Geographic Data
Keyvan Mohammadzdeh; Sayyed Ahmad Hosseini; Mehdi Samadi; Ilia Laaliniyat; Masoud Rahimi
Abstract
Extended Abstract
Introduction
Landforms represent influential processes affecting features on the earth’s surface both in the past and in the present while providing important information about the characteristics and potentials of the earth. The shape of the terrain and features such as landforms ...
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Extended Abstract
Introduction
Landforms represent influential processes affecting features on the earth’s surface both in the past and in the present while providing important information about the characteristics and potentials of the earth. The shape of the terrain and features such as landforms affect the flow in water bodies, sediment transport, soil production, and climate at a local and regional scale. Identification and classification of landforms are among the most important purposes of geomorphological maps and also a fundamental step in the process of producing such maps. Geomorphologists have always been interested in achieving a proper and accurate classification of landforms in which their morphometric properties and construction processes are clearly indicated. The present study has attempted to develop a new method and identify the relationship between morphometry of landforms and surface processes using a multi-scale and object-based analysis. Extraction and classification of landforms are especially important in mountainous areas, which are considered to be dynamic due to their special physical and climatic conditions. These areas are often remote and sometimes unknown. Mountainous topography has also made them difficult to access. However, they are of great importance due to their impact on the macro-regional system. Because of this significant importance, Maku County was selected as the study area.
Materials and methods
Maku County is located in northwestern Iran (West Azerbaijan Province) which borders Qarasu River and Turkey in the north, Aras River and the Republic of Azerbaijan in the east, Turkey in the west, and Shut County in the south. This County is located between 44° 17' and 44° 52' east longitude and 39° 8' and 39° 46' north latitude. The present study takes advantage of satellite images (sentinel-2A) with a spatial resolution of 10 m, derivatives of DEM layer (slope, maximum curvature, and minimum curvature, profile and plan curvature) and object-based methods to identify and extract landforms of the study area precisely.
Discussion and results
The present study applies various functions and capabilities of OBIA techniques to extract landforms precisely. These functions include texture features (GLCM), average bands in the image, geometric information (shape, compression, density, and asymmetry), brightness index, terrain roughness index (TRI), maximum and minimum curvature, texture, and etc. The image segmentation scale was first optimized in the present study using ESP tools and objects of the image were created on three levels (9, 17, and 27 scales). In the next step, sample landforms were introduced, membership weights were calculated and defined for the classes in accordance with the fuzzy functions, and finally, 14 types of landforms were extracted using object-oriented analysis.
Conclusion
Fuzzy method includes boundary conditions, defines membership function, and constantly considers landform changes in class definition. Thus, it seems to be ideal for the purpose of the present study. The present study used two types of data (data derived from satellite imagery and DEM layer) along with OBIA approach to extract landforms. Classification of landforms based on fuzzy theory makes it possible to collect more comprehensive information from the earth's surface. Results indicate that fuzzy object-based method has classified landforms with an accuracy of 87% and a kappa index of 85%. Considering the resolution of the images applied in the present study, all features were extracted with an acceptable accuracy except for debris. This can be attributed to the fact that debris is usually accumulated in a small area on steep mountainsides, and thus remains hidden from satellites in nadir images. OBIA approach shows a high efficiency because it can combine spectral characteristics of various types of data (i.e. images and DEM data) and their derivatives while analyzing the shape of the segment, and size, texture and spatial distribution of segments based on their class and other neighboring segments.
Geographic Information System (GIS)
Zhila Yaghoubi; Ali Asghar Alesheikh; Omid Reza Abbasi
Abstract
Extended AbstractIntroductionSelecting a suitable place for a new retail store is a very important decision since new shops cost a lot and new retailers puts themselves at financial risk. Physical location of stores affects the consumer's perception of their first purchase and their subsequent loyalty ...
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Extended AbstractIntroductionSelecting a suitable place for a new retail store is a very important decision since new shops cost a lot and new retailers puts themselves at financial risk. Physical location of stores affects the consumer's perception of their first purchase and their subsequent loyalty to the store. Therefore, spatial analysis is very important for retail stores. Site selection for retail stores has always been difficult and the current competitive market has made decision making even more difficult since stores face increased competition and consumers have many options to satisfy their needs. They generally choose a suitable store in their vicinity which provides high quality, cheap, and diverse products. Therefore, markets and especially retailers shall follow an accurate and valid location strategy for new stores. Retail stores have various marketing and customer service strategies. Marketing strategies require a lot of information about different aspects such as customers, shops, competitors, and products. Many marketing strategies only provide information about consumer behavior or customer satisfaction. However, spatial aspects are more important and in fact determine future success of a store. Several methods are used for spatial analysis in retail sector. The present study use a multiplicative interaction model to forecast sales of confectionaries. This can help retailers develop strategies and find an optimal location for their new stores. Materials & MethodsThe present study has developed a location-based marketing model for online confectioneries in Tehran which can improve site selection strategies of new confectioneries. This marketing model is based on the multiplicative competitive interaction model (MCI) of the retail location theory. To do so, characteristics attracting customers to confectioneries are determined and related data are collected from the Snappfood online platform through web crawling. ArcMap software is then used to analyze and process the collected data. After data normalization, MCI model is implemented using Python programming language. The model is then calibrated using 80% of the collected data and the ordinary least squares (OLS) method. The model is then evaluated using root mean square error (RMSE) method and the remaining data. Results and DiscussionMean errors obtained for districts number 1 to 22 of Tehran municipality show high accuracy of the model. Snappfood site lacked any information about districts number 9 and 18 and thus these districts were not considered in the calculations. Depending on the available data, other districts showed different levels of accuracy. Results indicate that district number 22 had the lowest level of accuracy and district 17 had the highest level of accuracy. In general, this model predicts customer behavior with an error rate of 17.03%. Results of the present study show the probability of purchasing from each confectionery which can be used to map market potential for a new store. This map determines the best place with maximum sale and helps in site selection for new stores based on specific features of the store, competitors and the environment. ConclusionsMCI model predicts sales. From a geomarketing perspective, this model shows that distance between customers and the store and accessibility affect location strategies in new stores. Variables such as pricing and customer satisfaction (scoring) are used to improve the goodness-of- fit of the model. This precise method identifies some key factors to success in a retail strategy. It predicts the probability of purchasing in each district, the number of customers in each store, and distribution of customers in each district. Experts and new retailers can use the results to design various location and sales strategies. Using this model, new retailers in confectionary market can accurately predict their sales before even opening the store and thus protect themselves against possible financial losses. Moreover, this model predicts total sales of different stores and help retailers compare their market shares with those of their competitors. They also can enter features of a new store into the model and find several potential sales strategies. In other words, the model helps determine sales of existing and new shops. In this way, retailers can find an optimum location for their new confectioneries based on the principles of geomarketing.
Aerial photography
Zahra Azizi; Mojdeh Miraki
Abstract
Extended Abstract
Introduction
Advances in computer vision and the development of remote sensing instruments have made indirect measurement of tree features possible. Individual tree crown delineation is an important step towards information collection and mapping trees in an urban area. This information ...
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Extended Abstract
Introduction
Advances in computer vision and the development of remote sensing instruments have made indirect measurement of tree features possible. Individual tree crown delineation is an important step towards information collection and mapping trees in an urban area. This information is then used to help planners design strategies for optimization of urban ecosystem services and adapt to climate changes. Common methods of Individual tree crown delineation (ITCD) were based on very high-resolution satellite or Light Detection and Ranging (LiDAR) data. However, satellite data are usually covered by clouds and thus, cannot be appropriate for the measurement of individual trees. Aerial Laser scanning is also relatively expensive. Remote sensing with unmanned aerial vehicle (UAV) captures low altitude imagery and thus, is potentially capable of mapping complex urban vegetation. Automatic delineation of trees with UAV data makes collection of detailed information from trees in large geographic and urban regions possible. Therefore, a multirotor UAV equipped with a high-resolution RGB camera was used in the present study to obtain aerial images and delineate individual trees.
Materials & Methods
The present study has compared the performance of Inverse watershed segmentation (IWS) and region growing (RG) algorithms using point clouds derived from Structure from Motion (SfM) algorithm and UAV imagery captured with the aim of tree delineation in Fateh urban forest located in Karaj. Region growing (RG) is used to separate regions and distinguish objects in an image. It starts at the initial seed points and determines whether the neighboring pixels should be added to the growing region. If the neighboring pixels are sufficiently similar to the seed pixel, they are labeled as belonging to the seed pixel. To implement the algorithm, the window size and the growing threshold were set for all resolutions. In order to obtain the most appropriate size for the search window, we examined different window sizes with a growing threshold of 0.5 for each resolution. Individual trees delineation was performed for each CHM resolution in the three different sites using "itcSegment" package of R software. Watershed segmentation algorithm is also similar to RG algorithm. The only difference is that it sets the growing seeds at the local minima. In other words, the local maxima in this algorithm change into local minima and vice versa. Inverse Watershed Segmentation (IWS) method was implemented in ArcGIS 10.3 because of its capability in delineation of distinct tree entities. In the summer of 2018, three sites with different structures including a mixed uneven-aged dense stand (site 1), a mixed uneven-aged sparse stand (site 2), and a homogeneous even-aged dense stand (site 3) were surveyed and photographed, and a 3D point cloud was extracted from the images. Then, the performance of algorithms was tested using a series of different canopy height models (CHM) with spatial resolutions of 25, 50, 75, 100, and 120 cm. To generate these models, digital surface model (DSM) was subtracted from digital terrain model (DTM). Results of individual tree delineation were validated using data collected in field observation of the aforementioned sites.
Results & Discussion
Results indicated that both RG and IWS algorithms yielded their best performance in the dense homogeneous structure. Moreover, the number of segments resulting from CHMs with low resolution was often much more than the actual number of trees. This was due to the occurrence of several peaks within an individual tree crown especially in low resolution images. With an F-score of 0.88, homogeneous even-aged dense stand (site 3) showed the highest overall accuracy in RG algorithm with a pixel size of 75 cm. Generally, results indicated that RG is an appropriate approach for individual tree delineation due to its flexibility in delineation of varying crown sizes. Furthermore, this method does not assume a circular shape for tree crowns and thus, is capable of detecting and segmenting irregular crowns. Generally, delineation of trees in urban forests using CHMs obtained from UAV-captured aerial imagery was highly accurate in homogeneous sites, while such models lacked efficiency in heterogeneous sites.
Geographic Data
Shahin Jafari; Saeid Hamzeh; Hadi Abdolazimi; Sara Attarchi
Abstract
Extended AbstractIntroductionHuman activities as well as environmental and climate changes affect the trends of wetlands. Detecting and monitoring aquifers are considered to be very important for evaluation of past, present, and future influential factors, and the findings of such studies are essential ...
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Extended AbstractIntroductionHuman activities as well as environmental and climate changes affect the trends of wetlands. Detecting and monitoring aquifers are considered to be very important for evaluation of past, present, and future influential factors, and the findings of such studies are essential for taking measures and making decisions based on the goals of sustainable water and soil resources management. Over the past decade, many researchers around the world have been attracted to remote sensing and especially satellite remote sensing and used this technology to detect such changes over time. The present study has used Landsat (monitoring the area of water body), TRMM (monitoring rainfall), MODIS (monitoring vegetation and evapotranspiration), Grace (monitoring groundwater) satellite images available in Google Earth Engine to study last two decades changes (from 2000 to 2019) in Maharloo wetland, Goshnegan catchment and their surroundings. Materials & MethodsMaharloo wetland is located in Fars province and Goshnegan catchment (426 square kilometers). The present study has used Landsat 7 and 8 images to extract the area of water body, TRMM images to obtain precipitation values, MODIS products to calculate NDVI and evapotranspiration, and data received from Grace to extract changes in groundwater level. These satellite images were available in Google Earth Engine. Mann-Kendall test was also used to assess the overall trend of the aforementioned factors. Results & DiscussionThe automated water extraction index was used in the present study to identify and estimate the area covered by water bodies in the study area. The largest area belonged to 2006 (216.76 square kilometers) and the smallest belonged to 2018 (66 square kilometers). In 2000 (the beginning of the reference period), an area of 216.52 square kilometers was covered by this wetland which is close to what was observed in 2006. In 2018, this has reduced to 66 square kilometers. Thus, there is about 150.72 square kilometers (69.54 percent) difference between these two years. In 2009, the total area has reduced to 66.67 square kilometers. A numerical comparison between 2000 and 2019 also indicates a reduction of 91.17 square kilometers (42% decrease) in the total area covered by this wetland. Also, a 53.72 square kilometers (29.60%) difference was observed between the average area covered by the water body in the first and second ten years. Since calculated p-value value (< 0.00001) is less than the alpha level (0.05), so a significant trend was observed in the average annual data of the area covered by this wetland. Kendall's tau also indicated declining trend of the collected data. Groundwater level was calculated using data received from Grace Satellite to investigate the role of groundwater level in reducing the area covered by the water body. Results indicated that since 2008, groundwater level have always showed a negative value (a decreasing trend). For an instance, a groundwater level of -10.86 cm in 2019 indicates a decrease in the water level in the study area. As the calculated p-value (< 0.0001) is less than the alpha level (0.05), so a significant decreasing trend was observed in the groundwater level. Results of Mann-Kendall test (-0.6) also indicated that changes in water bodies, vegetation, rainfall and groundwater level had a decreasing, increasing, increasing and decreasing trend, respectively. No significant trend was observed in evapotranspiration. It seems that the expansion of agricultural lands and subsequent water extraction from aquifers have intensified the decreasing trend of water bodies in this wetland. ConclusionWetlands provide many ecological services including water treatment, natural hazard prevention, soil and water protection, and coastline management (Amani et al., 2019). Therefore, understanding the importance of wetlands and their management need to be seriously considered by relevant organizations in different countries of the world, and Iran is no exception. Satellite data and remote sensing methods and techniques are considered to be one of the most important and cost-effective methods of monitoring wetlands. The present study used satellite data collected by Landsat, MODIS, Grace, and TRMM to monitor water bodies, vegetation, groundwater level, and rainfall in Goshnegan catchment in which Maharloo wetland is located. The results of Mann-Kendall test showed a decreasing annual trend for changes in the average area of this wetland. This decreasing trend is considered to be a serious threat to human settlements around the wetland which can intensify over time. It will also affect the thermal islands of Shiraz and Sarvestan in near future. Obviously, management of agricultural and forest land uses with the aim of stopping their increasing trend can improve water balance in catchment areas. A 132.2 ha (approximately 36.16%) difference was observed between the average vegetation cover in this catchment area over the first and second ten years (233.4 vs. 365.6 ha). It seems that the expansion of agricultural lands and subsequent water extraction from aquifers have intensified the decreasing trend of water bodies in this wetland. Due to the proximity of this wetland to the city of Shiraz and its importance as an ecological and tourist attraction, it is suggested that related authorities (Department of Environment and Water Organization) demarcate lake bed and riparian zone with the help of remote sensing researchers to improve the management of this wetland and prevent it from drying up. Also, it is suggested that the Organization of Agriculture Jihad review and improve water consumption methods and cultivation patterns in the areas surrounding this wetland.
Geographic Data
Ali Akbar Sabziparvar; Alireza Seifzadeh
Abstract
Extended Abstract
Introduction
Ultraviolet radiation (UVA) is a dangerous part of solar radiation that makes a small percentage of total solar radiation energy (5 to 7 percent). Despite the beneficial role of solar energy in the production of vitamin D3, it can cause irreparable damage to human cells. ...
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Extended Abstract
Introduction
Ultraviolet radiation (UVA) is a dangerous part of solar radiation that makes a small percentage of total solar radiation energy (5 to 7 percent). Despite the beneficial role of solar energy in the production of vitamin D3, it can cause irreparable damage to human cells. The majority of previous studies on ultraviolet radiation in Iran have focused on in-vitro impacts of UV radiation on human health and plant physiology in a limited study area. The present study estimates daily cumulative UVA radiation in central regions of Iran and compare it with total column ozone (TCO), cloud optical depth (COD) and aerosol optical depth (AOD) in different seasons.
Materials and methods
The present study estimates daily cumulative UVA radiation (320-400 nm) over a 13-year reference period (2005-2017) in a large area in Central Plateau of Iran with arid and semi-arid climate using TUV5 multilayer radiative transfer model (Madronich, 1993). 22 synoptic stations in 9 provinces were investigated in this study. Daily cumulative UVA radiation under three different sky conditions (clear-sky, overcast and real-sky) was also compared with geographical distribution of total column ozone (TCO), cloud optical depth (COD), aerosol optical depth (AOD) and surface albedo (SALB). Required data were extracted from satellite images (downloaded from http://disc.gsfc.nasa.gov) and Iran Meteorological Organization data center.
Results and Discussion
In general, maximum daily UVA radiation was recorded in the southern half of the study area. During warm seasons of the year, the eastern part of the study area (Kerman and Khorasan-e-Jonubi Provinces) and during the cold seasons of the year, central and southwestern part of the study area (Yazd and Fars Provinces) experience maximum daily UVA radiation. Maximum cloudiness in spring has occurred in northeastern and western parts of the study area and a lower level of cloudiness has always been recorded in its southern parts. Thus, the highest level of UVA radiation has been recorded in southeastern parts of the study area and especially in Birjand station (1071.12 kj/m2 per day). As expected, maximum UVA radiations in all sky conditions and all stations were recorded in summer. The lowest level of cloudiness was also recorded in this season. During autumn and in overcast condition, the highest concentration of UVA was recorded in southeastern parts of the study area and Birjand station (725.85 kj/m2 per day). This is consistent with cloud optical depth and total column ozone, and so, the lowest amount of ozone in this season was recorded in Birjand station (276.57 Dobson). The highest values of atmospheric aerosol with an average of 0.59 optical depth were recorded in winter in the eastern parts of the study area. Thus unlike other seasons, maximum UVA radiation in overcast condition moves toward central stations in winter. Comparison of daily cumulative radiation maps in overcast condition shows that there is a good agreement between daily cumulative radiation and cloud optical depth (COD) and aerosol optical depth (AOD). This indicates that in overcast condition, total column ozone (TCO) have a weaker impact on UVA radiation as compared to other sky conditions. However, UVA radiation is consistent with total column ozone in clear-sky conditions.
Conclusions
Geographical distribution of UVA radiation indicates that maximum daily radiation in warm seasons has often occurred in the eastern parts of the study area. However, maximum concentration of UVA radiation moves towards southwestern parts of the region in cold seasons. Therefore, residents of the eastern and southwestern regions face a higher risk due to daily cumulative UVA radiation. Findings indicate high biological risk of solar UVA wavelengths in clear-sky condition within the study area. Overcast conditions can reduce daily UVA radiation up to 52% in winter and 21% in summer as compared to clear sky conditions. In real-sky conditions, daily UVA radiation decreases up to 19% in summers and up to 32% in winters as compared to clear-sky conditions. As a result of lower solar zenith angle, the impact of cloudiness on surface UVA radiation in summer is relatively less than cold seasons.
Geographic Data
Ghorban Vahabzadah Kbriya; Aref Saberi
Abstract
Extended AbstractIntroductionFrom ancient times, stone has always been a symbol of stability and strength, and ancient human beings took refuge and chose to settle in mountains and mountainsides (Santos et al, 2018: 2). However, rocks on the ground or near its surface decay and decompose gradually due ...
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Extended AbstractIntroductionFrom ancient times, stone has always been a symbol of stability and strength, and ancient human beings took refuge and chose to settle in mountains and mountainsides (Santos et al, 2018: 2). However, rocks on the ground or near its surface decay and decompose gradually due to factors such as weathering (Memarian, 2000: 2). Climatic geomorphology is a scientific field in which shape and distribution of landforms are analyzed according to climate type. Specific weathering processes affected by the climate are in place in different morphological zones (Jafaria Aqdam et al., 2012: 1). The present study seeks to investigate the lithology of southwestern mountainsides of West Azerbaijan province using Lewis Peltier model.Methods: Peltier weathering and morphogenetic models were used in the present study. Topographic, geologic, isothermal and isohyetal maps were produced using Inverse Distance Weighted (IDW) method in GIS environment. Temperature and precipitation were analyzed using different graphs and tables to determine drought and humidity conditions. ResultsResults indicated that the northern mountainside is wider and thus, its precipitation 407-477 mm and temperature of 15-17 ° C have the greatest impact on the region. Data collected from four synoptic stations in the province with a common 30-year reference period (1986 to 2018) were used to investigate weathering and morphological condition of rocks in the study area. Table (1) shows the location of these stations. Climatic data such as average annual temperature and precipitation were reviewed and corrected in ArcGis environment. Then, ArcGis was used to create a basic database to store data and prepare relevant maps. Weathering regimes are determined based on the Peltier chart (1950). In this diagram model, two variables -average temperature and annual rainfall- are used and weathering regimes are divided into seven classes each of which represents a type of weathering condition. The model of morphogenetic regimes is more similar to a climatic or vegetation classification than a weathering model. In this model, two variables of average temperature and annual precipitation are used and morphogenetic regions are divided into nine different classes. Areas having a low temperature are mainly classified as glacial areas and areas having a high temperatures and low rainfall are classified as arid and semi-arid areas. Areas having a high precipitation and temperature classified as temperate and cold areas. To apply Peltier model to the study area, the specifications of synoptic stations were first presented separately in a table. Then, zoning was performed based on the square value of temperature and precipitation using IDW method and then, the percentage of area covered by each temperature and precipitation class was determined. Precipitation class of 407-477 mm covers 32.67 percent of the area. Moreover, temperature changes in the region indicated that 15-17 ° C temperature range has covered the largest part of the study area with a percentage of 39.41. The values of temperature and precipitation along with the results of Peltier model indicated that a very low level of weathering is present in the study area. Farahmand et al. (2015; 10) have shown that temperature and precipitation parameters in this region depend on elevation. To determine the morphological condition of the region, it was divided based on its climatic conditions. To determine the accuracy of weathering results, a map of geographical directions in the region was produced. Vegetation and soil in western and northwestern parts of West Azerbaijan province have a pretty good condition. These were divided into three different classes and weighed based on the weighing parameter. Result was presented as a map and a table in which mechanical weathering with a lower-intensity had a weight of 1 and chemical weathering with a higher-intensity had a weight of 3. The classification results are consistent with Hanafi et al. (2002; 72) who introduced mechanical weathering as a factor leading to rock disintegration in northwestern Iran due to climatic conditions. They are also consistent with Maghsoudi et al. who used climatic parameters of temperature, precipitation, and weathering intensity to determine weights for the Peltier model. In mountainous areas of the country such as Zagros, Alborz and northwestern Iran, low temperature and frost may lead to a low level of mechanical weathering (Maghsoudi et al., 2010; 36).
