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Land use change modeling through an integrated Multi-Layer Perceptron Neural Network and Markov Chain analysis(case study: Arasbaran region, Iran)

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Journal of Forestry Research 2019年第3期30卷 943-957页

作者： vahid nasiri Ali.A.Darvishsefat Reza Rafiee Anoushirvan Shirvany Mohammad Avatefi Hemat Department of Forestry Faculty of Natural Resources University of TehranKarajIran Department of Environmental Science Faculty of Natural ResourcesUniversity of TehranKarajIran

Temporal land use/land cover (LULC) change information provides a variety of applications for informed management of land resources. The aim of this study was to detect and predict LULC changes in the Arasbaran region using an integrated Multi-Layer Perceptron Neural Network and Markov Chain analysis. At the first step, multi-temporal Landsat images (1990, 2002 and 2014) were processed using ancillary data and were classified into seven LULC categories of high density forest, low-density forest, agriculture, grassland, barren land, water and urban area. Next, LULC changes were detected for three time profiles, 1990–2002, 2002–2014 and 1990–2014. A 2014 LULC map of the study area was further simulated (for model performance evaluation) applying 1990 and 2002 map layers. In addition, a collection of spatial variables was also used for modeling LULC change processes as driving forces. The actual and simulated 2014 LULC change maps were cross-tabulated and compared to ensure model simulation success and the results indicated an overall accuracy and kappa coefficient of 97.79% and 0.992, respectively. Having the model properly validated, LULC change was predicted up to the year 2025. The results demonstrated that 992 and 1592 ha of high and lowdensity forests were degraded during 1990–2014,respectively, while 422 ha were added to the extent of residential areas with a growth rate of 17.58 ha per year. The developed model predicted a considerable degradation trend for the forest categories through 2025, accounting for 489 and 531 ha of loss for high and low-density forests, respectively. By way of contrast, residential area and farmland categories will increase up to 211 and 427 ha, respectively. The integrated prediction model and customary area data can be used for practical management efforts by simulating vegetation dynamics and future LULC change trajectories.

关键词： Satellite images Land use changes Land change modeler Artificial neural network Prediction

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Natural regeneration of oriental beech(Fagus orientalis Lipsky)trees in canopy gaps and under closed canopy in a forest in northern Iran

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Journal of Forestry Research 2018年第4期29卷 1065-1071页

作者： Nasrin nasiri Mohammad R.Marvie Mohadjer vahid Etemad Kiomars Sefidi Leila Mohammadi Maryam Gharehaghaji Department of Forestry Faculty of Natural ResourcesUniversity of Tehran Faculty of Agriculture and Natural Resources Technology University of Mohaghegh Ardabili Department of Biological Science Ecology and Evolution GroupUniversity of Illinois at Chicago

For developing nature-based silvicultural practices in a beech forest to promote, abundance, height, vitality, and preferred growth form, regenerated trees growing in gaps were compared with those under closed canopies. A systematic 50 ×50 m grid was plotted in a beech stand in the Kheyrud Experimental Forest for selecting trees to measure variables in gaps and under closed canopies. Abundance and mean height of regenerated beech trees were significantly higher in closed canopies than in canopy gaps. Beech seedlings with excurrent growth were significantly taller within regeneration patches under closed canopy. Moreover, regenerated trees with high vitality were more abundant in closed canopy areas than in gaps. Thus, beech regeneration should improve under closed canopies; hence, gaps in a near natural forest should be created only after adequate regeneration and appropriate growth under the parent tree in a closed canopy area is ensured. The results of this research have profound implications for the sustainable management of the forest and for ensuring sustainable beech regeneration. The presence of a closed canopy cover likely will reduce potential stresses on oriental beech regeneration.

关键词： Closed canopy Canopy gap Growth form Vitality Beech

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Comparative Assessment on the Performance of Open-Loop and Closed-Loop IFOGs

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Optics and Photonics Journal 2012年第1期2卷 17-29页

作者： Mohammad Reza nasiri-Avanaki vahid Soleimani Rohollah Mazrae-Khoshki Electronic Engineering Department RAZI University Kermanshah Iran Electronics Department Azad University of Karaj Tehran Iran

In this paper, we evaluated comprehensively the structure and operation of open-loop interferometric optical fiber gyroscopes (IFOG). To complete the previous works, a digital approach to derive the rotation angle in optical fiber gyroscopes is investigated theoretically. Results are simulated by the MATLAB software;therefore we could compare the results in simulated area with the values derived from theory. Also, feedback Erbium-doped fiber amplifier (EFDA) FOGs, called FE-FOG, is categorized in closed-loop IFOGs. The procedure of finding the Sagnac shift for open-loop and closed-loop IFOG have been studied and compared to one another. The signal processing in the open-loop IFOG was simulated using Matlab software and for the closed-loop IFOG by PSCAD. In the open-loop IFOG the analogue formulation of the IFOG in order to extract the phase shift is analyzed. A novel and promising method for derivation of Sagnac phase shift based on digital finite impulse response filtering is proposed. Based on our simulation results, the reliability and accuracy of the method is determined. In the closed-loop IFOG, the shift was derived through frequent use of Sagnac loop. The output signal is injected in the input again as feedback. The shift phase between clockwise and counterclockwise waves in each complete route, including primary and feedback route, is identified as Sagnac shift phase.

关键词： Feedback Erbium-Doped Fiber Amplifier FOG (FE-FOG) Erbium-Doped Fiber Amplifier (EFDA) Digital Signal Processing PSCAD FIR Digital Filters Interferometric Fiber Optic Gyro (IFOG) Sagnac Shift

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