A5061091258- Remote Sensing in Agriculture
- Remote Sensing and LiDAR Applications
- Plant Ecology and Soil Science
- Land Use and Ecosystem Services
- Species Distribution and Climate Change
- Hydrology and Drought Analysis
- Plant Water Relations and Carbon Dynamics
- Fire effects on ecosystems
- Forest ecology and management
- Climate variability and models
- Cryospheric studies and observations
- Soil and Land Suitability Analysis
- Horticultural and Viticultural Research
- Plant and animal studies
- 3D Surveying and Cultural Heritage
- Ecology and Vegetation Dynamics Studies
- Engine and Fuel Emissions
- Tree-ring climate responses
- Precipitation Measurement and Analysis
- Climate change and permafrost
- Geochemistry and Geologic Mapping
- Flood Risk Assessment and Management
- Conservation, Biodiversity, and Resource Management
- Remote-Sensing Image Classification
- Urban Heat Island Mitigation
University of Agriculture in Krakow
2023-2025
Transylvania University of Brașov
2022-2023
University of Tehran
2018-2022
Accurate and real-time land use/land cover (LULC) maps are important to provide precise information for dynamic monitoring, planning, management of the Earth. With advent cloud computing platforms, time series feature extraction techniques, machine learning classifiers, new opportunities arising in more accurate large-scale LULC mapping. In this study, we aimed at finding out how two composition methods spectral–temporal metrics extracted from satellite can affect ability a classifier...
Forest canopy cover (FCC) is an important ecological parameter of forest ecosystems, and correlated with characteristics, including plant growth, regeneration, biodiversity, light regimes, hydrological properties. Here, we present approach combining Sentinel-2 data, high-resolution aerial images, machine learning (ML) algorithms to model FCC in the Hyrcanian mixed temperate forest, Northern Iran. multispectral bands vegetation indices were used as variables for modeling mapping based on UAV...
The tree species composition (TSC) reflects a forest's diversity and is relevant for forest planning, biodiversity conservation, resources management. Yet, accurate information on at landscape scale largely missing, especially mixed forests remote areas. One reason being that mapping time-consuming, costly, in Here we develop robust method TSC temperate forest. Based inventory plots considering the frequency of dominant dataset, five groups were defined: pure oriental beech, common hornbeam,...
Tree height and crown diameter are two common individual tree attributes that can be estimated from unmanned aerial vehicle (UAV) images thanks to photogrammetry structure motion. This research investigates the potential of low-cost UAV estimate diameter. Two successful flights were carried out in different seasons corresponding leaf-off leaf-on conditions generate a digital terrain model surface model, which further employed calculation canopy (CHM). The CHM was used using low pass local...
Despite utilizing various remote sensing datasets, precise tree-cutting detection remains challenging due to spatial and spectral resolution constraints in satellite imagery, complex landscapes, data integration issues, the need for accurate multi-temporal reference datasets. This study investigates utilization of PlanetScope (PS) images, along with pixel-based (PBIA) object-based (OBIA) image analysis, mapping forest cover tree cuttings. Detailed datasets were collected based on airborne...