A5000343846- Remote Sensing in Agriculture
- Plant Water Relations and Carbon Dynamics
- Land Use and Ecosystem Services
- Atmospheric and Environmental Gas Dynamics
- Soil Moisture and Remote Sensing
- Urban Heat Island Mitigation
- Remote Sensing and LiDAR Applications
- Greenhouse Technology and Climate Control
- Leaf Properties and Growth Measurement
- Climate change impacts on agriculture
- Spectroscopy and Chemometric Analyses
- Remote Sensing and Land Use
- Landslides and related hazards
- Plant Stress Responses and Tolerance
- Geology and Paleoclimatology Research
- Smart Agriculture and AI
- Hydrological Forecasting Using AI
- Climate variability and models
- Species Distribution and Climate Change
- Hydrology and Watershed Management Studies
- Plant responses to water stress
- Plant responses to elevated CO2
- Soil and Unsaturated Flow
- Climate change and permafrost
- Tree-ring climate responses
University of Twente
2019-2025
St Petersburg University
2022-2024
GeoInformation (United Kingdom)
2024
Bioinformatics Institute
2016
Although soil moisture is a key factor of hydrologic and climate applications, global continuous high resolution datasets are still limited. Here we use physics-informed machine learning to generate global, long-term, spatially dataset surface moisture, using International Soil Moisture Network (ISMN), remote sensing meteorological data, guided with the knowledge physical processes impacting dynamics. Global Surface (GSSM1 km) provides (0-5 cm) at 1 km spatial daily temporal over period...
Abstract. Vegetation productivity is a critical indicator of global ecosystem health and impacted by human activities climate change. A wide range optical sensing platforms, from ground-based to airborne satellite, provide spatially continuous information on terrestrial vegetation status functioning. As Earth observation (EO) data are usually routinely acquired, can be monitored repeatedly over time, reflecting seasonal patterns trends in metrics. Such metrics include gross primary...
Abstract. The Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model aims at linking satellite observations in the visible, infrared, thermal domains with land surface processes a physically based manner, quantifying microclimate vegetation canopies. It simulates radiative transfer soil, leaves, canopies, as well photosynthesis non-radiative heat dissipation through convection mechanical turbulence. Since first publication 12 years ago, SCOPE has been applied remote...
Crop yield prediction plays an important role in food security. growth models can be used for this purpose, however, they require empirical parametrization. In study, we show that remote sensing observations to parameterize a crop model, providing monitoring and predictions, while mitigating the need extensive field measurements accounting variability varieties. For coupled SCOPE radiative-transfer model with state-rate WOFOST. paper, explain how two are coupled, assess accuracy present...
Introduction Detecting and monitoring crop stress is crucial for ensuring sufficient sustainable production. Recent advancements in unoccupied aerial vehicle (UAV) technology provide a promising approach to map key traits indicative of stress. While using single optical sensors mounted on UAVs could be monitor status general sense, implementing multiple that cover various spectral domains allow more precise characterization the interactions between crops biotic or abiotic stressors. Given...
Estimation of essential vegetation properties from remote sensing is crucial for a quantitative understanding the Earth system. Ill-posedness model inversion problem leads to multiple interpretations one satellite observation, and using prior information promising way reduce ill-posedness increase accuracy land surface products. Tobler's first law geography states that "everything related everything else, but near things are more than distant things". Likewise, it expected state an object at...
Sentinel-3 satellite has provided simultaneous observations in the optical (visible, near infrared (NIR), shortwave (SWIR)) and thermal (TIR) domains since 2016, with a revisit time of 1–2 days. The high temporal resolution spectral coverage make data this mission attractive for vegetation monitoring. This study explores possibilities using Soil Canopy Observation, Photochemistry Energy fluxes (SCOPE) model together to exploit two sensors onboard (the ocean land color instrument (OLCI) sea...
Abstract. Accurate information on surface soil moisture (SSM) content at a global scale under different climatic conditions is important for hydrological and climatological applications. Machine-learning-based systematic integration of in situ measurements, complex environmental climate data, satellite observation facilitate the generation reliable data products to monitor analyse exchange water, energy, carbon Earth system proper space–time resolution. This study investigates estimation...
Savannas, characterized by scattered trees with a grass layer, are key ecosystems in semi-arid regions. They profoundly influence global carbon (C) and water fluxes through high seasonal inter-annual variations. Understanding these dynamics at the ecosystem scale is essential for better representing their impacts on Earth’s climate system. Terrestrial models (TEM) such as QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles system), new generation TEM that...
 Pan-European Network of Green Deal Agriculture and Forestry Earth Observation Science (PANGEOS) funded by the European Cooperation in Technology (COST) organisation brings together researchers to share their expertise bring up a new generation scientists. In October 2024 PANGEOS conducted an intensive 5-day summer school where more than 20 participants learnt how propagate uncertainty spectral measurements higher-level products. The training material form Python Jupyter notebooks...
Most applications of remote sensing in agricultural crop monitoring use multispectral imaging techniques, but with upcoming hyperspectral missions, the opportunity arises to better estimate pigment absorption and structure by exploiting full solar reflective spectrum. In this study, we demonstrate how time series can be used Soil Canopy Observation Photochemistry Energy fluxes (SCOPE) model yield variability among fields, varieties nitrogen treatments generically, i.e. without a calibration...
The most important part of the plant antioxidant system is ascorbate-glutathione cycle (AGC), activity which observed upon exposure to a range stressors, including lack O 2 , and oxidative stress occurring immediately after restoration oxygen access, hereafter termed reaeration or post-anoxia. operation AGC (enzymes low-molecular components) in wheat ( Triticum aestivum cv. Leningradka, non-resistant hypoxia) rice Oryza sativa Liman, resistant) seedlings 24 h anoxia 1 was studied....
Accurate estimates of carbon, water and energy fluxes between the Earth surface atmosphere are crucial for enhancing our understanding ecosystem–climate interactions. Such can be made by combining remote sensing derived land parameters with climate reanalysis data. We analysed to what degree generic (plant functional type (PFT)-independent) satellite-derived vegetation properties data explain extent PFT-specific information extends flux simulations. For this purpose, we used Soil Canopy...
Abstract. The Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model aims at linking satellite observations in the visible, infrared thermal domains with land surface processes a physically based manner, quantifying micro-climate canopy. It simulates radiative transfer soil, leaves vegetation canopies, as well photosynthesis non-radiative heat dissipation through convection mechanical turbulence. Since first publication 11 years ago, SCOPE has been applied remote sensing...
In this study, we demonstrate that the Google Earth Engine (GEE) dataset of Sentinel-3 Ocean and Land Color Instrument (OLCI) level-1 deviates from original Copernicus Open Access Data Hub Service (DHUS) data by 10–20 W m−2 sr−1μμm−1 per pixel band. We compared GEE DHUS single time series for period April 2016 to September 2020 identified two sources discrepancy: ground position reprojection. The OLCI product can be determined in ways: geo-coordinates or tie-point coordinates (GEE)....
Abstract. Accurate information on surface soil moisture (SSM) content at a global scale under different climatic conditions is important for hydrological and climatological applications. Machine learning (ML) based systematic integration of in-situ measurements, complex environmental climate data satellite observation facilitate to generate the best products monitor analyse exchanges water, energy carbon in Earth system proper space-time resolution. This study investigates estimation daily...
Abstract. Vegetation productivity is a critical indicator of global ecosystem health and impacted by human activities climate change. A wide range optical sensing platforms, from ground-based to airborne satellite, provide spatially continuous information on terrestrial vegetation status functioning. As Earth observation (EO) data are usually routinely acquired, can be monitored repeatedly over time; reflecting seasonal patterns trends in metrics. Such metrics include e.g., gross primary...
The study of peatland is challenging due to the water saturation and evergreen mixed vegetation that ranges from simple forms plants such as mosses higher cranberries, grasses, etc. changing level through growing season makes very dynamic. In this work, we have used ground-level remote-sensing signals understand dynamic nature vegetation. We also estimated leaf area index (LAI) Sun-Induced fluorescence (SIF) Soil Canopy Observation Photosynthesis Energy fluxes (SCOPE) model. LAI SIF were...
Crop phenology data offer crucial information for crop yield estimation, agricultural management, and assessment of agroecosystems. Such becomes more important in the context increasing year-to-year climatic variability. The dataset provides in-situ (first leaves emergence harvest date) major European crops (wheat, corn, sunflower, rapeseed) from seventeen field study sites Bulgaria two France. Additional such as sowing date, area each site, coordinates, method equipment used phenophase...