Kourosh Ahmadi

• Ph.D. Environmental Modelling
• Researcher at Lund University

Climate change has diverse effects on the planet’s environment, including changes and shifts in the distribution and abundance of species. In this paper, we present a robust prediction ensemble algorithm for the current and future species distribution of Aegilops tauschii. Four modeling approaches were trained using various environmental variables...

The first national-wide epidemiological modeling of oak charcoal disease in the Zagros forest of Iran is presented. We estimate that the areas prone to epidemic development can be predicted by a combination of massive on-site data analysis and machine-learning approaches. Data collected on the affected trees in an area of 3.1 M ha of oak forests an...

The first national-wide epidemiological modeling of oak charcoal disease in the Zagros forest of Iran was presented. We estimate that the areas prone to epidemic development can be predicted by a combination of massive on-site data analysis and machine-learning approaches. Data collected on the affected trees in an area of 3.1 M ha of oak forests a...

The current research is conducted to model the effect of climate change and land use change (LUC) on the geographical distribution of Quercus brantii Lindl. (QB) forests across their historical range. Forecasting was done based on six general circulation models under RCP 2.6 and RCP 8.5 future climate change scenarios for the future years 2050 and...

Land degradation encompasses ecological, biological, and physical deterioration of land resulting from natural or anthropo�genic factors, including soil erosion. Piping erosion, specifcally in arid and semi-arid regions, is recognized as a signifcant cause of land degradation. Therefore, it is crucial to identify the infuential factors and spatial...

Investigating the correlation between environmental variables and species distribution should be performed using data acquired from appropriate spatial scales to meet adaptive management requirements in a changing environment. This study aimed to model the influence of climate change on the spatial distribution of Br’nt's oak (Quercus brantii Lindl...

The present study models the effect of climate change on the distribution of Persian oak (Quercus brantii Lindl.) in the Zagros forests, located in the west of Iran. The modeling is conducted under the current and future climatic conditions by fitting the machine learning method of the Bayesian additive regression tree (BART). For the anticipation...

Species distribution models (SDMs) are useful for predictive and explanatory purposes, allowing biologists to identify how human and environmental factors influence distributions of plants and animals. Lack of high-resolution climatic variables is one of the challenges for accurately predicting distributions of organisms at local or landscape scale...

Prioritizing new areas for conservation in the Hyrcanian mountain forests is important because future climate change is an immediate threat to endangered species in these areas. Taxus baccata L. (European yew) is one of the most important coniferous species of the Hyrcanian forests that is endangered today for various reasons; therefore, the conser...

Today, water supply in order to achieve sustainable development goals is one of the most important concerns and challenges in most countries. For this reason, accurate identification of areas with groundwater potential is one of the important tools in the protection, management and exploitation of water resources. Accordingly, the present study was...

A major earthquake (6.9 Moment magnitude) occurred in the Sikkim and Darjeeling areas of the Indian Himalaya as well as in the adjacent Nepal on 18th September 2011, triggering a large number of landslides. A total of 188 landslide locations were extracted in order to create the landslide inventory map (LIM). The earthquake-induced landslide suscep...

One of the important issues in plant autecology is the analysis and understanding of species-environment relationships and response of species to ecological gradients. Understanding how species respond to environmental variables is useful for predicting the environmental and geographic distribution of species. The main objective of this research is...

Nepeta crispa Willd. is a very rare medicinal plant that grows in a very limited habitat in western Iran. In recent years, due to climate change, many plants have become endangered, which poses a very serious threat to very rare species such as N. crispa Willd. In the present study, we aimed to model the current and future potential geographical di...

Flood is the most common natural hazard that causing unprecedented loss of life and property in the world. In recent years, flood damage has increased due to human intervention and land use and climate changes. The purpose of this study is to predict flood susceptibility in Tafresh watershed in Markazi Province, Iran based on K-nearest neighbor (KN...

The modeling and prediction of land movement susceptibility hazards, i.e., debris flow, landslide, and rock fall, can assist in controlling and preventing a variety of societal and environmental damages. The purpose of this study was to develop a land movement susceptibility hazard model of debris flow, landslide, and multiple land movement, i.e.,...

The main aim of this research is to predict the impact of seasonal precipitation regimes on flood hazard applying machine learning models. For this purpose, twelve static variables and eight rainfall dynamics variables for 2050s (RCP 2.6 and 8.5) were used as conditioning factors. Four machine learning algorithms including K-Nearest Neighbour (KNN)...

The main aim of this research is to predict the impact of seasonal precipitation regimes on flood hazard applying machine learning models. For this purpose, twelve static variables and eight rainfall dynamics variables for 2050s (RCP 2.6 and 8.5) were used as conditioning factors. Four machine learning algorithms including K-Nearest Neighbor (KNN),...

Nitrate is a major pollutant in groundwater whose main source is municipal wastewater and agricultural activities. In the present study, Bayesian approaches such as Bayesian generalized linear model (BGLM), Bayesian regularized neural network (BRNN), Bayesian additive regression tree (BART), and Bayesian ridge regression (BRR) were used to model gr...

The predicts current and future flood risk in the Kalvan watershed of northwestern Markazi Province, Iran. To do this, 512 flood and non-flood locations were identified and mapped. Twenty flood-risk factors were selected to model flood risk using several machine learning techniques: conditional inference random forest (CIRF), the gradient boosting...

Landslides are most catastrophic and frequently occurred across the world. In mountainous areas of the globe, recurrent occurrences of landslide have caused huge amount of economic losses and a large number of casualties. In this research, we attempted to estimate the potential impact of climate and LULC on future landslide susceptibility in of Mar...

Large damages and losses resulting from floods are widely reported across the globe. Thus, the identification of the flood-prone zones on a flood susceptibility map is very essential. To do so, 13 conditioning factors influencing the flood occurrence in the Brisbane river catchment in Australia (i.e., topographic, water-related, geological, and lan...

Description of the subject. This study evaluates the application of Boosted Regression Trees (BRT) for predicting beech dominant height in the Hyrcanian forests of Iran, inscribed as a UNESCO’s World Heritage due to its remarkable biodiversity. Objectives. It is widely accepted that tree growth can be influenced by a wide variety of factors such a...

This study predicts forest fire susceptibility in Chaloos Rood watershed in Iran using three machine learning (ML) models—multivariate adaptive regression splines (MARS), support vector machine (SVM), and boosted regression tree (BRT). The study utilizes 14 set of fire predictors derived from vegetation indices, climatic variables, environmental fa...

The estimation and mapping of forest stand characteristics are vital because this information is necessary for sustainable forest management. The present study considers the use of a Bayesian additive regression trees (BART) algorithm as a non-parametric classifier using Sentinel-2A data and topographic variables to estimate the forest stand charac...

The Hyrcanian Forest region is rich in relict species, and endemic and endangered species. Although there are concerns about climate change, its influence on tree species in the Hyrcanian forests in the north of Iran is still unidentified. Taxus baccata is among the few conifer species found in the region, and the present study aims to evaluate the...

Predicting landslide occurrences can be difficult. However, failure to do so can be catastrophic, causing unwanted tragedies such as property damage, community displacement, and human casualties. Research into landslide susceptibility mapping (LSM) attempts to alleviate such catastrophes through the identification of landslide prone areas. Computat...

Iran's Hyrcanian forests cover a relatively narrow strip in the northeastern part of the country, and are among the most important and valuable ecosystems inscribed in United Nations Educational, Scientific and Cultural Organization (UNESCO) World Heritage List. European yew Taxus baccata L. is a Tertiary relict in the region and a long‐lived dioec...

Gully erosion is the most active hydro-geomorphological phenomenon in the continental areas due to the high erosion rates triggered by the gully system. Monitoring and modelling gully development and gully distribution will contribute to understand landforms evolution and risk assessment. The purpose of the current research is to model head-cut gul...

Knowing the natural and human potentials of each area makes it possible for the development planning to be done based on the current situation and its potential. Typical tourism areas of the country are one of the key issues in policymaking and tourism development, where attracting private sector investment, will provide sustainable regional develo...

The Hyrcanian climate in the northern parts of Iran has warmed over the past 50 years, but the impacts on plant species are unknown. As the longest-lived tree in the Hyrcanian forest, English yew, Taxus baccata L., is a rare and endangered species in the forests along the Iranian coasts of the Caspian Sea, which is likely affected by climate change...

Freshwater scarcity is an ever-increasing problem throughout the arid and semi-arid countries, and it often results in poverty. Thus, it is necessary to enhance understanding of freshwater resources availability, particularly for groundwater, and to be able to implement functional water resources plans. This study introduces a novel statistical app...

In this study, the site form index which is the most reliable criterion for evaluation of forest site productivity in uneven-aged and mixed stands was used. For this purpose, random-systematic sampling method was used to locate 105 0.1 ha circular sample plots in beech dominated forests in Tarbiat Modares University research forest. The height and...

Study of forest structure is important, especially discussions of the importance of close to Nature silviculture purposes. This study was conducted to evaluate for stands of Pistachio (Pistacia atlantica) structure in the Baghe Shadi protected area in Yazd province. In this study, the sampling method with a fixed area plot has been used. A total of...

Regarding the ever increasing issue of water scarcity in different countries, the current study plans to apply support vector machine (SVM), random forest (RF), and genetic algorithm optimized random forest (RFGA) methods to assess groundwater potential by spring locations. To this end, 14 effective variables including DEM-derived, river-based, fau...

In the domain of sustainable forest management, site productivity assessment is a major forestry topic. The reliable estimates of site quality are crucial for improved predictions of timber yields and for meaningful simulation studies. Site quality curves were constructed and assessed for beech forests in a Hyrcanian forest, located in the north of...

In this study, 39 generalized height-diameter prediction models were developed for Oriental beech (Fagus orientalis Lipsky) in the Hyrcanian forest in Iran. Data were collected from 75 permanent sample plots in uneven-aged stands of F. orientalis. A total of 1,067 individual tree height-diameter measurements were available for this study. For model...

Velvet maple (Acer velutinum) is one of the woody species in the Hyrcanian forests. In this study, the relationship between height and diameter of velvet maple was surveyed. A complete list of the selected heightdiameter models was used and nineteen candidate models were considered. Various criteria were chosen and applied to evaluate the predictiv...

In arid and semi-arid lands using industrial wastewater for irrigating tree plantations offers a great opportunity to fulfill the purpose of Clean Development Mechanism by sequestering carbon in living tissues as well as in soil. Selection of tree for plantation has a great effect on the goal achievements, especially when the managers deal with aff...

Abstract Site productivity is a key indicator of forest ecosystem such as timber production and carbon sequestration; therefore it is an important criterion for forest manager. This index was used by forester in order to estimate the yield, annual exploitation and growth, and choose the most suitable tree species for sites as well. There are many m...

Abstract Relationship between environmental variables and site productivity is one of the important issues in forest management. In the past, investigation of this relationship was performed using basic methods such as linear regression (LR) but recently, new methods are being used that one of these techniques is Artificial Neural Network (ANN). In...

Height - diameter equations are often used to estimate tree height, when tree diameter is the only measured variable. Considering that tree diameter measuring is often easier and inexpensive than tree height, height-diameter functions are generally used to estimate tree height. In this study, nineteen non-linear height-diameter equations were fitte...

Abstract Height - diameter equations are often used to estimate tree height, when tree diameter is the only measured variable. Considering that tree diameter measuring is often easier and inexpensive than tree height, height-diameter functions are generally used to estimate tree height. In this study, nineteen non-linear height-diameter equations w...

The relationship between tree height and diameter is an important element in growth and yield models, in carbon budget and timber volume models, and in the description of stand dynamics. Six non-linear growth functions (i.e. Chapman-Richards, Schnute, Lundqvist/Korf, Weibull, Modified Logistic and Exponential) were fitted to tree height-diameter da...