جستجوی مقالات مرتبط با کلیدواژه "درخت تصمیم گیری" در نشریات گروه "جغرافیا"

Floods play an important role in the flow of rivers, so their investigation and analysis are importance. Studying the dynamics of floods and the water discharged into the sea (plume) is very important in the fields of fisheries, sedimentation, transportation and environment. Babolrud-River originates from the south of Babol city and flows into the Caspian-Sea after traveling about 67 kilometers. In this research, the expansion of the plume entering from the Babolrud-River to the Caspian Sea during the spring flood of 2018 has been investigated. For this purpose, firstly the images of Sentinel-2 satellite were taken, then the required pre-processing including geometric and radiometric correction was applied. According to the spectral behavior of muddy and clear waters, in the spectral range of wavelengths of 0.4 to 0.78 micrometers, this phenomenon can be distinguished. As a result, by using this feature and the optimal index factor (OIF), the best color combination with the largest information was detected. The combination bands of 3, 4 and 8, with the OIF of 0.19, was defined as the best band combination. In the next step, NDVI, NDFI, and MNDWI were applied, and thresholds were applied to the defined indices for better separation of muddy and clear waters. These thresholds were identified by drawing spectral profiles at the plume of river and checking their histograms. Finally, by building the decision tree with all these indicators and applying the thresholds, the amount of muddy water from the flood entering the Caspian Sea from the Babolrud-River was revealed.

The advantage of these markets is the direct supply of products by producers and reducing the cost of sales and marketing of farmers due to direct sales of the product. Based on this, the project intends to locate local rural markets, which are one of the main transformational methods of rural development. The present research is applied in terms of purpose and descriptive-survey in terms of data collection. The statistical population of the study is 135 villages with rural center in Khorasan Razavi province. The main tool for collecting data and measuring research variables is a questionnaire. The reliability of the questionnaire using Cronbach's test with 0.853 indicates that the questionnaire has a good reliability.Data were analyzed using SPSS software in the form of Friedman test, decision tree and k-means cluster. The results show that among 68 indicators, the average ranking of indicators related to tourist attractions, market-related activities and agriculture and horticulture have achieved ranks 1 to 3, respectively. Based on the decision tree analysis, 31 villages were classified as suitable for establishing permanent local markets. Cluster analysis based on impact factor put 2, 25 and 5 villages in priority 1 to 3 for market implementation, respectively. Based on the results, 20 villages were identified as suitable for creating a local road market and 89 villages as suitable for establishing local periodic markets. In relation to the upcoming research, it is also suggested to strengthen the expansion of the virtual market in the selected villages for the establishment of the Danish market.

Wind erosion as an “environmental threat” has caused serious problems in the world. Identifying and evaluating areas affected by wind erosion can be an important tool for managers and planners in the sustainable development of different areas.  nowadays there are various methods in the world for zoning lands affected by wind erosion. One of the most important methods is the use of satellite images and various classification methods. Satellite imagery with features such as wide coverage, repeatability and continuous updating is particularly important in determining land cove.  classification methods include pixel based, object oriented and map decision tree. Field studies on the spatial development of wind erosion sites are difficult and expensive to replicate and monitoring studies in these areas are not possible. the purpose of this study is to evaluate the classification methods in the detection of the Sarakhs plain sandy zones in order to identify endangered sources of these zones.

In this study, the Landsat ETM + satellite data was used from USGS web site and all the processed satellite images was done with ENVI software and Arcmap 10.3 GIS. After pre-processing the images, including geometric, atmospheric and radiometric corrections, the land use map was prepared using a supervised classification method in six classes. These classes include agricultural lands, barren lands, sand dunes, wind deposition, lakes and rangelands. Classification was performed based on all the algorithms of pixel based, object oriented and map decision tree methods. These algorithms include maximum likelihood, minimum distance, neural network, and support vector machine in the pixel based method and The object-oriented approach used the nearest-neighbor algorithms on the scales of 1, 3, 5, 7 and the support of vector machine. The final classification was done by a decision tree method map. Parameters used for validation of the results include total accuracy, kappa coefficient, accuracy matrix of the producer and the produced, quantity and allocation disagreement.

The results of the classification show that the number of pixels in the training samples is 25049 pixels obtained by random sampling. The number of ground points used to estimate the overall accuracy of the produced maps are 90 control points from Google Earth satellite imagery, 50 control points from 1: 50000 topographic maps and 45 field control points. The evaluation of classification methods showed that higher accuracy percentage for decision tree method is 87%, kappa index 82%, Quantity disagreement 6.7% and allocation disagreement 5.6% Compare to other methods. These coefficients in the pixel based method are respectively 83%, kappa coefficient 78%, quantity disagreement 10.4% and allocation disagreement 6.1% And in object-oriented method, the overall accuracy is 80%, Kappa index 75%, quantity disagreement 83% and allocation disagreement 7.6%. The least producer and user accuracy in all three methods is related to sand dune class and the highest amount of quantitative disagreement is assigned to the pixel based method for the class of wind deposition and rangelands, In the object-oriented method, it is related to the class of agricultural lands and sand dunes, and in the decision-tree method, it is related to the classes of agricultural lands and rangelands. This may be due to the lack of acceptable separation of the sand dune class.

In this study, it was assumed that the object-oriented classification method would more accurately classify sand dunes and zones but since the sand dunes of Sarakhs do not follow specific morphology and geometry and they are more longitudinal Therefore, the classification of these zones was performed better with the pixel based method. But the land use, such as agricultural that follows geometric shapes, was more accurately classified in the object-oriented method. The area of sandy lands, including hills and sandy zones, was estimated to be about 1349 km2. Most of these lands are located in the central part of the study area in the vicinity of biological and physical elements. Also, the comparison of the area maps shows that the area of land using water levels and agricultural lands are close to each other. And the area differences are mostly related to rangelands, barren lands and sandy areas. Based on the results of this study, it can be suggested that decision tree method is more suitable than pixel based and object oriented methods for classifying land cover and detecting sandy zone changes and the most important reason is the use of both algorithms.

IntroductionRemote Sensing is an effective tool for detecting and monitoring plume areas. Landsat8 satellite can be used for marine applications and the reason that it was used in this study was the need for a higher resolution to detect a Plume. The satellite has a resolution of 30 m and there is a 16-day spatial resolution. It was the first time that the remote sensing was used to detect the Arvand River's Plume. Because of human population growth and industrialization, there is an increasing pressure on coastal areas and it is important to evaluate the quality of water. Accordingly, remote sensing plays an important role. Considering the vast amount of water covering the surface of the earth, using field measures to study water resources is costly. For this reason, it has taken its place in the processing of satellite imagery. An interesting mesoscale feature of the continental and shelf sea is the plume produced by the continuous discharge of fresh water from a coastal buoyancy source (rivers, estuarine or channel). Coastal plumes resulting from the continuous discharge of brackish or fresh river water are common features ofcontinental and shelf seas. Inside the plumes, a set of physical and chemical processes occur. Plume areas are excellent sources of nutrients. They have a great impact on marine ecosystems. They are identified as water masses with decreased salinity relative to the ambient ocean water. The Arvand River is a permanent river located in the Gulf region and the Oman Sea. The length of its central part is 84 km and its length is about 190 km. The annual average of the discharge is estimated to be 761 to 792 m3 /s. The tides are mixed at the mouth of the Arvand River.
MethodologyIn this study, in order to detect the Arvand River plume, Landsat8 satellite images of October 2016 were used. The downloaded images did not have any cloud cover. River plumes with very high sediment loads have been widely studied by remote sensing technology. The suspended sediment increased the radians caused by surface water. It was in the visible and near-infrared region of the electromagnetic spectrum. The amount of impurities based on NDWI index was negative and the water was purer than the positive NDWI. The plume had more suspended sediments than its surrounding waters, so its NDWI index was less than the seas. The plumes were identified as water masses with decreased salinity relative to the ambient ocean water.
The plume had more radians (energy) than the surrounding waters. Indeed, the NDWI index of the plume had a lower content and the Salinity Ratio Index of the plume was lower. Then, to detect plume verifications, an image of the Sentinel-2 satellite of October 2016 was also produced. The Sentinel-2 satellite in the blue, green, red, and infrared bands had a resolution of 10 m. The Sentinel 2A satellite was launched in 2015. Using the ENVI software, the radiometric correction was first performed on images. After obtaining radiance and reflectance, the NDWI index and Salinity Ratio were calculated. These four conditions were considered for the detection of the plume. Then, using the scatter plot, the thresholds mentioned in the algorithm were determined, Finally, using the decision tree, the subscriptions of these four indicators were extracted and two plume and non-plume were obtained. In addition, in this study, the NSMI index was used to classify suspended material concentration, and the results showed how the plume dispersion was developed based on this index. In addition, to determine the core of the plume and coastal waters, the NSMI index was used. The more the water, the cleaner and purer it is. The NSMI was more negative. When the water had more suspended sediment, the NSMI was more positive. The NSMI had a fluctuation between one to one negative.
DiscussionIn this study, the scientific theories in relation to a plume were proved through the indicated indices. Also, through the use of an algorithm and Landsat 8 satellite imagery, successful results were obtained from the Arvand River Plume. In this study, plume and coastal waters were categorized using a decision tree. In addition, four different water zones were determined based on the spectral properties. Providing accurate and up-to-date information on the dynamics of the plume can lead to the better protection of the coast.
ConclusionThe results of this study can be used to monitor water quality. In October, Radian Band 4, Radian Band 2, NDWI, and salinity ratio matched the preconditions. The core of the plume was based on the distance from the river mouth.The Plume Core (the part with the highest concentration of suspended matter) was located adjacent to the mouth of the Arvand River.

Understanding and determining the amount of carried sediment by river have been considered by experts because of the importance and the role of sediment transfer in water-shed basins subject , among them is rivers organizing that carry out for erosion and sedimentation control or river-bed stabilization and flood eject. The current study aims at determining the efficiency of decision tree model in estimating suspended sediment of Meimeh river. The data used in the study includes sediment ,water , rain fall , and daily discharges related to the statistic periods from 1967-68 to 2009-2010. After data processing 554 records with accessible statistic discharges and their corresponding sediment were chosen and the obtained results were compared using sediment rating curve. To this aim, statistical criteria of R2 , RMSE, MAT , R and Bias were applied. To investigate, the rain fall effects and daily discharges on precise measuring of sediment by tree model, the data related to the rain fall and daily discharges were added to the model. The results showed that the decision tree model has presented reasonable results for the simulation of the suspended load in the present study station. So that based on criteria RMSE, MAE, r2 and Bias decision tree with less error than the sediment rating curve deposits is estimated. The results did not change much and sediment discharge rate is most correlated with the corresponding discharge of sediment.

Soil temperature and its changing with regards to place and time is not only one of important factors that effects on energy and material exchange but it may be said the rate and direction of all physical processes of soil are temperature dependent directly or indirectly. The Surface Energy Balance Algorithm for Land (SEBAL) is a rather new algorithm used to estimate the temperature and other fluxes on surface in most parts of the world that has satisfactory results. For accessing to the aims of research, at first, the heat map was prepared using SEBAL algorithm and decision tree classification by ArcGIS 9.3 and Envi 4.4 software. On the other hand, we extracted digital model of height, slope, lithology, direction and the dominant landform of the study area. Then, with the aim of studying the statistics of surface temperature at heights, slope, lithology, directions and landforms, the zonal statistical analysis was used. By choosing the ETM image at May of 2011, and because of single heat band, we used from SEBAL method for estimating the surface temperature of the land. In this method, we get the surface temperature was obtained based on corrected heat radian. For computing the emission rate at heat band we need to compute spectrum radian (Lλ), the reflection rate at each band (Pλ) and surface. The results showed a significant correlation between elevation, slope and aspect surface temperature is (respectively: ) Moreover, minimum temperature is in Qa3 formation (new andesite of Taftan) and maximum temperature is in qlu formation (siltstone with lichen with middle layers of tuff andesite). Also the most temperature average is in Ef (sandstone and shill) and the least temperature average in Qla (old andesite flows). It seems that because of andesite formation placement of high and low heights, direction has more important role at the temperature decrease of this formation, by the way, height factor has effect on temperature decrease in this formation. Regarding temperature conditions in geographic directions and different foramtions, could plan for implanting compatible agricultural corps and products and appropriate environmental conditions.

1- Building detection by satellite images decrease not onlyhuman role in city map production but also time and cost for those map production this also provide the opportunity for building map production in monthly and yearly periods. The mayoralty and all city organizations need an updated building maps. In the past, building detection from digital images was done manually and as a result, this process which was done slowly and costly, needs professional operator. This kind of detection was not appropriate for city area with high intensity.today, high resolution satellite images areprovided using remote sensing technology development. By use of these images, we are capable of Land use classifyingin city area. In high measure IKONOSSatellite was known as the first high separation commercial satellite in 1999.Afterthat similar satellites such as and quick bird geoeye werelaunched. Using a suitable automaticOr semi-Automatic method for building detection not only reducehuman role in city map production but also reduce cost and time for the map production and provide us with an opportunity to produce building maps in monthly and yearly periods.In addition,this method is useful for other objects with similar nature and geometry.Nowadays, mayoralties and other organizations which need updated information related to domains and city alley undergo many coststo survey domains by difficult operations and many professionals, most of the time, the accuracy of information was not satisfying and this lead to repetition. 2- In this research,multi spectral and panchromatic images of band1 to 4 of quick bird satellite were used to obtain city object Class boundary such as buildings,roads,plants, etc. The method is based on pixel base information using decision tree algorithm,i.e,by determiningSuitable there should level based on each phenomenon spectral characteristics,objects were deletedand finally building classes were detected based on study purpose. The above mentioned activates were done on images related to 2008 and 2012 and then building change maps were detected,finally,the output map was compared with domain digital maps By city survey and the method accuracy was evaluated. • By checking phenomenon observed in chabaharr satellite images,Decision tree for separation of following objects was chosen: • Plants,park and vegetations • Black top of street and ally surface • Building back top • Building and tree shadows which are observable because of time of recording • pavementcovered by dust which are part of wasteland, • Main buildings produced by other phenomenon separation. 3- After that, related phenomenon in each class of 2008 and 2012 images were separated and change percentage was calculated building courage percentage in 2008 image was 16.41 which was increased to 17.57 because of black tap percentage of 1.16 this percentage was increased to 24.69 in 2012 image; i.e. we had the increase of 7.12 percentage as a result of new construction in the period of 4 years. 4- After accuracy evaluation using survey experimented information and obtaining building parcels diversity in 2 layers, we observed the diversity about 8.2 percentage which is explainable; this diversity can be because of different errors of measurement such as, using map whit 2000/1 measure as a base map for survey, errors during detection without reduction unbuilt area such as in survey map. Therefore, this method can be usual for new building detection without local reference.

One of the major challenges in the Iran water resources management is reduction of Helmand River’s inflows that has happened several times in recent years. Increasing in the basin’s cultivated area (mainly after Kajaki dam) and the recent droughts are declared as the reasons; however none of them is analyzed in a quantative manner. This paper aimed to address this issue and at this stage evaluated land cover changes in the last two decades using remote sensed data. Due to importance of the selected algorithm for classification, three methods have been applied for the evaluation, including maximum likelihood classifier (MLC), decision trees (DTs) and support vector machines (SVMs). It is obvious that direct sampling was not possible from the study area, therefore the FAO land use maps, watershed atlas of Afghanistan (AIMS), and Google Earth images were applied in this regard. Considering the capabilities of Landsat (ET and ETM), three images for 1990, 2001 and 2011 during growing season (all in May) were prepared and processed for this study. The results were evaluated using Kappa coefficient and overall accuracy, which showed almost similar performances of the algorithms. It was concluded that the total cultivated area in the region increased from 103’000 ha in 1990 to 122’000 ha in 2001. Notably that this amount increased to 167’000 ha in 2011. These changes show definite impact of land use change on the river inflows. In spite of similar results of the applied methods, we found DT method more suitable for such an analysis due to its computation cost and efficiency as well as less relying on training samples.

In a wide variety of scientific climatology studies earth surface temperature, is important, Astronomy, meteorology hydrology,ecology, geology, medical science, design and optimization of transportation network and site selection of fire extinction and particularly cases required. In the calculation of the actual evapotranspiration also we consider these.. Considering the earth's surface temperature monitoring in a limited number of meteorological stations to the distribution point and the need to place the surface temperature in a wide area and at the same time the surface temperature were estimated. To access the earth's surface temperature and classification SEBAL algorithm and decision tree were used. Using ETM + image dated 31 August 2000 and pre- process, files became ready for implementation. For processing of SEBAL method. the above mentioned software Envi4.5 and ArcGIS9.3 were used. This paper estimates the difference less than 5.57° C, temperature difference between a satisfactory level was estimated through remote sensing and statistics. Temperature measured from ground level 12 years (1993 -2005) in Maragheh meteorological station was achieved.Temperature was estimated through remote sensing and studies applicable in earth sciences research and the environment.