A5089535226- Remote Sensing in Agriculture
- Remote Sensing and Land Use
- Botany and Plant Ecology Studies
- Remote-Sensing Image Classification
- Remote Sensing and LiDAR Applications
- Plant Ecology and Soil Science
- Lichen and fungal ecology
- Hydrology and Drought Analysis
- Forest ecology and management
- Urban Heat Island Mitigation
- Heavy metals in environment
- Peatlands and Wetlands Ecology
- Neural Networks and Applications
- Integrated Water Resources Management
- Diverse Scientific Research in Ukraine
- Machine Learning and ELM
- Land Use and Ecosystem Services
- Climate change and permafrost
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Cryospheric studies and observations
- Forest, Soil, and Plant Ecology in China
- Time Series Analysis and Forecasting
- Turfgrass Adaptation and Management
- Soil Moisture and Remote Sensing
- Face and Expression Recognition
Institute of Geodesy and Cartography
2010-2021
Contemporary satellite Earth Observation systems provide growing amounts of very high spatial resolution data that can be used in various applications. An increasing number sensors make it possible to monitor selected areas great detail. However, order handle the volume data, a level automation is required. The semi-automatic change detection methodology described this paper was developed annually update land cover maps prepared context Geoland2. proposed algorithm tailored work with...
Remote sensing is a suitable candidate for monitoring rapid changes in Polar regions, offering high-resolution spectral, spatial and radiometric data. This paper focuses on the spectral properties of dominant plant species acquired during first week August 2015. Twenty-eight plots were selected, which could easily be identified field as well RapidEye satellite imagery. Spectral measurements individual acquired, heavy metal contamination stress factors measured contemporaneously. As result,...
The main objectives of the research work were to determine usefulness Landsat and SPOT data for monitoring various forest parameters, assess impact changeable climatic conditions with use vegetation indices derived from remotely sensed data. Vegetation describing aspects plant condition structure satellite images, their values analysed in a temporal profile different seasons, conjunction meteorological parameters. results analyses proved that dedicated water stress plants – disease index...
Abstract Heavy metals and radioactive compounds are potentially hazardous substances for plants, animals humans in the Arctic. A good knowledge of spatial variation these soil primary producers, their sources, is therefore essential. In samples lichen Thamnolia vermicularis, Salix polaris Cassiope tetragona, collected 2014 Svalbard near Longyearbyen, concentrations following heavy were determined: Mn, Ni, Cu, Zn, Cd, Pb Hg, as well activity following: K-40, Cs-137, Pb-210, Pb-212, Bi-212,...
Remote sensing, which is based on a reflected electromagnetic spectrum, offers wide range of research methods. It allows for the identification plant properties, e.g., chlorophyll, but registered signal not only comes from green parts also dry shoots, soil, and other objects located next to plants. is, thus, important identify most applicable remote-acquired indices chlorophyll detection in polar regions, play primary role global monitoring systems consist areas with high low accessibility....
Abstract We have compared historical changes in concentrations of the heavy metals Mn, Ni, Cu, Zn, Cd and Pb accumulated samples from Polish woodlands Beskidy Karkonosze (S, SE Poland) north-east regions country, versus relatively little polluted areas Spitsbergen Svalbard Archipelago. combined results literature with new 2014. The were most exposed to deposition. However, 1975 2014 there was a considerable decrease at all sites, clearly signifying improvement environmental quality. For...
The use of effective methods for large-area drought monitoring is an important issue; hence, there have been many attempts to solve this problem. In study, the Drought Information Satellite System (DISS) index presented, based on synergistic meteorological data and information derived from satellite images. allows us monitor phenomena in various climatic environmental conditions. approach utilizes two indices constructing a index: (1) hydrothermal coefficient (HTC), which characterizes...
Artificial Neural Networks (ANN) is an important technique for land cover classification of high resolution images. However, there are many inherent limitations ANN based on Multi-Layer Perception (MLP) with back propagation such as the necessity fine-tuning number input parameters and slow convergence time. Therefore, attempt has been made to introduce explore potential Extreme Learning Machine (ELM) which deviates from iterative weight adjustment neurons during learning process extremely...
The study was carried out for agricultural area in Poland the years 2016-2017. aim of project to examine applicability vegetation parameters calculated from Sentinel-2 and PROBA-V satellite data crop yield prognosis. extensive field measurements have been parallel Proba-V overpasses order elaborate best relationship between in-situ measured LAI. Finally prognosis model based on meteorological with periodical input LAI wheat has applied. Additionally classification crops over JECAM site...
The study covered the analysis of crop development during seasons for years various conditions. Temperature Condition Index characterized growth vegetation season. For better assessment conditions, TCI was taken as decaying 3-point moving average. examination has been done to find out delay in reaction on lack precipitation and increase air temperature. approach utilizes two indices constructing a drought index: (1) hydrothermal coefficient (HTC), which characterizes meteorological...
The study is carried out for agricultural areas in Poland and South Africa the years 2019–2021. aim of project to develop crop growth monitoring system using Copernicus satellite data (Sentinel-1,-2,-3) low-resolution from Terra MODIS satellites. At first stage analysis Sentinel-2 indices, based on various combinations spectral reflectance, were derived particular fields within JECAM sites. correlation coefficients between S-2 indices LAI most often exceed 0.7 precision determination varies...
The transfer of knowledge from research community to specialized remote sensing software has been extremely slow hindering the application ANN techniques in field. There are many variants depending upon its topology and learning paradigms but Multilayer perception (MLP) with back propagation (BP) is widely used despite limitation such as fine tuning numbers input parameters rate, momentum, number hidden layers nodes. In this paper, recently proposed Extreme Learning Machine (ELM) version...
This paper presents the main concepts and initial analysis of ESA SEOM project SInCohMap "EXPLOITATION OF SENTINEL-1 INTERFEROMETRIC COHERENCE FOR LAND COVER AND VEGETATION MAPPING". The evaluates performance using interferometric coherence S-1 time series for land cover vegetation mapping. One objectives is to quantify impact in InSAR (Interferometric Synthetic Aperture Radar) data relative traditional mapping optical (especially Sentinel-2, hereafter named S-2) or SAR-based (Synthetic...
Landscape is heterogeneous part of the Earth surface, forming mosaic various habitats organized at different scales and levels (Johnson et al. 1992). The landscape pattern has important impact on ecological processes; hence its analysis through quantitative measures essential for environmental studies. There are many indicators characterizing spatial structure level detail; they enable fragmentation patch level, studies habitat up to complex analyses level. Seven indicators, which related...