Seyed Kazem Alavipanah

University of Tehran | UT · Department of Remote Sensing and GIS

Rapid changes of land use and land cover (LULC) in urban areas have become a major environmental concern due to environmental impacts, such as the reduction of green spaces and development of urban heat islands (UHI). Monitoring and management plans are required to solve this problem effectively. The Tabriz metropolitan area in Iran, selected as a...

Mining activities and associated actions cause land-use/land-cover (LULC) changes across the world. The objective of this study were to evaluate the historical impacts of mining activities on surface biophysical characteristics, and for the first time, to predict the future changes in pattern of vegetation cover and land surface temperature (LST)....

The expansion of urbanization has increased the scale and intensity of thermal islands in cities. Investigating how cities are affected by these thermal islands plays an important role in the future planning of cities. For this purpose, this study examines and predicts the effect of land cover (LC) changes in the three classes of LC including urban...

Climate change is one of the most pressing problems among scientists worldwide, with experts warning about it and even referring to it as unfathomable human agony. In this study, we reviewed previous studies and examined two gaps in the existing approach to climate change studies. First, look at the "side effects" of global warming that have been o...

In contrast to the well-investigated field of Synthetic Aperture Radar (SAR)-to-Optical translation, this study explores the lesser-investigated domain of Optical-to-SAR translation, which is a challenging field due to the ill-posed nature of this translation. The complexity arises as single optical data can have multiple SAR representations based...

Urban planning and comprehensive understanding of human-environmental interactions within cities require precise and up-to-date information of urban impervious surfaces. In this regards, the emergence of accurate data, particularly short-range photogrammetric data with high spatial and spectral resolutions has proven to be essential. Urban impervio...

Introduction: Land cover maps are essential elements in geographical analysis and spatial planning. The accuracy and effectiveness of these maps rely on three factors: Satellite imagery, classification algorithms and training samples. The quality of the training dataset significantly impacts the accuracy of classification results. This study aims t...

Reliable and up-to-date training reference samples are imperative for land cover (LC) classification. However, such training datasets are not always available in practice. The sample migration method has shown remarkable success in addressing this challenge in recent years. This work investigated the application of Sentinel-1 (S1) and Sentinel-2 (S...

Spatial downscaling satellite sensor-derived land surface temperature (LST) is of great importance for various environmental applications. However, the energy balance at the land surface is complex, especially in urban environments. As a result, the complexity of land surface thermal processes and the resulting LST cannot be accurately modeled usin...

Soil Organic Carbon (SOC) constitutes a fundamental component of terrestrial ecosystem functionality, playing a pivotal role in nutrient cycling, hydrological balance, and erosion mitigation. Precise mapping of SOC distribution is imperative for the quantification of ecosystem services, notably carbon sequestration and soil fertility enhancement. D...

Quantification of Surface Ecological Status (SES) changes is of great importance for understanding human exposure and adaptability to the environment. This study aims to assess the effect of urban growth on spatial and temporal changes of SES over a set of neighboring Iranian cities, Amol, Babol, Qaemshahr, and Sari, which are located in moderate a...

Due to the limited number and sparse distribution of meteorological and hydrometric stations in most watersheds, the runoff estimation based on these stations may not be accurate. However, the accurate determination of the Antecedent Soil Moisture (ASM) in watersheds can improve the accuracy of runoff forecasting. The objective of this study is to...

Digital soil mapping (DSM) is an advanced approach that integrates statistical modeling and cutting-edge technologies, including machine learning (ML) methods, to accurately depict soil properties and their spatial distribution. Soil organic carbon (SOC) is a crucial soil attribute providing valuable insights into soil health, nutrient cycling, gre...

This study mainly aims to estimate the actual evapotranspiration rate and calculate the water requirement of pistachio crops in the central plateau of Iran applying satellite remote sensing products. In order to achieve this main goal, 12 images from the Operational Earth Imager (OLI) of the Landsat 8 satellite for the water year 2018-2019 were dow...

Several earth science investigations depend heavily on knowing the surface energy budget and determining surface temperature. The primary factor affecting the energy balance in the surface physical processes of the planet is the land surface temperature (LST). Even in the case of small-scale green areas like local parks, plants have a significant i...

Quantifying biophysical and biochemical vegetation variables is of great importance in precision agriculture. Here, the ability of artificial neural networks (ANNs) to generate multiple outputs is exploited to simultaneously retrieve Leaf area index (LAI), leaf sheath moisture (LSM), leaf chlorophyll content (LCC), and leaf nitrogen concentration (...

Land surface temperature is a vital indicator for studying environmental changes, hydrological conditions and the energy balance of the earth, which can also be used to monitor the temperature changes of cities. The lack of meteorological stations in most parts of the country, including the study area, has created information limitations in the fie...

The PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite of the Italian Space Agency, lunched in 2019, has provided a new generation source of hyperspectral data showing to have high potential in vegetation variable retrieval. In this study, the newly available PRISMA spectra were exploited to retrieve Leaf Area Index (LAI) of sug...

One of the key parameters that affects the accuracy of Land Surface Temperature (LST) disaggregation is the environmental variables that are fed to the disaggregation model. The aim of this study is to present a new strategy for the disaggregation of LST based on adjacency effects. To do this, a dataset obtained from satellite images and auxiliary...

The purpose of this study is to comprehensively review of Satellite-derived Land Surface Temperature Spatial Sharpening (SLSTSS) studies and provide appropriate solutions to error reduction in SLSTSS presses. Firstly, the initial search was done for the related keywords to SLSTSS, and 391 papers were found over the period 1985 to 2020. Secondly, to...

The normalization of LST relative to environmental parameters is of great importance in various environmental applications. The purpose of this study was to develop a new approach for LST normalization relative to environmental variables. These included topographic variables (i.e. solar irradiance and near-surface temperature lapse rate (NSTLR)) as...

In remote sensing (RS), shadows play an important role, commonly affecting the quality of data recorded by remote sensors. It is, therefore, of the utmost importance to detect and model the shadow effect in RS data as well as the information that is obtained from them, particularly when the data are to be used in further environmental studies. Shad...

COVID-19 pandemic has had a major impact on our society, environment and public health, in both positive and negative ways. The main aim of this study is to monitor the effect of COVID-19 pandemic lockdowns on urban cooling. To do so, satellite images of Landsat 8 for Milan and Rome in Italy, and Wuhan in China were used to look at pre-lockdown and...

Many countries today are facing severe water shortages as a result of extensive urban development and population grow. Meanwhile, the increasing pressure on water resources has turn out to be a threat to sustainable development requiring considerable attention both locally and globally. Several modeling techniques have been developed to understand...

Sand and dust storms (SDS) are common meteorological phenomena in arid and semi-arid regions caused by natural or anthropogenic factors. Central Iran, covers a large area on the Iranian plateau, and SDS has been known as a prevalent phenomenon in certain parts of the region since ancient times. The frequency and severity of SDS have increased over...

Urban land surface temperature (ULST) is a key variable for environmental applications and widely used in a variety of fields. However, retrieving ULST with high spatial and temporal resolution is still a challenging task since its a function of surface characteristics and geographical, climatic, and seasonal conditions. Assessing the type and inte...

Improving the spatial resolution of Land Surface Temperature (LST) obtained from satellite images is of great importance in various applications, especially in urban areas. Aiming to bridge the gap in the research background, this study attempted to quantify the effect of landscape metrics on the accuracy of urban LST downscaling. The research data...

The effect of urban thermal islands due to intersections with major environmental challenges of the 21st century is one of the most important studies on environmental phenomena, and in this regard, the study of the land surface temperature gives a clear perspective of the thermal islands in cities, which, according to the warm and dry climate of Ya...

The purpose of this study is to present a new approach for satellite imagery-derived Land Surface Temperature (LST) disaggregation based on a decision level integration of various disaggregation strategies. Firstly, common disaggregation models including Global Window Strategy (GWS), Regular Local Window Strategy (RLWS), Object-based Window Strateg...

Using the GIS and the Weight-Of-Evidence method, this research prepared a potential map of ancient sites for North-East of Iran. First, some related criteria were selected, and then, using statistical methods, the importance of each causative factor was determined. For example, the slope direction was not statistically significant in the study area...

Moisture is one of the most important factors affecting soil reflectance spectra. However, provisional and dynamic behavior of soil moisture (SM) in salty soils reduce the capability of field spectrometry in the estimation of soil properties. This study aims minimising the effect of SM on the accuracy of visible and near-infrared (VNIR) spectra est...

Content: Omar Khayyam Neyshabouri, the great Iranian mathematician, quatrain philosopher, poet and sage, lived in the fifth-sixth/eleventh-twelfth centuries. Khayyam' poems show a man who is fascinated by the mystery of existence, the quatrains that are the manifestation of nature and humankind. The nature of everything has a sense of soul, in whic...

Mapping the distribution and type of land use and land cover (LULC) is essential for watershed management. The Tigris-Euphrates basin is a transboundary region in the Middle East shared between six countries, but a recent fine-scale LULC map of the area is lacking. Using Landsat-8 time series, a 30-m resolution LULC map was produced for the Tigris-...

Land surface temperature (LST) is one of the essential parameters of environmental science studies. In this study the land surface temperature of Ardabil city using a LST automatic calculator application was estimated with a single channel algorithm. for this purpose, Landsat 5 and 8 satellite images on 2000/07/31 and 2019/08/21 were used. In order...

Soil moisture hampers the estimation of soil variables from remote and proximal sensing data, reducing the strength of the relevant spectral absorption features. In the present study, 95 soil samples which have different texture were rewetted to 7 different moisture levels (air-dry, 6, 12, 18, 24, 30 and 36%) and reflectance measured by spectroradi...

In this research, the data of the LISS-III sensor used for mapping saline soils in the vicinity of Tashk and Bakhtegan Lake, Fars Province. After the corrections of the imagery, the training and control pixels selected and the soil samples (depth of 5 cm) prepared. Then pixels of the imagery classified in different approaches by maximum likelihood...

Employing recent technological advances in surveying and mapping soil salinity is a step forward in controlling saline soils. The aim of this study was to map the topsoil salinity using different methods within the environmental context of the area around Tashk & Bakhtegan Lake (8062 ha) in Iran where soil salinity appears to be a major threat to a...

The data classification of fully polarimetric synthetic aperture radar (PolSAR) is one of the favourite topics in the remote sensing community. To date, a wide variety of algorithms have been utilized for PolSAR data classification, and among them kernel methods are the most attractive algorithms for this purpose. The most famous kernel method, i.e...

گسترش شهر نشینی سبب افزایش مقیاس و شدت جزایر حرارتی در شهرها شده است. بررسی نحوه متاثر شدن شهرها از این جزایر حرارتی نقش به سزایی در برنامه‌ریزی‌های آتی شهرها دارد. بدین منظور، این پژوهش با بررسی و پیش‌بینی اثر تغییرات پوشش اراضی در سه طبقه مناطق شهری، زمین‌های بایر و پوشش گیاهی در شهر یزد طی 30 سال اخیر با استفاده از تصاویر لندست 5 و 8 و همچنین بر...

Estimation of mineral quantity with the presence of dry and green vegetation at pixel level is a challenging task in hyperspectral image analysis. A multiple linear regression model was trained to remove the effect of vegetation at pixel level in Hyperion image. The main diagnostic absorption features of the minerals in the study area are in 900, 2...

Soil moisture (SM), a critical component of the global hydrological cycle, is affected by individual or combinations of multiple factors including soil properties, climate, and topography. Despite its importance to many disciplines, predicting SM continuously, accurately, and inexpensively over a large area is a great challenge due to its dynamic n...

The COVID-19 pandemic has caused unprecedent negative impacts on our society, however, evidences show a reduction of anthropogenic pressures on the environment. Due to the high importance of environmental conditions on human life quality, it is crucial to model the impact of COVID-19 lockdown on environmental conditions. Consequently, the objective...

Accurate modeling of Land Surface Ecological Status (LSES) is crucial in environmental applications. Despite valuable benefits, common indices are unable to distinguish LSES of bare soils from lands affected by Anthropogenic Destructive Activities (ADAs). The objective of this study was to present an index to distinguish LSES of different Land Use/...

Thermal anomaly detection related to strong earthquakes is one of the earthquake precursors extensively investigated by researchers. In this research, five years (March 16th to May 16th, every year from 2009 to 2013) of Land Surface Temperature (LST) data products, obtained from satellite data (MODIS-Aqua), and meteorological data (air and soil tem...

A set of factors cause the Surface Ecological Status (SES) of urban areas to become largely different from the surrounding rural areas. Hence, the degree of poorness of SES in urban areas versus surrounding rural areas forms a zone, which is named Urban Surface Ecological Poorness Zone (USEPZ). The main objective of this study was to propose a new...

The primary formation of soil spatial heterogeneity of young surfaces is not well studied. Along the coast of the Caspian Sea, due to the constant sea-level changes of this closed water basin, young soilscapes have formed in the last centuries. The variability and the spatial pattern of soil salinity were studied at two key sites located at the coa...

In order to support sustainable forest management, it is essential to estimate the extent and change of forest cover and to evaluate the environmental and socio-economic impacts of forest dynamics. It is challenging, however, to calculate forest area on a large scale using traditional statistical survey methods. Access to satellite images make it f...

Background and Objective Over the past two decades, the intense need for land surface temperature information for environmental studies and management and planning activities has made estimating the land surface temperature one of the most important scientific topics. On the other hand, different methods have been proposed to estimate the land surf...

This paper proposed an extended rotation-based ensemble method for the classification of a multi-source optical-radar data. The proposed method was actually inspired by the rotation-based support vector machine ensemble (RoSVM) with several fundamental refinements. In the first modification, a least squares support vector machine was used rather th...

Due to the excessive use of natural resources in the contemporary world, the importance of ecological and environmental condition modeling has increased. Wetlands and cities represent the natural and artificial strategic areas that affect ecosystem conditions. Changes in the ecological conditions of these areas have a great impact on the conditions...

The surface anthropogenic heat island (SAHI) phenomenon is one of the most important environmental concerns in urban areas. SAHIs play a significant role in quality of urban life. Hence, the quantification of SAHI intensity (SAHII) is of great importance. The impervious surface cover (ISC) can well reflect the degree and extent of anthropogenic act...

Moisture is one of the most important factors affects soil reflectance spectra. Temporary and spatially variability of soil moisture leads to reducing capability of spectroscopy in soil properties estimation. Developing a method that could tackle the effect of moisture on soil properties prediction using spectrometry is necessary. This paper utiliz...

Urban Surface Ecological Status (USES) reflects the structure and function of an urban ecosystem. USES is influenced by the surface biophysical, biochemical, and biological properties. The assessment and modeling of USES is crucial for sustainability assessment in support of achieving sustainable development goals such as sustainable cities and com...

Many scientists and experts have tried to provide better conditions for human comfort with the help of science and technology. From the following two paths, such as existence and non-existence, wisdom and love, matter and meaning, color and colorlessness, medicine and placebo, and in short, we are too far and too close. Since many of the ancients,...

A harmful effect of anthropogenic activities in urban environments is the increases of thermal discomfort and subsequently, a negative effect on humans’ mental and physical performance. Therefore, it is of high importance to detect, monitor, and predict thermal discomfort, especially its temporal and spatial patterns in cities. The objective of thi...

Anthropogenic heat flux (AHF) is a main contributor to the formation of surface urban heat islands (SUHI). Megacities in particular are facing severe problems due to excessive population growth, urban area expansion, human activity, increased energy consumption, and increased anthropogenic heat. In this study, a physical modeling approach based on...

The modeling of Near-Surface Temperature Lapse Rate (NSTLR) is of great importance in various environmental applications. This study proposed a new approach for modeling the NSTLR based on the Normalized Land Surface Temperature (NLST). A set of remote sensing imagery including Landsat images, MODIS products, and ASTER Digital Elevation Model (DEM)...

Modeling and mapping of soil properties are critical in many environmental, climatic, ecological and hydrological applications. Digital soil mapping (DSM) techniques are now commonly applied to predict soil properties with limited data by developing predictive relationships with environmental covariates. Most studies derive covariates from a digita...

Accurate information on soil moisture (SM) is critical in various applications including agriculture, climate, hydrology, soil and drought. In this paper, various predictive relationships including regression (Multiple Linear Regression, MLR), machine learning (Random Forest, RF; Triangular regression, Tr) and spatial modeling (Inverse Distance Wei...

One of the important factors of sustainable development is renewable energies penetration in the energy systems. The present study evaluates the optimum feed-in tariff of photovoltaic electricity production based on the available downward solar radiation potential of each province of Iran while this potential calculated considering geographical, to...

Soil moisture retention is an important environmental factor that controls water availability in agro-ecosystems. Comprehensive information on spatial distribution and patterns of soil properties controlling moisture retention such as organic carbon (OC), clay content, and saturation percentage (SP) are crucial for effective land management and sus...

Dust storms occur when strong winds combine with erodible soils that are mainly located in semi-arid and arid regions of the world. Dust storms are multi-driver phenomena with harmful impacts on health, agriculture, infrastructure, transportation, environment, and economy. These natural-anthropogenic phenomena have been especially influential in so...

Flooding is one of the most problematic natural events affecting urban areas. In this regard, developing flooding models plays a crucial role in reducing flood-induced losses and assists city managers to determine flooding-prone areas (FPAs). The aim of this study is to investigate on the prediction capability of fuzzy analytical hierarchy process...