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Volume 17, Issue 47 (12-2017)

The attempt to recognize phenomena and affairs has always been a concern of the human mind and has constantly sought to complete this knowledge. The correct recognition is also achieved when the real nature of phenomena is clear to man. The phenomena are based on their own philosophical foundations and, therefore, their understanding requires perception these philosophical foundations and using proper methods of recognition. The map is also a phenomenon that has its own philosophical foundations and by understanding these philosophical foundations, the true meaning and the components that influence its meaning are clarified. Recognizing it correctly requires understanding many of the elements and other factors. To real understanding this phenomenon, one needs to understand beyond what is usually said about it. In this research, we tried to clarify the philosophical foundations of the map and the factors influencing its meaning by using of hermeneutical methodology. The results of this research showed that the map of the ontology aspect is of an objective-subjective nature. Therefore, it should be understood by methodology such as hermeneutics and not explanation. Also, using this method, it is determined that the mapping factors are divided into two categories. Internal factors, such as the choice of the type of projection and cartographic deviations and external factors such as, the mental purpose of the cartographer and the banners, understand map reader from map, and the spaces of thought, power, and so on make up the actual meaning of the map.

Bakhtiar Feizizadeh, Ali Khedmat Zadeh, Mohammad Reza Nikjoo,,
Volume 18, Issue 48 (4-2018)

Remote sensing technology is one of the most efficient and innovative technologies for agricultural land use/cover mapping. In this regard, the object-based Image Analysis (OBIA) is known as a new method of satellite image processing which integrates spatial and spectral information for satellite image process. This approach make use of spectral, environmental, physical and geometrical characteristics (e.g. texture, shape) together images contexts for modeling of land use/cover classes. The main objective of this study is to classify micro land use/cover of Meyandoab County by applying appropriate and effective algorithms and parameters in the object based approach. For this goal, Quick Bird and Aster satellite images were used within the integrated approach for processing and land use modeling. Accordingly, the land use map was classified in 9 class based on spectral and spatial characteristics.  In order to perform OBIA, the segmentation was applied in the scale of 10, shape parameter of 0.7 as well as the compactness of 0.3. In terms of the classification task, fuzzy based algorithm and operators (AND, OR) was applied to detriment the membership functionality of segments for each class as well as classifying the related objects.  We also applied textures, geometric, NDVI, GLCM, brightness algorithms based on fuzzy operators and assign class algorithm. In order to applying the validation of results, the accuracy assessment step was performed and the finally overall accuracy of 93.6 was obtained for the derived map. The Kappa coefficient was also detriment to be 0.92. The area under cultivation included respectively for lands of wheat and barley, prunes and plums, apples, vineyards and alfalfa hay2622.42, 4505, 4354.55, 4457.85, 14110.58 hectares.

Ms Akram Hedayati Dezfuli, Ms Zahra Ghassabi,
Volume 24, Issue 73 (8-2024)

Flood is one of the most destructive natural phenomena. Every year it brings extensive losses to the country’s financial and human resources. In our country, major parts of Iran’s provinces are always at risk of flooding. The Gorgan and Atrak catchments have also become more important, as several floods have occurred in Golestan province in recent years, causing many deaths and economic losses. The purpose of this study was to investigate the synoptic and thermodynamic conditions of the March 2019 flood event in Golestan province in order to atmospheric system that lead to such floods. This study includes statistical analysis of provincial stations (Gorgan, Gonbadkavus, Aliabadkatol, Hashemabad, Kalale, Maravetape and Bandaretokman), calculating of the return period of precipitation during the available statistical period of each station, analysis of synoptic maps on the day of the flood event, the analysis of satellite images of the days involved in the flood, and calculation of instability indices of the Gorgans’s station. Statistical results showed that Gorgan and Gonbadkavus stations, with the highest amount of rainfall in March 2019, had a return period with 800 and 400 years respectively. Also the highest amount index of Gorgan with values of K=26°c, PW= 0.27 cm and TT= 48 was obtained with high relative humidity (about 80%). The analysis of the synoptic maps showed the severe sea level pressure and mid- level height drop with a deep trough in the study area, which led to extreme rainfall.
Key words: Flood, return period, Synoptic maps, instability indices, Golestan province.

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