results of qualitative coding of the current situation of variables with regression relationship show that regions 9, 10, 18 and 21 due to the low level of green space and high concentrations of these pollutants, are in the first priority category to apply suggestions.

The results showed that the presence of green space does not affect the changes in the concentration of all air pollutants. It only affects CO, SO2 and PM2.5 in Tehran. Finally, despite the need for suggestions aimed at controlling air pollutants, the focus of this study is on green space-based suggestions to reduce air pollutants based on the priority of actions by regions. These suggestions are presented in the form of top-down and bottom-up approaches in two short-term and long-term periods.

Soil chemical properties variability and value of their variability have specific importance in sustainable production. Measuring methods of these which usually possible with soil testing, in a large scale are so timing and cost consuming. One of methods which use for monitoring these properties and decrease the costs of sampling in large scale is interpolation. Interpolation has many methods and each one has a different accurate in various conditions. In current research three ordinary interpolation methods were used for interpolation some chemical properties of Khuzestan’s agricultural soils. These variables in this research were Total Nitrogen (TN), Absorbable Phosphorous (P), Absorbable Potassium (AK), Calcium Carbonate percent (CaCo3%), Organic Carbon percent (OC%),  Electrical Conductivity (EC), and Soil Acidity (pH), which measured in 270 soil samples. Due to the skewness and Kurtosis of these data, it was found they have not a normal distribution. In order to normalize the data, after deleting the outdated data, logarithm and Cox-box method were used.   The interpolation methods which used were kriging (OK), Radial Basic Functions (RBF), and Inverse Distance Weighted (IDW). Mean absolute error (MAE), mean bias error (MBE), and root mean square error (RMSE) were used for detecting the optimum method. Examination of variographic results showed that the spatial structure (correlation ratio) of absorbable phosphorus (0.243) and absorbable potassium (0.159), strong, total nitrogen weak (measurement error 0.816) and the other parameters had a moderate spatial structure. Based on the results of this table, the ordinary kriging method with exponential model can be considered as the best and most accurate method (MAE = 0.01515, RMSE = 0.0890, MBE = 0.0006 and R2 = 0.912) for interpolation the total nitrogen.However, the best method for interpolation of organic carbon, absorbable phosphorus, absorbable potassium, calcium carbonate, acidity and electrical conductivity of soil are RBF, ordinary kriging (spherical model), ordinary kriging (spherical model), RBF, ordinary kriging (with exponential model) and RBF respectively.The results showed that the IDW method was not a suitable method for interpolating any of the parameters. From the prepared maps, it can be clearly seen the non-uniformity of fertilization, amount of absorbable phosphorus in the southern parts of the study area is higher but amount of absorbable potassium in the northern and central parts of the study area has been more.While in the eastern and western part of the study area and in places where the pH is above 7.7, the amount of calcium carbonate in soils is at its highest level of 46 to 49 percent. Preparing maps with appropriate accuracy by geostatistical methods for parameters that have good spatial dependence is a suitable method for monitoring and land management at the macro level.

Environmental studies require an environmental gridded database. Environmental change, and climate change studies are not possible without a gridded climate database. In those environmental studies that cover a geographical area, but the necessary data is available for a restricted number of points (for example, meteorological stations) and not for the entire area under study, interpolation is required to convert the point data to areal data. In other words, it is necessary to create a network database.The first sample of such databases for Iran called Asfezari was introduced in 1996 at the University of Isfahan. This article introduces the process of preparing the third version of the Asfazari rainfall database prepared at the University of Isfahan. This gridded rainfall database is provided in a conical Lambert projection system. Its temporal resolution is daily and its spatial separation is ten kilometers. This database covers the daily rainfall of the mainland of Iran from 1349/01/01 to 1394/12/29. The error in estimating the average rainfall in this database is less than 15%. In preparing this database, the daily rainfall data of 2188 meteorological stations (including synoptic stations, climatic stations and rain gauge stations) of the Meteorological Organization of Iran (IRIMO) have been used.

One of the important issues in water resources management is the estimation of rainfall in areas where pregnancy has not been done. Due to the lack of complete coverage of the rain measuring stations, it is necessary to estimate the rainfall in the areas between the stations. . Estimation of unknown data at different points is done using interpolation methods on the measured data in the studied area. For this purpose, different methods are used to analyze spatial dataIn this research, a variety of common methods of interpolation and geostatistics have been used to estimate the average annual rainfall parameter of Chahar Mahal and Bakhtiari province. The statistics used are the statistics of 44 rain gauge stations for the period from 1980 to 2008. . Due to the extreme changes in the topography of the study area, the effect of altitude on the distribution of precipitation as a barrier against the spread of clouds has also been investigated. For this purpose, interpolation was calculated with various models and a prediction map was drawn. Then, using the mutual evaluation method, the square root of the errors and the error of the maps were estimated and one map was selected as the appropriate map The obtained results show that for the interpolation of the average annual rainfall methods that considered the heights as obstaclesThey show higher accuracies in the studied area, among which the fourth and fifth degree polynomial models showed the most suitable information for interpolation of average annual rainfall values

Wind and wind velocity data from satellite QUIKSCAT, for 10 years and the monthly average, in the Jask Bay(latitude of 25.1 into 25.5 North and longitude 57.2 into 58 East) were extracted. Convenient digital map of the study area were prepared using the software ArcGIS 9.3 and XTools Pro 7.1, spatial modeling of currents due to wind by Kriging interpolation method during all months of the year was done. The result of continuous development of maps of the velocity and direction of wind driven currents and also produce various charts for months. For optimal display the currents direction, two-dimensional and three-dimensional map was drawn. In the Jask Bay of the Oman Sea, the maximum velocity of wind driven currents in August 0.47 m / s and the lowest in October, is 0.14 m / s respectively. In autumn, the difference between the lowest and highest wind driven velocity in the Jask Bay is 0.29 m / s that have highest range in all seasons, so in spring the range of wind driven velocity is the lowest 0.03 m/s. In winter and spring, the pattern of wind driven current direction is southwestern, in summer is east and northeast and in autumn, south and southwest.

Regarding to importance of Juniperus sites, it is important to estimation of tree density and spatial structure of them using Geostatic. This study was conducted in Golestan province, Chaharbagh with area of 60 ha. We refined a 15×20 grid and 300 plots (45×45 m2) were measured. The number of trees with diameter at breast height (DBH) <7.5 cm were considered. The results of the variogram analysis showed that the tree density parameter had a vigorous spatial structure. First, the spherical model was fitted on the variogram. Then, the estimations and mapping were done using Kriging and IDW approaches. Cross validation results of approaches showed that the estimation of tree density was unbiased and these methods can be used for mapping spatial distribution of tree density with acceptable precision. The Kriging method with RMSE of 6.8 tree.ha-1 and 8.7% had the better performance in comparison with IDW with RMSE of 7.5 tree.ha-1 and 9.5%. So, the Kriging method is useable in ChaharBagh for tree density mapping.

The aim of this study was to analyze rainfall drought indices to predict and reduce their negative effects in Ardebil province, which involved a descriptive-analytical study in terms of research type. Data were collected using documentary method. Accordingly, the information of mean rainfall and mean temperature on a monthly basis in synoptic stations of Ardebil, Germi, Parsabad, Meshkinshahr and Khalkhal were received from the Meteorological Organization in Ardebil province for the period (1996-1996). Dip and Dic software were used to analyze the SPI and CZI indices data in each of the 5 synoptic stations of the province. Drought zoning was then performed in two scales of 6 and 12 months, from IDW interpolation, in ArcGIS software. The innovation of the present study was the use of if-then rules in MATLAB software in combining drought indicators in the field of climatology. The results showed that very severe droughts at the 12-month scale were less than at the 6-month scale, and in all 5 stations studied, the number of moderate droughts was more than severe and very severe ones. Also, the highest frequency of drought was observed in Ardebil city and the lowest in Germi station. Similarly, a comparison of the two indicators displayed that their performance did not differ much; but it turned out that the SPI index, could reveal the number of droughts better than the CZI index.

Public transportation plays a significant role in decreasing energy consumption and greenhouse gases. By reducing private passenger vehicles, lowering vehicle traffics, and decreasing travel distances via public transport, millions of liters of gasoline can be saved and carbon dioxide emissions may be prevented. But in order to achieve these public transport goals, it faces numerous economic, political, managerial, infrastructure, and other barriers among which physical barriers are more tangible than others. Among the physical barriers to public transportation fleets, especially vehicles physics, are more prominent. The present study aims to investigate and analyze the barriers to public transportation fleet development in Ahvaz metropolis with emphasis on the physical barriers of the vehicles. The main research approach is developmental-applied, descriptive, analytical, and survey research. The research data were collected through documentary, library, survey techniques, and interviewing with individuals and experts. The ARAS decision-making method was used to rank the barriers and the Kriging model to map these barriers to the city. The findings indicated that barriers in each bus and taxi use have different effect sizes in such a way that for taxi use, fleet deficiency (with the weight of 0.0161), poor quality of interior hygiene (with the weight of 0.074) and poor diversity (with the weight of 0.066) have the most effect sizes; while for bus use, fleet burnout, poor heating-cooling system, and low safety (with common weights of 0.0116) have the greatest effects. Zoning these barriers in the city revealed that most of the city area is very inappropriate range, and districts 2 and 5 are the most appropriate and inappropriate zones, respectively.

Bioclimatic variables are one of the most important environmental variables that used in mapping and species distribution modeling for the management and conservation of vegetation and species cultivation. In order to provide bioclimatic maps, long-term climate data of 49 weather stations were used during the years 1952 to 2017 to extract 19 bioclimatic variables. Geostatistics methods (Kriging and Cokriging) and Multiple Linear Regression model were used to create 19 bioclimatic variables in Lorestan Province. Correlation ratio was used to select the best interpolation model. Also, Cross-validation was used to validate the interpolation method. Root Mean Square Error (RMSE) and the Root Mean Square Standardized Error (RMSSE) were used to select the best interpolation method. Based on the results, the best interpolation method for maping Bio4, Bio5, Bio7, Bio12, Bio13, Bio15, Bio16, Bio17 was Kriging method due to lower error values of RMSE and RMSSE for and Bio18 and the best interpolation method for maping of Bio1, Bio2, Bio3, Bio6, Bio8, Bio9, Bio10, and Bio11 was Cokriging method. Multiple Linear Regression model was also the best interpolation method for Bio19. Based on the results of this study, the use of an elevation auxiliary variable and climatic factor can increase the accuracy of the evaluation of interpolation methods to create accurate maps for modeling of species distribution.

The basis of climatic data is measurements taken at a predetermined chronological order at air monitoring stations, so all measured values ​​of climatic elements can only be attributed to the point of measurement. Therefore, different interpolation methods can help a lot in estimating climate data in different places. The study area in this study is northeastern Iran, including the provinces of Khorasan Razavi and North Khorasan, and monthly summer temperature data were used for 21 synoptic and evaporative stations in the northeast belonging to the Meteorological Organization and the Ministry of Energy with appropriate distribution. The statistical period of 21 years (1997-1997) was considered as a common statistical period for all stations. Then, in order to compare the interpolation methods, several different methods, including ordinary kriging, spline, inverse squares and Thyssen were used by ARCGIS software. Comparing the deviations of the estimates from the measured data was evaluated by cross-validation. Then, in order to check the hypothesis of normality of the calculated errors in each interpolation method, the test thigh test was used and finally, to evaluate the best interpolation method, AHP method and Expert Choice software were used. The results showed that based on the root mean square error (RMSE) criterion, Thyssen, Kriging, inverse distance and spline methods were located, respectively. Based on the absolute maximum error criterion (MAE), the kriging method estimates the summer temperature better than other methods. According to the MBE standard, the kriging method is better than other methods and can be used for temperature interpolation. According to the set coefficients, the calculated compatibility rate is 0.03, which indicates the high accuracy of the selection of weights.

Collective mobility focuses on sharing trips, transport modes, and infrastructures. This can reduce the number of vehicles on roads. Thus, it is important to evaluate and measure transport subsystems. One of the most important of transport subsystems is urban transport as a key element of human and commodity transportation, playing an essential role in the viability of all communities, and as a justified choice to avoid unintended urban problems such as road and traffic congestion as well as air pollution. Therefore, urban transport organization is one of the necessities of urban planning. However, But, transport itself is not such a challenge, but rather, it is a gift. However, it will become a problem when its effects will cause dissatisfaction with the transport network and thereby reduce the quality of urban services. Political-managerial, environmental, physical, and socio-cultural barriers are involved in transportation challenges, most visible of which are physical barriers. These barriers vary in different Iranian cities according to their natural and human geography, but in Ahvaz City, they are effective on preventing Land use barriers to transportation apart from human, environmental, and climate issues. Also, according to Ahvaz Metropolis Second Five Year Development Plan in the field of transportation and traffic, one of the most important strategies of Ahvaz transportation and traffic development is to identify the barriers to transportation development in different dimensions, one of which is the physical barriers to transportation, doubling the significance of doing research in the field. Therefore, these barriers need to be identified and categorized in each public transport infrastructure and land use. The present study aims to investigate the physical barriers of inter-urban public transport in six dimensions of stations, urban arteries, urban terminals, urban public parking lots, fuel stations, and public transport urban fleet in the eight urban districts of Ahvaz and seeks to answer the following question. What are the most important physical barriers to urban transport development of Ahvaz Metropolis? To this end, the study makes attempts to examine and analyze these barriers and identify the significance of each one in order to prioritize them in terms of effectiveness and weight in Ahvaz transportation planning, and then, zone each of these barriers in Ahvaz.

The present study is applied-theoretical in terms of objectives; also descriptive-analytical and survey in terms of research methods. The research data was collected through documentary, library, survey, and interviewing with people and urban planning experts. The research population consisted of citizens of eight districts of Ahvaz Metropolis districts. The questionnaires were distributed among 130 participants selected via stratified sampling technique according to the weight ratio of each district. To rank the land use barriers in each of the different transport infrastructures, the ARAS decision making method was employed. To map. Moreover, the kriging interpolation method was employed for zoning these barriers in Ahvaz with ARC GIS10.3 software. After interpolating all the obstacles using the Reclassify tool, which is a subset of Spatial Analyst Tools in the Arc Toolbox., the maps were drawn into a five-point spectrum (very low, low, medium, high and very high) and finally overlaid using the Weighted Sum function.

In sum, this study identified 36 key barriers to each of Ahvaz public transport land use for analyzing the land use barriers to public transport development in Ahvaz. These barriers were for belonged to public transport stations (9 factors), urban arteries (9 factors), urban terminals (9 factors) and public parking lots (9 factors). This classification is such that it encompasses the different public transport modes in Ahvaz, such as those used to measure the public transport stations of the bus and taxi stations. In measuring urban arteries, physical barriers to Ahwaz's various public transport modes such as walking as well as bus and taxi driving were considered. In assessing the barriers related to urban terminals in Ahvaz, eight existing terminals were evaluated. Due to the lack of accurate statistics on types of urban public parking lots such as mechanized and non-mechanized parking, flat or floored,  marginal, etc., public parking lots, barriers to urban parking lots are generally evaluated as being inadequate access, organizational carving, weakness of the heating and cooling system, avoidance of health centers, lack of fleet and incompatibility which are the major barriers to stations, urban arteries, terminals, parking lots, urban transport fleets and fuel stations, respectively. In addition, zoning these barriers also depicts that most of Ahvaz’s zones in terms of stations, urban arteries, urban terminals, parking lots, transport fleets and fuel stations were in the range of relatively inappropriate, relatively inappropriate, relatively inappropriate, relatively inappropriate, very inappropriate, and moderately appropriate levels, respectively.

The present study employed barriers covering each of the six physical dimensions. We then need to rank these barriers to identify the most effective barriers to each of the six dimensions of physical barriers (stations, urban terminals, urban arteries, public parking lots, fuel stations, and transport fleets). The significance of this ranking is that the underlying organizations are not capable of removing all of them at a given time, and removing these berries barriers over certain courses of time is important. To this end, we performed each of the barriers to the six dimensions separately. Until these criteria are met, the extent of the barriers to each of the physical dimensions will be identified; and public transport development planning was will be facilitated. Eliminating existing barriers is among public transport development strategies. The research findings can be generalized and employed by the Municipal Transport and Traffic Departments, the Urban Housing Agency, the Reconstruction and Renovation Organization, and other related agencies. Collecting and extracting multiple barriers to public transport in each of the applications and categorizing them as a package that informs the related organizations of the status quo are among one of the significances of the research findings which depict that the geographical distribution of these barriers in the study area is known.

LiDAR (Light Detection and Ranging) employs pulse models which penetrates vegetation cover easilyand provides the possibility of retrieving data related to Digital Terrain Model (DTM).Pulses sent by the Lidar sensorhitdifferent geographical features on the surfaceground and scatter inall directions. Distance to the object is determined by recording the time between transmitted and backscattered pulses and by using the speed of light to calculate the distance traveled by the small portion of pulses backscattered. Most LiDAR receivers at least record the first and last backscattered pulses. The first backscattered pulses are used to produce Digital Surface Models (DSMs) and the last ones are used to produce DTMs. Despite the fact that these data can provide a valuable source for DTM generation, the volume of vegetation (vegetation density) in forest areas reducesthe accuracyof DTMs. Onthe other hand, ground surveying of forest areas is rather expensive and time consuming, especially in largerforests. Aerial images are also used as a source for DTM generation, but this approach requires a 60–80% overlap between images which along with canopy height reduce the potential of this method for DTM generation. Also, low spatial resolution of satellite images collected from forest areas increases errors in DTM generation to a large degree. The present study investigates the accuracy and precision of DTMsproduced from LiDAR data in a forest area. Furthermore, the effect of different methods of filtering and DTM interpolation was explored. Different methods of DTM generation were also closely analyzed and evaluated.

 The case study area is located in Doroodforests, a part of Zagros forests, in the southeastern regions of Lorestan province in Iran (48°51’19’’E to 48°54’31’’E and 33°19’21’’N to 33°21’15’’N). Minimum and maximum altitude above sea level were 1143 and 2413m, respectively. The study area covers 100 hectares of mountains with an average slope of 38%. Approximately 50% of the area is covered by forests in which Brant’s oak (Quercusbrantii Lindley) is the most frequent species. LiDAR data were collected by the National Cartographic Center of Iran (NCC) in 2012 using a Laser scanner system (Litermapper 5600) fixed on an aircraft flying at an average altitude of 1000m. LiDAR data consisted of the first and last returns (backscattered pulses), distance and their intensity value. Collected data had an irregular structure and included an average of more than four points per square meter. A DTM was produced using a two-step filtering. First, a morphological filter removed most of non-ground points, and then a slope-based filter detected remaining points. Inforest areas with rough-surface, DTM was producedthrough processing ofLiDAR data with statistical methods likekriging and inverse distance weighting (IDW). These methods apply third and fourth power to detect and remove non-ground points. To assess the accuracy of DTMs produced by different approached, 5 percent of the LiDAR point cloudswererandomly separated as the test data. Amongst these data sets, 62 points with a suitable dispersion were selected and measured using a GPS-RTK. An error matrix, along with accuracy indices (including correlation and Root Mean Square Error (RMSE)) were calculated based on these data.

Results indicated that 44-degree slope is the best threshold for isolation of non-ground points and inverse distance weighting (IDW) is the best third power interpolation method with the highest correlation (0.9986) and the lowest RMSE (0.204 meter). Amongst the filtering methods, slope-based filter used for separation of ground and non-ground points had the best performance. Since this filter combines two parameters of slope and radius, it can remove cloud points related to the vegetation cover and results in high efficiency for steep forest areas. Slope-based filter is suitable for processing of near-surface vegetation, whilst statistical filter is well-suited for vegetation cover consisting of tall trees.

The present study proposed and investigated different scenarios for the production offorest areas’ DTM using LiDAR data and two interpolation methods. These algorithms were practicallyassessed using LiDAR data collected from Dorood forest areas. The best scenario was slope-based filter with inverse distance weighting (IDW) interpolation. Based on accurate assessment, this approach can produce reliable DTM in forest areas.

Obtaining reliable environmental values in vast geographic areas is usually costly and difficult; therefore, the ability to predict unknown values or in other words, the use of better interpolation methods is very important. Interpolation methods utilize a set of different mathematical and statistical models to predict the unknown values. The similarity of the unknown points to the nearest known points or the principle of the nearest neighbor is the basis of interpolation methods, and how this principle is used depends on the selected model. In a general classification, interpolation methods are divided into two large classes. The first method is deterministic, in which interpolation is carried out based on determining the level of sampled points and also based on the similarities such as Inverse Distance Weighting (IDW) method or Radial Basis Function (RBFs). In the second method, interpolation is probabilistic – geostatistical, that is done based on the statistical properties of the sampled points. On the other hand, due to the growing increase in the problems of urbanization and urban heat islands, current cities need to have a detailed planning for future developments and preserving the quality of urban environment. Also, the geometry of urban valleys, which is defined by changing the height, length and distance of buildings, has a significant impact on the energy exchange and thus, the temperature of urban areas. But, this temperature, in turn, depends on a number of geographical - geometric factors (such as SVF) and meteorological variables. The Sky View Factor (SVF), as one of the usual indicators of describing urban geometry that refers to the amount of sky observable from a point on the Earth, has become one of the most important predictors of UHI due to its applicability in the urban climate, its contribution to the spatial data, and the existence of available techniques. In the climatic studies, the SVF is also considered as an important geometric parameter due to its correlation with the local temperature performance and its potential importance in the urban design process.Although urban Climatologists know this indicator well, it is not that much known among the urban designers and planners. This issue has not progressed much in Iran and there are no reliable sources about it. Despite the fact that different methods and models have been introduced for interpolation of Point data, no specific method has been proposed for estimating this index. Hence, this study has empirically compared the interpolation models with an emphasis on the Empirical Bayesian Kriging (EBK). This comparison is important since EBK has automated the most difficult aspects of the construction of a kriging model. This is while in other Kriging methods, the parameters are adjusted manually to obtain accurate results. EBK automatically simulates and calculates these parameters through a setup process. In classical kriging, it is also assumed that the estimated semivariogram is a true semivariogram of the observed data. This means that the data are generated from Gaussian distribution with the correlation structure defined by the estimated semivariogram. This is a very strong assumption, and it rarely holds true in practice. Accordingly, measures should be taken to make the statistical model more realistic. 

 The present study is an applied research in terms of its objective and it is quantitative in terms of the data analysis method. The study area is district 6 of Shiraz Municipality (496 hectares). Due to the multiplicity of interpolation methods and techniques as well as kernel functions and model fit functions, about 138 interpolation scenarios arewereimplemented. Also, four indices of Root-Mean-Square (RMS), Mean Standardized (MS), Root-Mean-Square Standardized (RMSS) and Average Standard Error (ASE) have been used for evaluating the models. The input data (sample) contains 6157 points, measured at intervals of 30 m distances in the study area. These points are werecreated based on the SVF calculation software method and using the GIS base model in ArcGIS10.6.  

Out of 138 scenarios, seven scenarios with the lowest RMS values arewereseparately examined in detail taking into account three other indicators. Another variable called “Neighborhood type” iswas added to the surveys in two standard and smooth modes. The results show that simple kriging and EBK have better results than the other models. Also, among the simple Kriging fitted models, the RQ model shows better results than other fitting models.  

Based on the RMS index, EBK is one of the best reliable automatic interpolation models (ranked second) for estimating the SVF. In general, based on RMS, MS, RMSS, it is the best automatic interpolation model for estimating SVF.

Determination of precipitation in energy balance calculations are vital for hydrological studies and meteorology. Due to the importance of precipitation data in different sciences and the absence of a wide and appropriate rainwater meter, precipitation data needs to be estimated in some way. One of the ways to estimate precipitation is the use of satellite data In this study, GLDAS, CRU, GPCP, TRMM, CMAP and NCEP-NCAR models are evaluated with station data in Alborz, Qazvin, Zanjan, Kurdistan and Hamedan provinces. The results showed that GPCP, TRMM, CMAP and NCEPNCAR had good outcomes in these regions, among which GPCP and TRMM provided better results.In the evaluation of GPCP with mean stations in the study area in pixel 3 in 2003, the explanatory factor (R2), EF coefficients, average error margin (MBE), absolute error of error (MAE) and root mean square error (RMSE) were 0.96, 0.94, 3.13, 5.30, and 6.58, respectively. In addition, precipitation data model of GLDAS is evaluated with station data. Results show that GLDAS model is not very accurate in areas with high precipitation such as Rasht and Noshahr stations.

The over-exploitation of groundwater has led to many problems in the country. Since groundwater level is a variable that varies over the time and place, it can be considered as a spatio-temporal dataset. The purpose of this study is to investigate the spatial-temporal variation of the groundwater level in Jask plain from 1997 to 2013 to determine the spatial trend of groundwater changes. First, interpolation was carried out based on the Kriging and the Radial Basis Functions (RBF), and then accuracy was evaluated using MBE, MAE and RMSE statistics. The findings suggested that, compared with RBF, Kriging can estimate groundwater levels more accurately in the study area. Consequently, for each time in the study period, a groundwater level map was produced based of the method. To identify the spatial variability of the groundwater level, R2 and Man-Kendall test were used. The results of the R2 statistics indicated a significant variation in the water level. Similarly, the results of the Man-Kendall test showed a decreasing trend in the north-to-northwest margin with a high intensity of nearly -1. Generally, in different parts of the study area, the process of change has a specific and meaningful pattern.

Climate zoning is the identification of zones with the same climate. With the expansion of quantitative methods, traditional methods of cluster classification have been replaced by new methods, such as various interpolation methods in the field of climatological zoning studies. In this study, we evaluated the zoning of radiation effects on the administrative spaces of Kerman city. Accordingly, the ordinary Kriging interpolation method is used along with circular, Gaussian, and spherical models for data interpolation with error criteria including root square error (RMS), its standardized value (SRMS), standard mean (Ms Mean Mean), and Mean Square Error (ASE). These factors are intended for accuracy evaluation. This research is a descriptive-analytical study on the basis of spatial analysis using the GIS system. The results of the final maps produced for climate zoning (radiological factors) showed that the angle of the sun shine is right in the equinoxes and horizontal in the revolutions. Therefore, radiation is more in the offices uptown and less in the ones downtown. The latter case is due to the presence of mountains in the south of the city. Also, solar radiation is maximal in the northern and eastern regions while it is the lowest in the west and the south. In proportion to the AD months and with regard to the amount radiation in offices in equinoxes and revolutions, it was found that the Gaussian distribution spectrum and the angle of radiation have the greatest effect on the offices in the north of the city, which is due to the position of those buildings to the sun.

In developing countries, especially Iran, public transport is still inefficient. Several factors are involved in this inefficiency, one of which is urban morphology. Identification, quality, dimensions, and the effectiveness of this issue in recent decades have led to the evolution of inter-city transport in some countries, so understanding such evolution on public transport is essential. Therefore, the present study aims to investigate and analyze the barriers to urban morphology affecting the underdevelopment of public transport in Ahwaz. This research is an applied-theoretical, and descriptive-analytical and survey study in terms of aim and method. The required data were collected through documentary, library, survey, and interviewing with citizens and experts. The ARAS decision-making method was used to rank morphological barriers in each mode of transport. Moreover, ARG GIS10.3 software was employed for zoning these barriers in Ahwaz city. After interpolating barriers of each dimension using the Reclassify tool which is a subset of Spatial Analyst Tools in Arc Toolbox, the maps were drawn in different zones in five spectra and were finally overlayed using the Weighted Sum Model (WSM). The results show that 35 factors in 12 morphological dimensions are considered as barriers to public transport development in Ahwaz. Exogenous development, urban distribution, and administrative buildings of the Oil Company with weights of 0.0392, 0.0322, and 0.02089, respectively, are the most frequent barriers to the morphology of public transport development in Ahwaz. The research also proved that the effect of these barriers are different in the four current public transport modes of Ahwaz. Finally, the zoning of these barriers illustrates that most of Ahwaz area is morphologically moderate, but the southern area is less desirable than the northwest part, and the central zone is slightly desirable. Districts 6 and 7 are the least and most desirable areas, respectively.