A5064894817- Hydrology and Watershed Management Studies
- Hydrological Forecasting Using AI
- Flood Risk Assessment and Management
- Hydrology and Drought Analysis
- Soil erosion and sediment transport
- Remote Sensing in Agriculture
- Remote Sensing and LiDAR Applications
- Land Use and Ecosystem Services
- Air Quality Monitoring and Forecasting
- Air Quality and Health Impacts
- Soil Moisture and Remote Sensing
- Hydrology and Sediment Transport Processes
- Remote Sensing and Land Use
- Climate variability and models
- Groundwater and Watershed Analysis
- Landslides and related hazards
- Urban Design and Spatial Analysis
- Neural Networks and Applications
- Energy Load and Power Forecasting
- Remote-Sensing Image Classification
- BIM and Construction Integration
- Soil and Unsaturated Flow
- Human Mobility and Location-Based Analysis
- Rangeland Management and Livestock Ecology
- Water resources management and optimization
Tarbiat Modares University
2012-2024
École Polytechnique Fédérale de Lausanne
2020-2022
ETH Zurich
2015-2021
Canberra Hospital
2018-2020
Soil Conservation and Watershed Management Research
2020
Calvary Hospital
2019
Yazd University
2013-2018
Abstract Computational complexity has been the bottleneck for applying physically based simulations in large urban areas with high spatial resolution efficient and systematic flooding analyses risk assessment. To overcome issue of long computational time accelerate prediction process, this paper proposes that maximum water depth can be considered an image‐to‐image translation problem which rasters are generated using information learned from data instead by conducting simulations. The...
Data-driven and machine learning models have recently received increasing interest to resolve the computational speed challenge faced by various physically-based simulations. A few studies explored application of these develop new, fast, applications for fluvial pluvial flood prediction, extent mapping, susceptibility assessment. However, most focused on model development specific catchment areas, drainage networks or gauge stations. Hence, their results cannot be directly reused other...
ABSTRACT Assessment of the watershed health and associated ecological security is crucial for proper land resources management, notably when sufficient money time have lacked. The present study aimed to prepare Pishkuh Watershed in Yazd Province, central Iran. To atlas Watershed, conceptual framework pressure, state, response (PSR) was employed. pressure index investigated by analyzing driving forces natural human-induced factors. Then, existing conditions environment performance were...
Estimation of suspended sediment load is one the important topics in river engineering. Different methods are used for estimating rate. In recent years, different artificial intelligence (AI) methods, such as neural network (ANN), have been estimation sediments rivers. this research, has studied by using regression trees (RTs) and model (MTs). The study area located Hyderabad watershed west Iran. input data included flow discharge, sum three days five precipitation discharge were considered...
Research Article| May 01, 2015 Gully Erosion Mapping Using Object-Based and Pixel-Based Image Classification Methods AYOOB KARAMI; KARAMI Faculty of Natural Resources, Hormozgan University, Minab Road, Bandar Bbbas, Province, P.O. Box 3995, Iran Search for other works by this author on: GSW Google Scholar ASADOLLAH KHOORANI; KHOORANI 1 1Corresponding email: khoorani@hormozgan.ac.ir. AHMAD NOOHEGAR; NOOHEGAR Tehran Karaj, SEYED RASHID FALLAH SHAMSI; SHAMSI College Agriculture, Shiraz 71454,...
This article presents a computer-aided design framework for the generation of non-standard structural forms in static equilibrium that takes advantage interaction between human and machine intelligence. The relies on implementation series operations (generation, clustering, evaluation, selection, regeneration) allow to create multiple options navigate space according objective subjective criteria defined by designer. Through intelligence, can learn nonlinear correlation inputs outputs...
The main objective of this study is to combine remote-sensing and artificial intelligence (AI) approaches estimate surface soil moisture (SM) at 100 m spatial daily temporal resolution. two variables used in the Triangle method, that is, land-surface temperature (LST) vegetation cover, were downscaled calculated LSTs applying Wavelet-Artificial Intelligence Fusion Approach (WAIFA) on Moderate Resolution Imaging Spectroradiometer (MODIS) Landsat imageries. Vegetation fractions also estimated...