En
  • دکتری (1392)

    مهندسی سنجش ازدور

    نیوساوث ولز، سیدنی، استرالیا

  • کارشناسی‌ارشد (1385)

    سنجش ازدور و سیستم اطلاعات جغرافیایی

    تربیت مدرس، تهران، ایران

  • کارشناسی (1382)

    مرتع و آبخیزداری

    علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران

    داده ای یافت نشد

    داده ای یافت نشد

    ارتباط

    رزومه

    MODIS and Sentinel-2 Data Fusion For 10-m Daily Evapotranspiration mapping

    Hamid Salehi, Ali Shamsoddini
    Journal PapersIranian Journal of Irrigation & Drainage , Volume 14 , Issue 6, 2021 January 20, {Pages 1881-1892 }

    Abstract

    Downscaling methods seem to be a reasonable solution to solve the problem of having no simultaneous high spatial and temporal satellite data, and it is possible somehow to meet the requirement of having high spatial-temporal resolution satellite data for monitoring the natural phenomena such as evapotranspiration, through these methods. Sentinel-2 satellite launched in 2015 enables to provide 10-m spatial resolution data with a 5-day revisit time; however, its sensor does not acquire data in thermal infrared wavelength. This study aims to generate 10-m daily evapotranspiration maps based on Sentinel-2 and MODIS data fusion for Amir-Kabir Agroindustry farms. For this purpose, STARFM and improved TSHARP methods were applied for downscaling MO

    Validation of the CHIRPS and CPC-Unified products for estimating extreme daily precipitation over southwestern Iran

    HA Ghaedamini, S Morid, MJ Nazemosadat, A Shamsoddini, ...
    Journal Papers , , {Pages }

    Abstract

    A wavelet-ANN-based framework for estimating air pollutant concentrations using remotely sensed data in Tehran metropolitan area

    A Shamsoddini, MR Aboodi
    Journal Papers , , {Pages }

    Abstract

    Use of Ensemble Methods for Improving Accuracy of Remotely Sensed-derived Actual Evapotranspiration of Global Databases Case Study:(Karkheh Dam Watershed)

    J Yarahmadi, A Shamsoddini, SM Mirlatifi, M Delavar
    Journal Papers , , {Pages }

    Abstract

    Urban Tree Canopy Mapping Using Object Oriented Classification and Machine Learning Algorithms

    N Haghshenas, A Shamsoddini, H Aghighi
    Journal Papers , , {Pages }

    Abstract

    Spatio–Temporal Estimation of Carbon Monoxide and Nitrogen Dioxide based on Remote Sensing Data and Ancillary Data in Tehran

    Ali Shamsoddini, Wanko Ahmadi
    Journal PapersGeography and Sustainability of Environment , Volume 10 , Issue 3, 2020 December 19, {Pages 107-124 }

    Abstract

    Air pollution is one of the most important consequences of human activities, which not only threatens human health but also negatively affects all elements of the environment, including plants and animals. Tehran, the capital of Iran, and the administrative, political and economic center of the country, is no exception which is constantly struggling with these hazard. So far, many linear and nonlinear models have been applied to model air pollution. In this research, 8 pollutant measurement stations distributed over Tehran were selected according to the availability of their recorded data. In order to provide a model predicting pollutants, spatially and temporally, the combination of spatial and temporal features extracted of remote sensing

    Spatio-temporal resolution improvement of actual evapotranspiration using MODIS and Landsat-8 data fusion

    Hamid Salehi, Ali Shamsoddini, Seyed Majid Mirlatifi
    Journal PapersIran-Water Resources Research , Volume 16 , Issue 1, 2020 May 21, {Pages 408-419 }

    Abstract

    Recently, downscaling algorithms have been developed to obtain ET images with high temporal-spatial resolution. The purpose of the present study is to produce daily ET maps with spatial resolution of 30 m for farmlands of Amirkabir Agriculture & Industry. To reach this goal, two different scenarios were used. In the first scenario, SEBAL algorithm input parameters (surface albedo coefficient, normalized difference vegetation index [NDVI], leaf area index [LAI] and land surface temperature [LST]) calculated from MODIS data were downscaled to spatial resolution of Landsat-8, and then actual ET was calculated. In the second scenario, ET data estimated by MODIS data and SEBAL algorithm was downscaled to Landsat-8 spatial resolution. In the firs

    Comparative analysis of LAI retrieval from hyperspectral imagery using machine learning approaches

    Behzad Mohammadi Sheikh Razi, Mohammad Sharif Molla, Ali Jafar Mousivand, Ali Shamsoddini
    Journal PapersIranian Journal of Remote Sensing & GIS , Volume 12 , Issue 3, 2020 October 22, {Pages 47-64 }

    Abstract

    < p >Vegetation biophysical and biochemical variables are key inputs to a wide range of modelling approaches for carbon, water, energy cycle, climate and agricultural applications. Leaf Area Index (LAI) is among the most important canopy variables, used by many different physiological and functional plant models. Several approaches have been developed for vegetation properties retrieval from remotely sensed hyperspectral data. Among them, nonparametric machine learning methods have increasingly gained attention?in vegetation variable retrieval due to their flexibility and efficiency while working with data of high dimensionality over the last decades. Although these methods provide reasonable accuracy at relatively high speed, they are main

    SPOT-5 Spectral and Textural Data Fusion for Forest Mean Age and Height Estimation

    S Miranzadeh, A Shamsoddini, A Mousivand
    Journal PapersJournal of Geomatics Science and Technology , Volume 9 , Issue 1, 2019 September 10, {Pages 119-130 }

    Abstract

    Precise estimation of the forest structural parameters supports decision makers for sustainable management of the forests. Moreover, timber volume estimation and consequently the economic value of a forest can be derived based on the structural parameter quantization. Mean age and height of the trees are two important parameters for estimating the productivity of the plantations. This research aims to estimate mean height and age of a Pinus radiata plantation using SPOT-5 textural and spectral data derived from multi-spectral and panchromatic images, respectively. The study site for this research consisted of a 5000 ha Pinus radiata plantation from 35◦ 23/35//S to 35◦ 29/58//latitude, and 147◦ 58/48//E to 148◦ 04/02//E longitude, ne

    A Field Study of the Function of Climatic Parameters in Tourism and the Validation of Bioclimatic Indices(Case Study: Gandoman Lagoon)

    A Shamsoddini, S Miranzadeh, AJ Mousivand
    Journal Papers , 2019 January , {Pages }

    Abstract

    Sustainable management of the forests requires satellite data at a large scale. This research aims to exploit pixel-based image fusion methods including principal component analysis (PCA) transformation, wavelet transformation, PCA/Wavelet transformation to improve the estimation accuracy of the mean height and age of a Pinus radiata plantation using SPOT-5 panchromatic and multi-spectral images at segment level. Therefore, the average height and age of the trees is measured within 61 plots in a Pinus radiata plantation in NSW, Australia. After applying preprocessing on the images, the spectral information including reflectance and vegetation indices along with textural information derived from gray level co-occurrence matrix for four windo

    Fusion of socio-economic and remote sensing-based attributes for Karaj physical growth modeling

    Shahrbanou Esmaeili, Ali Shamsoddini
    Journal PapersThe Journal of Spatial Planning , Volume 23 , Issue 1, 2019 June 10, {Pages 119-150 }

    Abstract

    Urban physical growth is affected by different parameters including environmental, neighborhood and socio-economic factors; however, socio-economic variables are often ignored due to the lack of socio-economic information, especially in developing countries, when the urban physical growth analysis and modeling is the aim. Accordingly, there is not many studies conducted to develop GIS-based socio-economic layers to be used along with common data, such as slope, distance to the roads and so on, in urban physical growth modeling. Therefore, this study aims to introduce an efficient method to generate GIS-based socio-economic layers to be exploited along with the information layers extracted from Landsat images and field-collected data for phy

    Estimating the Average Age and Height of the Trees using SPOT-5 Panchromatic and Multi-spectral Image Fusion

    ALI SHAMSODDINI, Saeed Miranzadeh, Alijafar Mousivand
    Journal Papers , Volume 8 , Issue 2900744, 2019 January 1, {Pages 45-59 }

    Abstract

    Sustainable management of the forests requires satellite data at a large scale. This research aims to exploit pixel-based image fusion methods including principal component analysis (PCA) transformation, wavelet transformation, PCA/Wavelet transformation to improve the estimation accuracy of the mean height and age of a Pinus radiata plantation using SPOT-5 panchromatic and multi-spectral images at segment level. Therefore, the average height and age of the trees is measured within 61 plots in a Pinus radiata plantation in NSW, Australia. After applying pre-processing on the images, the spectral information including reflectance and vegetation indices along with textural information derived from gray level co-occurrence matrix for four wind

    Land surface temperature mapping based on emissivity fusion in urban areas

    Ali Shamsoddini, Fatemeh Madadi
    Journal PapersJournal of Geomatics Science and Technology , Volume 9 , Issue 2, 2019 December 10, {Pages 77-91 }

    Abstract

    Land surface temperature (LST) is one of the most important variables required in environmental and climatological studies. In order to calculate LST, accurate emissivity is needed. Recently, several methods have been developed to calculate LAST and emissivity. Some of these methods estimate LST based on a pre-known emissivity, while the others calculate LST and emissivity, simultaneously. LST mapping in urban areas can be difficult due to the high variation of the land cover and the formation of mixed pixels. Accordingly, the LST calculation based on the emissivity derived from a single method can be erroneous, especially using a low spatial resolution image in the urban areas. Integration of the emissivity values derived from different me

    Prediction of future land use changes in Tehran Metropolitan Region (TMR) with the combination of logistic regression, Markov chain, and cellular automata

    Hossein Panahi, Ali Shamsoddini
    Journal PapersRegional Planning , Volume 9 , Issue 35, 2019 September 23, {Pages 39-56 }

    Abstract

    The metropolitan regions, especially in developing countries, have experienced rapid population growth due to the absorption of economic immigrants, which have had destructive effects on change in land use environment in the past decades. The current planning process of land use makes it necessary to identify the future pattern of land use on the basis of appropriate criteria with the natural, economic and social environment. Changes in land use occur in a dynamic and complex process due to the mutual effect of natural, social and economic factors and the impact of each factor in different time and scales. Simulation as an efficient way to understand these changes and assess the potential impact of land use changes on the ecology system and

    تخمین میانگین سن و ارتفاع درختان با استفاده از ترکیب تصاویر چندطیفی و پانکروماتیک اسپات-5‎

    شمس الدینی, علی, میرانزاده, سعید, موسیوند, علی جعفر‎
    Journal Papers , , {Pages }

    Abstract

    Prediction of future land use changes in Tehran Metropolitan Region (TMR) with the combination of logistic regression, Markov chain, and cellular automata

    H DADASHPOOR, H PANAHI, ALI SHAMSODDINI
    Journal Papers , , {Pages }

    Abstract

    Mapping red edge-based vegetation health indicators using landsat tm data for australian native vegetation cover

    Ali Shamsoddini, Simitkumar Raval
    Journal PapersEarth Science Informatics , Volume 11 , Issue 4, 2018 December 1, {Pages 545-552 }

    Abstract

    The usefulness of red edge bands, and vegetation indices based on red edge bands, for vegetation health monitoring has already been demonstrated. There are some satellites such as WorldView-2 and Sentinel-2 acquiring images in red edge band data; while, the former data can be expensive and often lack consistent global coverage, the latter does not have a long term archive and consequently cannot be used for a long term time series analysis. This study tests the ability to predict red edge band and red edge-based vegetation indices through freely available Landsat Thematic Mapper data for an Australian Eucalyptus-dominated vegetation cover within and around a mine site. Two modelling strategies including multiple-linear regres

    Medium Spatial Resolution Image Classification Based on Spatial and Thermal Indices

    A Shamsoddini, Sh Esmaeili
    Journal PapersIranian Journal of Remote Sensing & GIS , Volume 9 , Issue 2, 2018 February 20, {Pages 117-132 }

    Abstract

    Differentiating agricultural areas which are not covered by vegetation from bare lands as well as identifying bare lands from urban areas in medium spatial resolution images, e.g. Landsat imagery, are usually difficult and erroneous tasks which lead to the inaccurate classification results. Therefore, this study aims to present a new approach to increase the accuracy of the classification. For this purpose, different scenarios were applied based on different input attributes. The input attributes comprised of spectral bands, textural attributes, i.e. grey level co-occurrence matrix (GLCM), and two types of indices including spatial and thermal attributes proposed in this study. Three classification methods, maximum likelihood (ML), artifici

    MODIS image downscaling using STARFM and SADFAT algorithms for daily Landsat-like spatial resolution evapotranspiration mapping

    Hamid Salehi, Ali Shamsoddini, Seyed Majid Mirlatifi
    Journal PapersIranian Journal of Remote Sensing & GIS , Volume 10 , Issue 3, 2018 March 21, {Pages 123-140 }

    Abstract

    Satellites acquire data in low, medium, and high spatial resolutions. Freely-available high temporal resolution images are often acquired in medium (or low) spatial resolution and high spatial resolution images usually suffer from a low temporal resolution or from high costs. Moreover, high spatial resolution images are prevented to use in modeling of processes such as evapotranspiration due to the lack of thermal bands. Evapotranspiration mapping with a high spatial and temporal resolutions have been always one of the main subjects in the field of remote sensing. Daily evapotranspiration mapping with a 30 meter spatial resolution is the aim of current study. The case study of the research is Amir-Kabir agro-industrial farms. For this purpo

    TEHRAN AIR POLLUTANTS PREDICTION BASED ON RANDOM FOREST FEATURE SELECTION METHOD.

    A Shamsoddini, MR Aboodi, J Karami
    Journal PapersInternational Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences , Volume 42 , 2017 September 26, {Pages }

    Abstract

    Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2. 5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected

    دروس نیمسال جاری

    • كارشناسي ارشد
      سنجش از دور حرارتي: نظريه ها و الگوريتمها ( واحد)
      دانشکده علوم انسانی، گروه سنجش از دور
    • كارشناسي ارشد
      سيستم هاي سنجش از دور ليدار ( واحد)
    • كارشناسي ارشد
      پردازش پيشرفته تصاوير ماهواره اي ( واحد)
    • كارشناسي ارشد
      پردازش پيشرفته تصاوير ماهواره اي ( واحد)

    دروس نیمسال قبل

    • كارشناسي ارشد
      سنجش از دور شهري ( واحد)
      دانشکده علوم انسانی، گروه سنجش از دور
    • كارشناسي ارشد
      مدلهاي رقومي زمين ( واحد)
    • كارشناسي ارشد
      مدلهاي رقومي زمين ( واحد)
    • كارشناسي ارشد
      پردازش پيشرفته تصاوير ماهواره اي ( واحد)
    • كارشناسي ارشد
      پردازش پيشرفته تصاوير ماهواره اي ( واحد)
    • كارشناسي ارشد
      نظام اطلاعات جغرافيايي (GIS) پيشرفته ( واحد)
    • كارشناسي ارشد
      نظام اطلاعات جغرافيايي (GIS) پيشرفته ( واحد)
    • 1397
      ابراهيمي, پگاه
      بهينه سازي الگوريتم حذف پيت هاي داده هاي ليدار مبتني بر روش هاي يادگيري ماشين
    • 1397
      نحوي, سارا
    • 1398
      اريانژاد, سحر
    • 1398
      اسدي, بهار
    • دوره پسادکتری در زمینه کاربردهای سنجش ازدور و سیستم اطلاعات جغرافیایی، دانشکده مهندسی معدن، دانشگاه نیوساوث ولز، سیدنی استرالیا (1392 تا 1393)
    • مدیر گروه سنجش ازدور و سیستم اطلاعات جغرافیایی (1399 تا اکنون)
    • برنده جایزه بهترین مقاله پژوهشی سال 2013 مجله Spatial Sciences
    • برنده جایزه پژوهش برتر تحصیلات تکمیلی دانشکده مهندسی دانشگاه نیوساوث ولز سال 2011
    • برنده جایزه مسابقه جهانی چالش 8-باند شرکت دیجیتال گلوب آمریکا در سال 2011
    • برنده جایزه مقاله برتر بخش سنجش از دور کنفرانس ژئوماتیک 86 سال 1386، تهران، ایران
    • پژوهشگر فعال در بین دانشجویان بورسیه وزارت علوم، تحقیقات و فن اوری شاغل به تحصیل در کشور استرالیا سال 1391
    • دانشجوی استعدادهای درخشان وزارت علوم، تحقیقات و فن اوری سال 1382
    • رتبه اول کنکور سراسری کارشناسی ارشد رشته سنجش از دور و سیستم اطلاعات جغرافیایی در سال 1382
    • شاگرد اول مقطع کارشناسی ارشد سنجش از دور و سیستم اطلاعات جغرافیایی دانشگاه تربیت مدرس در بین ورودی های سال 1382
    • شاگرد دوم مقطع کارشناسی مهندس منابع طبیعی گرایش مرتع و ابخیزداری دانشگاه گرگان در بین ورودی های سال 1378

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