شاه حسینی, رضا
دانشگاه تهران
[ 1 ] - ارائه یک روش خودکار کشف تغییرات مبتنی بر کرنل در مناطق شهری با استفاده از تصاویر چندطیفی ماهواره لندست، مطالعه موردی: شهر کرج
در چند دههی گذشته جمعیت شهر نشین و در نتیجه توسعه مکانی مناطق شهری شتابی فزاینده داشتهاست. این مهم به بروز تغییرات محیطی در این مناطق منجر شده است. از این رو، کشف تغییرات در بازههای زمانی مختلف در مناطق شهری از اهمیت بالایی برخوردار است. روشهای کشف تغییرات متداول با استفاده از تصاویر سنجش از دوری، بیشتر مبتنی بر تشخیص تغییرات طیفی و محاسبه فاصله طیفی بین پیکسلها بوده و ماهیت تغییرات بصورت ...
[ 2 ] - پایش و برآورد خسارات ناشی از سیل به کمک آشکارسازی تغییرات شی گراء و تلفیق تصاویر راداری و نوری
کشف تغییرات و خسارات ناشی از وقوع بلایای طبیعی، به علت محدودیت زمانی و اهمیت بالا در مدیریت بحران از جمله عملیات دشوار و حساسی هستند. در اواخر فروردینماه سال 1396، بارش‌های شدید در حوضه کارون بزرگ و سد دز، باعث جاری شدن سیلابی بی‌سابقه در سال‌های اخیر با شدت هشت هزار مترمکعب در ثانیه شد. بروز این سیلاب منجر به وارد آمدن خسارات فرآوانی به این روستاها و دشت‌های کشاورزی شد. بنابراین نیاز به روشه...
[ 3 ] - Change Detection in Urban Area Using Decision Level Fusion of Change Maps Extracted from Optic and SAR Images
The last few decades witnessed high urban growth rates in many countries. Urban growth can be mapped and measured by using remote sensing data and techniques along with several statistical measures. The purpose of this research is to detect the urban change that is used for urban planning. Change detection using remote sensing images can be classified into three methods: algebra-based, transfor...
[ 4 ] - Comparative Evaluation of Image Fusion Methods for Hyperspectral and Panchromatic Data Fusion in Agricultural and Urban Areas
Nowadays remote sensing plays a key role in the field of earth science studies due to some of the advantages, including data collection at a very low cost and time on a very large scale. Meanwhile, using hyperspectral data is of great importance due to the high spectral resolution. Because of some limitations, such as hyperspectral imaging technology, it suffers from a reduction in the spatial ...
[ 5 ] - اندازه گیری شدت جزایرحرارتی سطحی شهری با استفاده از شاخص های پوشش گیاهی و شهری؛ مطالعه ی موردی: شهرهای رشت و لنگرود
در این مقاله روش جدیدی برای اندازه گیری شدت جزیره های گرمایی سطحی شهری پیشنهاد می شود که از رابطه بین دمای سطح زمین (LST) و شاخص تفاضلی یکنواخت شده ی شهری(NDBI) وشاخص تفاضلی یکنواخت شده ی گیاهی(NDVI) که در تصویری به نام...
[ 6 ] - A Hybrid Algorithm based on Deep Learning and Restricted Boltzmann Machine for Car Semantic Segmentation from Unmanned Aerial Vehicles (UAVs)-based Thermal Infrared Images
Nowadays, ground vehicle monitoring (GVM) is one of the areas of application in the intelligent traffic control system using image processing methods. In this context, the use of unmanned aerial vehicles based on thermal infrared (UAV-TIR) images is one of the optimal options for GVM due to the suitable spatial resolution, cost-effective and low volume of images. The methods that have been prop...
[ 7 ] - Crop Land Change Monitoring Based on Deep Learning Algorithm Using Multi-temporal Hyperspectral Images
Change detection is done with the purpose of analyzing two or more images of a region that has been obtained at different times which is Generally one of the most important applications of satellite imagery is urban development, environmental inspection, agricultural monitoring, hazard assessment, and natural disaster. The purpose of using deep learning algorithms, in particular, convolutional ...
[ 8 ] - A multi-scale convolutional neural network for automatic cloud and cloud shadow detection from Gaofen-1 images
The reconstruction of the information contaminated by cloud and cloud shadow is an important step in pre-processing of high-resolution satellite images. The cloud and cloud shadow automatic segmentation could be the first step in the process of reconstructing the information contaminated by cloud and cloud shadow. This stage is a remarkable challenge due to the relatively inefficient performanc...
[ 9 ] - Analysis of changes detection in Gano coal mine area using satellite image from 2000 to 2020 (northwest of Damghan)
In coal mines, fires and explosions due to rising temperatures and high coal densities are the most likely hazards. Due to the looseness of the coal-bearing terrestrial layers, there are also risks of collapsing extraction tunnels. Therefore, in order to manage the risk in coal mines, the risk model in these areas should be studied periodically. The purpose of this study is to comprehensively s...
[ 10 ] - Provide a Deep Convolutional Neural Network Optimized with Morphological Filters to Map Trees in Urban Environments Using Aerial Imagery
Today, we cannot ignore the role of trees in the quality of human life, so that the earth is inconceivable for humans without the presence of trees. In addition to their natural role, urban trees are also very important in terms of visual beauty. Aerial imagery using unmanned platforms with very high spatial resolution is available today. Convolutional neural networks based deep learning method...
[ 11 ] - An efficient method for cloud detection based on the feature-level fusion of Landsat-8 OLI spectral bands in deep convolutional neural network
Cloud segmentation is a critical pre-processing step for any multi-spectral satellite image application. In particular, disaster-related applications e.g., flood monitoring or rapid damage mapping, which are highly time and data-critical, require methods that produce accurate cloud masks in a short time while being able to adapt to large variations in the target domain (induced by atmospheric c...