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Jędrzej S. Bojanowski

Jędrzej S. Bojanowski
CloudFerro / CREODIAS

PhD

About

39
Publications
11,213
Reads
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507
Citations
Citations since 2016
20 Research Items
403 Citations
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2016201720182019202020212022020406080
2016201720182019202020212022020406080
2016201720182019202020212022020406080
Additional affiliations
January 2017 - present
Institute of Geodesy and Cartography
Position
  • Professor (Assistant)
Description
  • http://www.igik.edu.pl/en/Remote-Sensing-Variability-and-change-of-cloudiness-diurnal-cycle-over-the-past-30-years
March 2013 - December 2016
MeteoSwiss
Position
  • PostDoc Position
Description
  • http://www.esa-cloud-cci.org/ http://www.cmsaf.eu
January 2010 - January 2013
Joint Reseach Centre
Position
  • Generating long-term time series of daily gridded solar radiation data for Europe: application of satellite and weather station data
Education
January 2010 - January 2014
University of Twente
Field of study
  • Faculty of Geo-Information Science and Earth Observation (ITC)
September 2000 - December 2005
University of Warsaw
Field of study
  • Department of Geography and Regional Studies

Publications

Publications (39)
Article
Full-text available
Can we build stable Climate Data Records (CDRs) spanning several satellite generations? This study outlines how the ClOud Fractional Cover dataset from METeosat First and Second Generation (COMET) of the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) was created for the 25-year period 1991–2015. Modern multi-spectral cloud d...
Article
Full-text available
Radiometers such as the AVHRR (Advanced Very High Resolution Radiometer) mounted aboard a series of NOAA and MetOp (Meteorological Operational) polar-orbiting satellites provide 4-decade-long global climate data records (CDRs) of cloud fractional cover. Generation of such long datasets requires combining data from consecutive satellite platforms. A...
Article
Full-text available
Forests play a key role in humanity’s current challenge to mitigate climate change thanks to their capacity to sequester carbon. Preserving and expanding forest cover is considered essential to enhance this carbon sink. However, changing the forest cover can further affect the climate system through biophysical effects. One such effect that is seld...
Article
Well-maintained and regularly calibrated measuring instruments provide the most accurate solar radiation data. This extremely valuable research material makes it possible, among others, to analyse variability in solar radiation over the long term and its dependence on other atmospheric state elements such as cloud cover and atmospheric aerosol conc...
Article
Full-text available
The Vectorized Earth Observation Retrieval (VEOR) algorithm is a novel algorithm suited to the efficient supervised classification of large Earth Observation (EO) datasets. VEOR addresses shortcomings in well-established machine learning methods with an emphasis on numerical performance. Its characteristics include (1) derivation of classification...
Poster
Full-text available
Identification of crops over large areas is necessary for monitoring agricultural production, establishing food security policies or controlling compliance with the Common Agricultural Policy. Data acquired by Sentinel-1 and Sentinel-2 satellite constellations with a combination of high temporal and spatial resolutions has already demonstrated, sep...
Article
Full-text available
Timely crop yield forecasts at a national level are substantial to support food policies, to assess agricultural production, and to subsidize regions affected by food shortage. This study presents an operational crop yield forecasting system for Poland that employs freely available satellite and agro-meteorological products provided by the Copernic...
Article
Full-text available
The productivity response of a peatland ecosystem in Rzecin, Poland, was determined based on varying aerosols abundant in the atmosphere. The study was done with the use of a multifactorial model that combined atmospheric and ecosystem modules to describe plant photosynthetic ability from different perspectives. The Gross Ecosystem Production (GEP)...
Article
Full-text available
Crop classification is a crucial prerequisite for the collection of agricultural statistics, efficient crop management, biodiversity control, the design of agricultural policy, and food security. Crops are characterized by significant change during the growing season, and this information can be used to improve classification accuracy. However, cap...
Preprint
Full-text available
Timely crop yield forecasts at national level are substantial to support food policies, to assess agricultural production and to subsidize regions affected by food shortage. This study presents an operational crop yield forecasting system for Poland that employs freely available satellite and agro-meteorological products provided by the Copernicus...
Data
Ground-based measurements of global solar radiation are often subject to various errors which are very difficult to detect. This is why quality control procedures and homogenisation of data are essential and should be performed prior to further analyses. We present homogeneous global solar radiation data set, without any gaps, for 16 ground-based s...
Preprint
Full-text available
Abstract. Radiometers such as the AVHRR mounted aboard a series of the NOAA and MetOp polar-orbiting satellites provide 4-decade-long global climate data records (CDRs) of cloud fractional cover. Generation of such long datasets requires combining data from consecutive satellite platforms. A varying number of satellites operating simultaneously in...
Conference Paper
Full-text available
Clouds play a key role in the Earth’s radiation budget by reflecting shortwave radiation and reducing emissions of longwave radiation. A temporal shift in diurnal cycle of cloud formation leads to significant feedbacks in the climate system. The CM SAF ClOud Fractional Cover (CFC) dataset from METeosat First and Second Generation - Edition 1 (COMET...
Article
Full-text available
The CM SAF Cloud Fractional Cover dataset from Meteosat First and Second Generation (COMET, https://doi.org/10.5676/EUM_SAF_CM/CFC_METEOSAT/V001) covering 1991–2015 has been recently released by the EUMETSAT Satellite Application Facility for Climate Monitoring (CM SAF). COMET is derived from the MVIRI and SEVIRI imagers aboard geostationary Meteos...
Article
Full-text available
Solar radiation is the main driver of the Earth's climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy...
Article
Full-text available
The study presents first edition of cloud coverage and cloud physical properties climate data records (CDRs) over Central Europe compiled from 1x1 km2 resolution AVHRR imagery. The CDRs cover a climatological period of 30 years from 1986 to 2016. The dataset was generated using a novel Vectorized Earth Observation Retrieval (VEOR) algorithm that is...
Article
Full-text available
New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrieva...
Conference Paper
Full-text available
Generating a cloud climate data record (CDR) from observations acquired by a set of polar orbiting satellites requires dealing with potential artefacts caused by lack of long-term stability, degradation of satellite sensors, radiometric and geometric calibration problems, and satellite orbital drift. The majority of these aspects have been resolved...
Preprint
Full-text available
New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrieva...
Article
Full-text available
The European Organization for the Exploitation of Meteorological Satellites' (EUMETSAT) Meteosat satellites provide the unique opportunity to compile a 30+ year land surface temperature (LST) climate data record. Since the Meteosat instrument on-board Meteosat 2-7 is equipped with a single thermal channel, single-channel LST retrieval algorithms ar...
Article
Full-text available
Cloud property data sets derived from passive sensors onboard the polar orbiting satellites (such as the NOAA’s Advanced Very High Resolution Radiometer) have global coverage and now span a climatological time period. Synoptic surface observations (SYNOP) are often used to characterize the accuracy of satellite-based cloud cover. Infrequent overpas...
Article
Satellite-derived surface solar radiation estimates are an alternative to the solar radiation measured at weather stations or modelled from other measured meteorological variables. The advantage of satellite-derived solar radiation is its high spatial and temporal resolution in comparison with solar radiation derived from weather stations, which ha...
Thesis
Full-text available
The energy of the sun drives physical, chemical and biological processes taking place in the earth-atmosphere system, thereby determining the earth’s climate and making organic life on earth possible. Solar radiation provides the energy that plants need for growth. The knowledge about the spatial distribution and temporal variation of solar radiati...
Article
Solar radiation is a key input variable for crop growth models. However, direct measurement of solar radiation is performed operationally for only a limited number of weather stations. Instead of direct measurements, empirical solar radiation models are used that link solar radiation to more commonly measured meteorological variables. Coefficients...
Conference Paper
Full-text available
The European Commission requires in-season crop yield forecasts at a European level as part of the decision making process on market intervention and for policy support. For the past twenty years, the Monitoring Agricultural Resources (MARS) Unit of the European Commission Joint Research Centre (JRC) has operationally produced such forecasts using...
Article
Full-text available
Low spatial resolution of the NOAA-AVHRR images causes that observation footprints of the pixels can overlay the surface of more than one land cover type. The pure signal can be obtained for pixels covering only one land cover class. The extraction of the vegetation index (e.g. NDVI) for one land cover class can be interfered by the presence of oth...
Article
Crop monitoring systems that rely on agrometeorologic models require estimates of global radiation. These estimates are difficult to obtain due to the limited number of weather stations that measure this variable. In the present study, we validated the global radiation estimates derived from MeteoSat Second Generation (MSG) and evaluated their use...
Conference Paper
Full-text available
The area of the research is a part of the Landscape Park and belongs to agri-environment ecosystem of South-West Poland. The study on vegetation growth conditions has been carried out applying optical data from TERRA/ASTER, TERRA/MODIS, and ENVISAT/MERIS as well as microwave data from ENVISAT/ASAR. In situ data collected at the time of satellite ob...
Article
Full-text available
In this paper we briefly present a whole processing chain for the preparation of NDVI 10- day composites derived from NOAA/AVHRR in 1 km2 spatial resolution and then we put strong emphasis on final noise reduction of the NDVI time series. The method of noise reduction is based on the Savitzky-Golay filter, which was introduced by Chen (2004). It in...
Article
Full-text available
The protection and regeneration of wetlands has been of crucial importance as a goal in ecological research and in nature conservation for some time and is more important than ever now. Knowledge about the biophysical properties of wetlands' vegetation retrieved from satellite images enables us to improve the monitoring of these unique areas, which...

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Cited By

Projects

Projects (3)
Archived project
The aim of the project is to develop and verify a method for detecting errors in ground-based measurement data on global solar radiation reaching the Earth's surface, and to devise a method for homogenising these data. To this end, the project will use high-resolution satellite data on solar radiation. The method for quality control and restoring homogeneity in measurement data developed in this project will make it possible to verify quality of radiation measurements in their native resolution. This is of the utmost importance for advancing research on solar radiation. The base of homogenic ground-based climatological data on global solar radiation in Poland, elaborated as part of the project, is made available to other researchers in the form of a digital repository. Thanks to that, it will be possible to use the results of the project in many applications, among others in agriculture and solar industry.
Project
The project aims to develop methods for a collection of statistical information about agricultural production and methods for a control of farmers’ activity in Poland using satellite data. CBK PAN is responsible for the following tasks: - Development of procedures for training/validation data collection - Development of algorithms for: - Crop classification based on SAR Sentinel-1 images - Crop classification based on synergistic use of Sentinel-1 and Sentinel-2 images - Toolboxes development for: - Automatic downloading and pre-processing of satellite images - Automatic crop classification - Aggregation routine of crop classification maps for verification of crop diversification - Development of a methodology for comprehensive verification of Ecological Focus Areas (EFA) for the requirements of direct support and greening systems Project is realised in the consortium composed by: IGIK (responsible for the development of methods for crop growth monitoring, yield prediction, detection of critic situations for crop), Kappazeta – development of an approach for monitoring of maintenance of permanent grasslands; and CBK PAN. Polish Statistics and the Agency for Restructuring and Modernisation of Agriculture act as a Steering Board and the end-users.
Project
The primary goal of this study is to render the satellite-derived dataset suitable for climate analysis. Cloud property datasets derived from passive sensors onboard a series of polar orbiting satellites (such as NOAA and MetOp) have a global coverage and now span a climatological time period (30 years). However, changes in a number of simultaneously operating satellites, drift of their orbits and varying equatorial crossing times of consecutive satellite missions lead to a different frequency of image acquisitions per day, and to their different local time. When observing the atmospheric state of a distinct diurnal cycle, such as cloud formation, the changing number and local time of measurements lead to uncertainty in cloud characteristics in the same order of magnitude as the GCOS requirements on decadal stability of cloud fraction data. Specifically we aim to: 1) develop and validate a method for statistical reconstruction of cloud cover diurnal cycle, 2) create a 30-year global cloud fraction climatology (1°×1°) suitable for trend analysis by correcting the satellite orbital drift issue, 3) quantify global changes in cloud cover distribution and in diurnal cycle of cloud formation over the last 30 years. See details on http://www.igik.edu.pl/pl/Remote-Sensing-Variability-and-change-of-cloudiness-diurnal-cycle-over-the-past-30-years