Kotarba, A.Z, Nguyen Huu, Ż. (2022) Accuracy of cirrus detection by surface-based human observers

The longest cirrus time series are ground-based, visual observations captured by human observers [synoptic observations (SYNOP)]. However, their reliability is impacted by an unfavorable viewing geometry (cloud overlap) and misclassification due to low cloud

Bojanowski J., Sikora S., Musiał J., Woźniak E., Katarzyna Dąbrowska-Zielińska K., Slesiński P., Milewski T., Łączyński A. (2022), Integration of Sentinel-3 and MODIS Vegetation Indices with ERA-5 Agro-meteorological Indicators for Operational Crop Yield Forecasting

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

Woźniak E., Rybicki M., Kofman W., Aleksandrowicz S., Wojtkowski C., Lewiński S., Bojanowski J., Musiał J., Milewski T., Slesiński P., Łączyński A. (2022), Multi-temporal phenological indices derived from time series Sentinel-1 images to country-wide crop classification

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

Arslan A. N. et al. (2021), Developing Support for Monitoring and Reporting of GHG Emissions and Removals from Land Use, Land Change and Forestry

This paper presents plans and efforts on European Union (EU) Member States (MSs) (including Norway and Iceland)-specific support for monitoring emissions and removals from land use, land use change and forestry (LULUCF) which are

Torralba J., Ruiz L. Á., Georgiadis C., Patias P., Gómez-Conejo R., Verde N., Tassapoulou M., Bezares Sanfelip F., Grommy E., Aleksandrowicz S., Krätzschmar E., Krupiński M., Carbonell-Rivera J. P. (2021), Methodological proposal for the identification of marginal lands with remote sensing-derived products and ancillary data

The concept of marginal land (ML) is dynamic and depends on various factors related to the environment, climate, scale,culture, and economic sector. The current methods for identifying ML are diverse, they employ multiple parameters

Grzyb T., Kulczyk S., Derek M., Woźniak E. (2021), Using social media to assess recreation across urban green spaces in times of abrupt change

For most of the world’s population, urban green spaces (UGS) offer the easiest form of contact with nature. Such environments deliver a wide variety of Recreational Ecosystem Services (RES) to visitors. This paper explores

Aleksandrowicz S., Wawrzaszek A., Drzewiecki W. Krupiński M., Jenerowicz M. (2021), Change Detection in Multispectral VHR Images Using Spatialized Hölder Exponent

Multifractals have proven to be a valuable tool in image analysis applications and remote sensing (RS). They can be used for image segmentation, texture analysis, and classification. This study explores their applicability to change

Barańska A., Bac-Bronowicz J., Dejniak D., Lewiński S., Krawczyk A., Chrobak T. (2021), A Unified Methodology for the Generalisation of the Geometry of Features

The development of generalisation (simplification) methods for the geometry of features in digital cartography in most cases involves the improvement of existing algorithms without their validation with respect to the similarity of feature geometry

Kotarba A. Z., Solecki M. (2021), Uncertainty Assessment of the Vertically-Resolved Cloud Amount for Joint CloudSat–CALIPSO Radar–Lidar Observations

The joint CloudSat–Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) climatology remains the only dataset that provides a global, vertically-resolved cloud amount statistic. However, data are affected by uncertainty that is the result of

Wawrzaszek A., Drzewiecki W., Krupiński M., Jenerowicz M., Aleksandrowicz S. (2021), Multifractal Features for Land Use Classification

In our work, we analyze multifractal parameters for the description and classification of a 2056 subsets of aerial images representing 21 land-use classes. In particular, we consider the degree of multifractality, estimated with different