landscapemetrics: an open‐source R tool to calculate landscape metrics MHK Hesselbarth, M Sciaini, KA With, K Wiegand, J Nowosad Ecography 42 (10), 1648-1657, 2019 | 258 | 2019 |
Geocomputation with R R Lovelace, J Nowosad, J Muenchow Chapman and Hall/CRC Press, 2019 | 105 | 2019 |
Information theory as a consistent framework for quantification and classification of landscape patterns J Nowosad, TF Stepinski Landscape Ecology 34 (9), 2091-2101, 2019 | 45* | 2019 |
Airborne Alternaria and Cladosporium fungal spores in Europe: Forecasting possibilities and relationships with meteorological parameters A Grinn-Gofroń, J Nowosad, B Bosiacka, I Camacho, C Pashley, ... Science of the Total Environment 653, 938-946, 2019 | 42 | 2019 |
Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset B Czernecki, J Nowosad, K Jabłońska International Journal of Biometeorology 62, 1297, 2018 | 36 | 2018 |
Global assessment and mapping of changes in mesoscale landscapes: 1992–2015 J Nowosad, TF Stepinski, P Netzel International Journal of Applied Earth Observation and Geoinformation 78 …, 2019 | 30 | 2019 |
Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula J Nowosad International Journal of Biometeorology 60 (6), 843–855, 2016 | 30 | 2016 |
Spatial association between regionalizations using the information-theoretical V-measure J Nowosad, TF Stepinski International Journal of Geographical Information Science 32 (12), 2386-2401, 2018 | 27 | 2018 |
Climate: An R Package to Access Free In-Situ Meteorological and Hydrological Datasets for Environmental Assessment B Czernecki, A Głogowski, J Nowosad Sustainability 12 (1), 394, 2020 | 23 | 2020 |
Evaluating the portability of satellite derived chlorophyll-a algorithms for temperate inland lakes using airborne hyperspectral imagery and dense surface … R Johansen, R Beck, J Nowosad, C Nietch, M Xu, S Shu, B Yang, H Liu, ... Harmful Algae 76, 35-46, 2018 | 18 | 2018 |
Temporal and spatiotemporal autocorrelation of daily concentrations of Alnus, Betula, and Corylus pollen in Poland J Nowosad, A Stach, I Kasprzyk, M Latałowa, M Puc, D Myszkowska, ... Aerobiologia 31 (2), 159-177, 2015 | 14 | 2015 |
Statistical techniques for modeling of Corylus, Alnus, and Betula pollen concentration in the air J Nowosad, A Stach, I Kasprzyk, K Chłopek, K D±browska-Zapart, ... Aerobiologia 34 (3), 301–313, 2018 | 13 | 2018 |
Global inventory of landscape patterns and latent variables of landscape spatial configuration J Nowosad, TF Stepinski Ecological Indicators 89, 159-167, 2018 | 13 | 2018 |
pollen: Analysis of aerobiological data J Nowosad R Package Version 0.71, 2019 | 10 | 2019 |
spData: Datasets for Spatial Analysis R Bivand, J Nowosad, R Lovelace R package version 0.2 7, 2018 | 10 | 2018 |
Stochastic, Empirically Informed Model of Landscape Dynamics and Its Application to Deforestation Scenarios J Nowosad, TF Stepinski Geophysical Research Letters 46 (23), 13845-13852, 2019 | 8 | 2019 |
Rcartocolor:’CARTOColors’ palettes J Nowosad | 8 | 2017 |
belg: A Tool for Calculating Boltzmann Entropy of Landscape Gradients J Nowosad, P Gao Entropy 22 (9), 937, 2020 | 7* | 2020 |
Forecasting model of Corylus, Alnus, and Betula pollen concentration levels using spatiotemporal correlation properties of pollen count J Nowosad, A Stach, I Kasprzyk, E Weryszko-Chmielewska, ... Aerobiologia 32 (3), 453-468, 2016 | 7 | 2016 |
Pattern-based identification and mapping of landscape types using multi-thematic data J Nowosad, TF Stepinski International Journal of Geographical Information Science 35 (8), 1634-1649, 2021 | 6 | 2021 |