List of Articles Development Stages

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  1 - Investigation of the efficiency of GeoEye-1 satellite data for mapping the development stages in the forests of Northern Iran
  Amin Mahdavi Saeidi Sasan Babaie Kafaky Asadollah Mataji
  Today, remote sensing with high spatial and spectral resolutions along with the use of a variety of plant indices has provided the possibility of more accurate analysis and classification of satellite data in the identification and structural resolution of natural pheno More

  Today, remote sensing with high spatial and spectral resolutions along with the use of a variety of plant indices has provided the possibility of more accurate analysis and classification of satellite data in the identification and structural resolution of natural phenomena. Accordingly obtain information from the structure of forests using satellite data to help the management of forest renewable resources is of interest to managers and researchers. In this research, maps of the development stages of natural forests in the north of the country were prepared using GeoEye-1 satellite data and different classification algorithms in pixel-based, object-based, and model-based methods. The ultimate accuracy of the classification maps was calculated with the overall accuracy parameters and the Kappa coefficient. The results of this study showed that maximum accuracy (78%) in the object-based method was estimated on the basis of the segmentation of the NDVI and the maximum likelihood algorithm. Also, the algorithms that follow the structural patterns for the classification of the pixel distribution provided a higher accuracy. Overall, the results showed the high potential of GeoEye-1 data in mapping forest development stages. Manuscript profile
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  2 - Investigation of Height-Diameter Models in Different Development Stages of Unmanaged Beech Forest(Case Study: Educational and research forest of Kheirud)
  Vahid Alijani Manouchehr Namiranian Jahangir Feghhi Omid Bozorg-Haddad Vahid Etemad
  10.22034/jest.2020.11182
  Background and Objective: Height Measurement of all trees in a forest or forest stand is almost impractical. For this reason, today different researchers prefer to estimate the tree height by the relationship between the DBH and height of trees. Method: In this study, More

  Background and Objective: Height Measurement of all trees in a forest or forest stand is almost impractical. For this reason, today different researchers prefer to estimate the tree height by the relationship between the DBH and height of trees. Method: In this study, to fitting different statistical models in different stages of forest development, after field inspection, three one hectare sample plots located in different development stages in Beech forest of Kheirud forest, Natural Resources Faculty in Tehran University were selected. Then the DBH of 251 trees have been measured randomly and 80 percent of trees were used for modeling and 20 percent were used to validate 22 regression models. In order to determine the best model for each of development stages, R2, E, MBE and NMPE criteria were used. Findings: The results of this study indicated the suitability of Rational Function and Weibull models in initial stage, Modified Exponential in optimal stage and Gompertz and Richard models in Decay stages. Discussion and Conclusion: Based on the results of this study it can be concluded that different regression models doesn’t have the same ability in fitting the data of DBH and height of different forest stands and the same model can’t be used to fit the data of DBH and height of different forest stands. Manuscript profile
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  3 - Development and Improvement of Neural network algorithm and forest cover index (FCD) classification methods in GEOEYE high resolution satellite data. (Case study: Ramsar-Safarood Hyrcanian forests)
  Amin Mahdavi Saeidi Sasan Babaie Kafaki Asadollah Mattaji
  10.30495/jest.2022.62275.5457
  Background and Objective: Due to the high spatial resolution of Geoeye data, due to the wider distribution of pixels, the output maps in Neural network algorithm and Forest cover index (FCD) classification methods are more sensitive and with more pixel detail. Consideri More

  Background and Objective: Due to the high spatial resolution of Geoeye data, due to the wider distribution of pixels, the output maps in Neural network algorithm and Forest cover index (FCD) classification methods are more sensitive and with more pixel detail. Considering the large amount of information in new sensors, the aim of this study is to develop and improve the performance of more complex classification algorithms for the interpretation of modern satellite data. Material and Methodology: FCD model base classification is based on four main indicators: sensitive to shadow, uncovered soil, vegetation conditions and density, and without the need for a training sample. The Neural network algorithm operates with high sensitivity to the original image bands and the bands created and added to the image, as well as training samples. Training samples were determined in the summer of 2016-2017 from series 5 and 6 of 30 Ramsar watersheds. Finding: Using this method, an accuracy of 24.5% was obtained for the FCD method and 26.2% for the Neural network method. Due to the high resolution of the data used, the output map developed in this method is associated with a high density of polygons. Discussion & Conclusion:  Due to the range of pixels in the output maps of the two methods, an extended method has been proposed to produce a more accurate map, due to the high spatial resolution of the Geoeye sensor. In this method, by reclassifying within the maximum frequency range of pixels, the demarcation of polygons in much smaller and more accurate dimensions is considerable. Manuscript profile
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  4 - Effects of heat treatments on mortality of different life stages of the cowpea weevil., Callosobruchus maculatus Pic. (Col., Bruchidae)
  R. Habibi-Karahrodi r. vafaie H. Farazmand A. Marouf S. Loni
  Cowpea weevil, Callosobruchus maculatus Pic., is one of the important pests of food industry in the world wide. The use of high temperatures or heat treatments is a very effective method for managing of the pests of stored products. In this study, the mortality of the p More

  Cowpea weevil, Callosobruchus maculatus Pic., is one of the important pests of food industry in the world wide. The use of high temperatures or heat treatments is a very effective method for managing of the pests of stored products. In this study, the mortality of the pest in 5 constant temperatures, including 45, 50, 55 and 60°C each at durations of 5, 10, 15, 20 and 30 minutes on different growth stages (egg, 1-days larvae, 11-days larvae, pupae and adult C. maculates) was determined. The treated insects, were kept at 30±1°C and relative humidity of 65±5%. the results showed that, The most sensitive and resistant stages were eggs and pupal stages, respectively. It also revealed that the minimum temperature to control eggs, 1-day old larvae, 11-day old larvae, pupal and adult stages were, 50, 50, 55, 55 and 55°C respectively. Since all stage of the insect are usually present in stored products, it is recommend to use 55°C heating at the duration of 15 minutes to control stored products infested with C. maculates. Manuscript profile
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  5 - Effect of Copper Oxychloride and Volck® Mineral Oil on Blooming Time, Frost Resistance and Yield in Almond cv. “Mamaei”
  R. Babadaei Samani M. Honarvar A.R. Javid
  10.22034/jon.2016.522954
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