En
  • دکتری (1388)

    جنگلداری- جنگلداری و علوم جنگل

    دانشگاه تربیت مدرس، تهران، ايران

  • کارشناسی‌ارشد (1383)

    مهندسی منابع طبیعی ، جنگلداری

    دانشگاه تربیت مدرس، تهران، ايران

  • کارشناسی (1381)

    مهندسی منابع طبیعی ، جنگلداری

    دانشگاه کردستان، سنندج، ايران

  • ارزیابی و پایش ماهواره ای توده های جنگلی
  • نمونه برداري و اندازه‌گيري درختان و توده هاي جنگلي
  • بکارگیری تصاویر پهباد در آماربرداری جنگل
  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: سید ابراهیم حسینی نسب

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: علی قنبری

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: محسن وفامهر

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: محمود مهرمحمدی

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: محمدحسین پاپلی یزدی

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: مرحوم فرهنگ خادمی ندوشن

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: مرحوم صادق آئینه وند

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: مرحوم نبی اله ابراهیمی

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: مرحوم منصور اعتصامی

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: مرحوم رضا امیدبیگی

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: مرحوم سیداکبر میرحسنی

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: مرحوم محمد حکاک

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: مرحوم محسن ظهیرمیردامادی

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: غلامرضا بابائی روچی

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: محمد رضا بنازاده ماهانی

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

  • آزمایشگاه اکوانفورماتیک

    زمینه های پژوهشی: سنجش از دور جنگل

    کارشناس مسئول: منوچهر نائیجی

    هیات علمی همکار: عزیزاله علیزاده

    تلفن: +981155448103

    مکان: ساختمان هیات علمی

دکتر هرمز سهرابی، تخصص علوم جنگل را از دانشگاه کردستان آغاز نمود و در سال 1388 رساله خود را در زمینه استفاده از تصاویر هوایی برای آماربرداری جنگل دفاع نمود. وی در همان سال در دانشگاه شهرکرد آغاز به کار نمود و در سال 1390 به دانشگاه تربیت رفته و فعالیت‌های علمی پژوهشی خود را از آن زمان تا کنون در این دانشگاه پیگیری می نماید.

ارتباط

رزومه

Detection of mistletoe infected trees using UAV high spatial resolution images

M Miraki, H Sohrabi, P Fatehi, M Kneubuehler
Journal Papers , , {Pages }

Abstract

Mapping vegetation in riparian areas using pixel-based and object-based classification of Sentinel-2 multi-temporal imagery

A Daryaei, H Sohrabi, C Atzberger, M Immitzer
Journal Papers , , {Pages }

Abstract

Using Bayesian kriging and satellite images to estimate above-ground biomass of Zagros mountainous forests

S Izadi, H Sohrabi
Journal Papers , , {Pages }

Abstract

Mechanical Characteristics of the Fine Roots of Two Broadleaved Tree Species from the Temperate Caspian Hyrcanian Ecoregion

Azade Deljouei, Ehsan Abdi, Massimiliano Schwarz, Baris Majnounian, Hormoz Sohrabi, R Kasten Dumroese
Journal PapersForests , Volume 11 , Issue 3, 2020 March , {Pages 345 }

Abstract

In view of the important role played by roots against shallow landslides, root tensile force was evaluated for two widespread temperate tree species within the Caspian Hyrcanian Ecoregion, ie, Fagus orientalis L. and Carpinus betulus L. Fine roots (0.02 to 7.99 mm) were collected from five trees of each species at three different elevations (400, 950, and 1350 m asl), across three diameter at breast height (DBH) classes (small= 7.5–32.5 cm, medium= 32.6–57.5 cm, and large= 57.6–82.5 cm), and at two slope positions relative to the tree stem (up-and down-slope). In the laboratory, maximum tensile force (N) required to break the root was determined for 2016 roots (56 roots per each of two species x three sites x three DBH classes x two s

Comparison of Geographically Weighted Regression and Regression Kriging to Estimate the Spatial Distribution of Aboveground Biomass of Zagros Forests

S Izadi, H Sohrabi, M Jafari Khaledi
Journal PapersJournal of Geomatics Science and Technology , Volume 9 , Issue 3, 2020 February 10, {Pages 113-124 }

Abstract

Aboveground biomass (AGB) of forests is an essential component of the global carbon cycle. Mapping above-ground biomass is important for estimating CO2 emissions, and planning and monitoring of forests and ecosystem productivity. Remote sensing provides wide observations to monitor forest coverage, the Landsat 8 mission provides valuable opportunities for quantifying the distribution of above-ground biomass at moderate spatial resolution across the globe. The combination of the sample plots and image data has been widely used to map forest above-ground biomass at local, regional, national, and global scales. Many predictive methods have been suggested to estimate forest aboveground biomass from sparse sampling points into continuous surface

Modeling spatial patterns and species associations in a Hyrcanian forest using a multivariate log-Gaussian Cox process

Abdollah Jalilian, Amir Safari, Hormoz Sohrabi
Journal PapersJournal of Statistical Modelling: Theory and Applications , 2020 March 3, {Pages 18-Jan }

Abstract

This paper aims to conduct a model-based analysis of the spatial patterns of three tree species in a Hyrcanian forest and investigate their associations. There are many known and unknown mechanisms that influence the spatial forest structure and species associations. These complex and mainly unobservable mechanisms can be modeled by hidden Gaussian random fields and log-Gaussian Cox process models are appropriate for linking them to the spatial patterns of tree species. We consider a multivariate log-Gaussian Cox process model that can take into account the overall mixed effects of all influential factors on spatial distributions of species and quantify species associations in terms of some parameters. This construction provides a suitable

Estimation of coppice forest characteristics using spatial and non-spatial models and Landsat data

Somayeh Izadi, Hormoz Sohrabi, Majid Jafari Khaledi
Journal Papers , 2020 February 28, {Pages 14-Jan }

Abstract

Accurate spatial modelling of forest characteristics is one of the most important challenges in remote sensing applications. In this study, we compared the ability of Multiple Linear Regression (MLR), Geographically weighted regression (GWR), and Random Forest (RF) to estimate different forest attributes based on field sample data and Landsat 8 image. CA was modelled with the highest accuracy compared to other variables using GWR. GWR outperformed other methods. The highest and the lowest values of RMSE were for BA using RF (31.0%) and CA using GWR (12.0%), respectively.

Integration of synthetic aperture radar and multispectral data for aboveground biomass retrieval in Zagros oak forests, Iran: an attempt on Sentinel imagery

Amir Safari, Hormoz Sohrabi
Journal PapersInternational Journal of Remote Sensing , Volume 41 , Issue 20, 2020 October 17, {Pages 8069-8095 }

Abstract

The use of freely accessible Sentinel-1 synthetic aperture radar (S-1 SAR) and Sentinel-2 multispectral instrument (S-2 MSI) data are currently a feasible way of mapping forest aboveground biomass (AGB) over large areas. Despite the extensive mapping of forest AGB by remote sensing, how to effectively combine different sensors data, selecting the proper statistical modelling method, and variable screening are still poorly understood. This paper presents a framework for Sentinel-based AGB estimation through the use of four variable screening techniques, namely, genetic algorithm (GA), least absolute shrinkage and selection operator (LASSO), boruta, and removal-based; and three statistical modelling methods including multiple lin

Fine-scale detection of vegetation in semi-arid mountainous areas with focus on riparian landscapes using Sentinel-2 and UAV data

Ardalan Daryaei, Hormoz Sohrabi, Clement Atzberger, Markus Immitzer
Journal PapersComputers and Electronics in Agriculture , Volume 177 , 2020 October 1, {Pages 105686 }

Abstract

Sparse vegetation such as riparian forests and trees outside forests (TOF) cover only small areas but present various ecological advantages. The detection of these vegetation types in semi-arid mountainous areas is challenging as trees are heavily mixed with other land cover types. Their mapping requires therefore high-resolution imagery. We propose to leverage the advantages and synergies of freely available Sentinel-2 data and a light-weight consumer-grade unmanned aerial vehicle (UAV) with a simple red–greenblue (RGB) camera to detect these vegetation types. In our approach, an object-based random forest land cover classification is first developed over smaller sites using very high-resolution UAV data. The resulting maps are afterward

Comparison of Machine Learning Algorithms for Broad Leaf Species Classification Using UAV-RGB Images

M Miraki, H Sohrabi, P Fatehi, M Kneubuehler
Journal PapersJournal of Geomatics Science and Technology , Volume 10 , Issue 2, 2020 December 10, {Pages 10-Jan }

Abstract

Knowing the tree species combination of forests provides valuable information for studying the forest’s economic value, fire risk assessment, biodiversity monitoring, and wildlife habitat improvement. Fieldwork is often time-consuming and labor-required, free satellite data are available in coarse resolution and the use of manned aircraft is relatively costly. Recently, unmanned aerial vehicles (UAV) have been attended to be an easy-to-use, cost-effective tool for the classification of trees. In fact, given the cost-efficient nature of UAV derived SfM, coupled with its ease of application, it became a popular choice. The type of imagery is an important factor in classification analysis because the spatial and spectral resolution can influ

Estimating the Spatial Distribution of Above-ground Carbon of Zagros Forests using Regression Kriging, Geographically Weighted Regression Kriging and Landsat 8 imagery

Somayeh Izadi, Hormoz Sohrabi
Journal PapersJournal of Environmental Science and Technology , 2020 February 25, {Pages }

Abstract

AbstractBackground and objectives: Estimating aboveground carbon (AGC) of forest is a fundamental task for sustainable management of forest ecosystems; therefore, there is a critical need for appropriate approaches for quantifying of AGC. The most commonly used approaches for estimating include global regression models that estimate the target variable over a wide range using cost-effective auxiliary data. Traditional regression models with fixed regression coefficients at all locations do not consider heterogeneity and spatial structure in modeling. The objective of this study is estimate the AGC using Regression Kriging, Geographically Weighted Regression Kriging and Landsat 8 data and compare methods.Method: The study was carried out in

Using the bootstrap approach for comparing statistical modeling methods to estimate remotely-sensed aboveground biomass in Zagros forests

Amir Safari, Hormoz Sohrabi
Journal Papers , Volume 11 , Issue 239, 2020 January 1, {Pages 49-67 }

Abstract

Abstract Background and Objective Considering the increasing importance of forest ecosystems in climate change mitigation projects, reliable and cost-effective methods are required to estimate the aboveground biomass (AGB). Common methods used to estimate the aboveground biomass (AGB) include in-situ measurement, the biomass calculation using aalometric equations and using remote sensing techniques. Remote sensing has been widely used to estimate the biomass of forests in recent decades. The used statistical modeling method is one of the most important factors to use remotely-sensed data for estimation of the aboveground biomass. A large number of researches have been carried out about using the modeling methods. However, these studies face

Investigating the effect of leaf-on and leaf-off canopy on PALSAR-2 data with the aim of estimating above-ground biomass in Hyrcanian Forests

Parisa Golshani, Yasser Maghsoudi, Hormoz Sohrabi
Journal PapersScientific-Research Quarterly of Geographical Data (SEPEHR) , Volume 29 , Issue 114, 2020 August 22, {Pages 51-65 }

Abstract

Extended Abstract Introduction Estimation of forest Carbon stocks plays an important role in assessing the quantity of carbon exchange between the forest ecosystem and the atmosphere. Direct methods of measuring carbon stock are not economically efficient. Optical remote sensing methodsalso have limited capability in predicting forest biomass, because the spectral response of optical images is related to the interaction between solar radiation and canopy, especially in mature forests. These obstacles limit the efficiency of optical sensors for forest biomass estimation. Recently, airborne data has received a great deal of scientific and operational attention for estimation of forest features. LiDAR data also faces challengessuch as limited

Biomass Expansion Factors (BEFs) and Carbon Stock for Brant's Oak (Quercus brantii Lindl.) Forests in West-Iran

Yaghub Iranmanesh, Hormoz Sohrabi, Khosro Sagheb-Talebi, Seyed Mohsen Hosseini, Abouzar Heidari Safari Kouchi
Journal PapersAnnals of Silvicultural Research , Volume 43 , Issue 1, 2019 June 28, {Pages 15-22 }

Abstract

Investigating a tree’s biomass can provide basic information about forest carbon stock. The Biomass Expansion Factor (BEF) is a variable for estimating carbon stock of forests. The aim of this study was to analyse the Above Ground Biomass (AGB) allocation, developing the BEF and carbon stock for two vegetation forms of Brant’s Oak (Quercus brantii Lindl.) based on forest inventory data. BEF is defined as the ratio of AGB to crown volume variables. The study data were taken from 30 trees that include 16 individual trees with single stem and 14 coppice shoots located in West-Iran. The trees selected were felled and separated into different components including: bole, main branches, lateral branches, twigs and leaves. The fresh weight of t

Modelling the biomass of Lebanon oak sprouts and it's response to thinning in northern Zagros forests (the case of Baneh, Kurdistan Province).

S Ebrahimi, A Valipour, H Sohrabi, L Ghahramany
Journal PapersIranian Journal of Forest , Volume 10 , Issue 4, 2019 January , {Pages }

Abstract

This study was carried out to understand the dynamics of Lebanon oak coppice coppice Subject Category: Miscellaneous

Estimation of Available Canopy Fuel of Coppice Oak Stands Using Low-Density Airborne Laser Scanning (LiDAR) Data

Farzad Yavari, Hormoz Sohrabi
Journal Papers , 2019 January , {Pages 171-173 }

Abstract

Predicting fire hazards and simulating fire intensity require knowledge of fuel conditions. Many aspects of wildfire behavior including the rate of spread and intensity are influenced by the amount of vegetation that fuels the fire. Coppice Oak Forests (COF) are strongly influenced by wildfires. In the present study, we examined the ability of airborne LiDAR data to retrieve available canopy fuel (ACF) of coppice Oak forest in Zagros Mountains, Iran. Two different oak-dominated stands were selected based on the stand density including sparse and dense forests. Systematically, 127 plots were established in the field and ACF was calculated using species-specific allometric equations. An outlier filter was used to remove any out

Effect of climate change and local management on aboveground carbon dynamics (1987–2015) in Zagros oak forests using Landsat time-series imagery

Amir Safari, Hormoz Sohrabi
Journal PapersApplied Geography , Volume 110 , 2019 September 1, {Pages 102048 }

Abstract

Forest carbon stocks are a time-integrated manifestation of various phenomena and processes ranging from tree growth and mortality to natural and human disturbances. Understanding the effects of environmental and human activities is critically important in vulnerable ecosystems like arid and semi-arid forests, given climate variability coupled with historical human activities. Zagros forests are one of the largest vegetation communities in the Middle East. This region is highly affected by dust storms which are mainly a result of the loss of vegetation. This current study is an exploration of changes to aboveground carbon (AGC) density as affected by climate change (CC) and local management from 1987 to 2015 at 5-year intervals based on L

The effect of digital preprocessing and modeling method on an estimation of aboveground carbon stock of Zagros forests using Landsat 8 imagery

A SAFARI, H SOHRABI
Journal Papers , Volume 9 , Issue 43300503, 2019 January 1, {Pages 73-89 }

Abstract

The aim of this study, was to evaluate the effectiveness of different preprocessing methods and modeling techniques on the accuracy of aboveground carbon stock estimates in two forest stands with different degradation levels (Gahvareh forest and SarfiruzAbad), in Zagros forests in Kurdistan province. Comparison of different digital pre-processing methods on Landsat 8 images was carried out in different scenarios of radiometric, atmospheric, topographic and their combination. In each scenario, we used four modeling methods included linear regression, generalized additive model, random forest, and support vector machine. In most cases, radiometric correction with improved correction coefficient was 0. 71 (R2adj= 0. 71) and the root means squa

THE EFFECT OF UAV FLIGHT ALTITUDE ON THE ACCURACY OF INDIVIDUAL TREE HEIGHT EXTRACTION IN A BROAD-LEAVED FOREST

S Sadeghi, H Sohrabi
Journal PapersInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences , Volume 42 , Issue 4/W18, 2019 January , {Pages }

Abstract

Advances in Unmanned Aerial Vehicle (UAV) technology made it possible to collect very high resolution images with affordable cost. From the other hand, data processing capabilities have made it feasible to obtain three dimensional (3D) data which can be used for measurement and estimation of different forest structural properties. In this research, we examined the accuracy of tree height measurement derived from photogrammetric processing of UAV images. Using structure from motion (SfM) algorithm, point cloud was generated and canopy height model (CHM) was derived. The study area is 2.50 hectares in which the height of all the trees were measured. Images were taken at five flight heights including 60, 80, 100, 120, and 140 meters above sea

Using canopy height model derived from UAV images for tree height estimation in Sisangan forest

MR Kargar, H Sohrabi
Journal Papers , Volume 10 , Issue 33600834, 2019 January 1, {Pages 106-119 }

Abstract

Recent advances in unmanned aerial vehicles (UAVs) technology, as well as the development of lightweight sensors, offers a great possibility for the measurement of different tree features with relatively low costs compared to traditional methods. In this research, the precision and accuracy of tree height measurement and estimation using imagery by a low-cost UAV were studied. For this aim, 854 images with an altitude of 100 m above the ground were taken and the images were processed and dense point cloud was extracted by applying Structure from Motion (SFM) algorithm. The study was conducted in 34. 79 ha of Sisangan forest park and 28 sample plots (30? 30 m) were located in the field and tree heights were measured. Also, tree height was me

دروس نیمسال جاری

  • دكتري
    سنجش از دور پيشرفته در جنگل ( واحد)
    دانشکده منابع طبیعی و علوم دریایی، گروه جنگلداري
  • دكتري
    سنجش از دور پيشرفته در جنگل ( واحد)
  • كارشناسي ارشد
    زيست سنجي جنگل ( واحد)
  • كارشناسي ارشد
    زيست سنجي جنگل ( واحد)
  • كارشناسي ارشد
    طرح آزمايشات پيشرفته ( واحد)
  • كارشناسي ارشد
    طرح آزمايشات پيشرفته ( واحد)

دروس نیمسال قبل

  • كارشناسي ارشد
    سنجش از دور در جنگل ( واحد)
    دانشکده منابع طبیعی و علوم دریایی، گروه جنگلداري
  • كارشناسي ارشد
    سنجش از دور در جنگل ( واحد)
  • دكتري
    روش هاي پيشرفته نمونه برداري در جنگل ( واحد)
  • دكتري
    روش هاي پيشرفته نمونه برداري در جنگل ( واحد)
  • 1396
    عباسي, مهري
    آشكاري سازي فنولوژي- مبناي تودههاي سرخدار با استفاده از سري زماني تصاوير ماهوارهاي
  • 1395
    دريايي, اردلان
    آشكارسازي توده هاي جنگلي كران رودي و درختان خارج از عرصه هاي جنگلي توسط تصاوير ماهواره اي و پهباد با استفاده از روش پيكسل و شي ءمبنا
  • 1396
    ميركي, مژده
  • معاون آموزشي و پژوهشي دانشكده منابع طبيعي دانشگاه شهركرد
  • مدير دفتر طرح تحول راهبردي دانشكده منابع طبيعي دانشگاه تربيت مدرس
    داده ای یافت نشد

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