References
- Abdi A.M., 2020. Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data. GIScience & Remote Sensing, 57(1), Article 1, https://doi.org/10.1080/15481603.2019.1650447.
- Alonso F., Martínez-Hernández C., Díaz A., Cánovas-García F., Castillo F., 2015. Main Environmental Features Leading to Recent Land Abandonment in Murcia Region (Southeast Spain). Land Degradation & Development, 27, https://doi.org/10.1002/ldr.2447.
- Anguiano E., Bamps C., Terres J., Pointereau P., Coulon F., Girard P., Lambotte M., Stuczynski T., Sanchez O.V., Del R.A., 2008. Analysis of Farmland Abandonment and the Extent and Location of Agricultural Areas that are Actually Abandoned or are in Risk to be Abandoned. JRC Publications Repository, https://publications.jrc.ec.europa.eu/repository/handle/JRC46185.
- Aybar C., Ysuhuaylas L., Loja J., Gonzales K., Herrera F., Bautista L., Yali R., Flores A., Diaz L., Cuenca N., Espinoza W., Prudencio F., Llactayo V., Montero D., Sudmanns M., Tiede D., Mateo-García G., Gómez-Chova L., 2022. CloudSEN12, a global dataset for semantic understanding of cloud and cloud shadow in Sentinel-2. Scientific Data, 9(1), 782, https://doi.org/10.1038/s41597-022-01878-2.
- Barnes E., Clarke T.R., Richards S.E., Colaizzi P., Haberland J., Kostrzewski M., Waller P., Choi C., Riley E., Thompson T.L., 2000. Coincident detection of crop water stress, nitrogen status, and canopy density using ground based multispectral data. 15 pp. Proceedings of the Fifth International Conference on Precision Agriculture.
- Bell S.M., Barriocanal C., Terrer C., Rosell-Melé A., 2020. Management opportunities for soil carbon sequestration following agricultural land abandonment. Environmental Science & Policy, 108: 104-111, https://doi.org/10.1016/j.envsci.2020.03.018.
- Bucha T., Papčo J., Sačkov I., Pajtík J., Sedliak M., Barka I., Feranec J., 2021. Woody Above-Ground Biomass Estimation on Abandoned Agriculture Land Using Sentinel-1 and Sentinel-2 Data. Remote Sensing, 13(13), Article 13, https://doi.org/10.3390/rs13132488.
- CAP 2023-27–European Commission. https://agriculture.ec.europa.eu/common-agricultural-policy/cap-overview/cap-2023-27_en (accessed 2024, September 13).
- Collier M., 2018. Farmland abandonment in Europe: An overview of drivers, consequences and assessment of the sustainability implications. https://doi.org/10.1139/er-2018-0001#.W3HYqi3MyrP.
- Congedo L., 2021. Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS. The Journal of Open Source Software, 6, 3172, https://doi.org/10.21105/joss.03172.
- Dara A., Baumann M., Kuemmerle T., Pflugmacher D., Rabe A., Griffiths P., Hölzel N., Kamp J., Freitag M., Hostert P., 2018. Mapping the timing of cropland abandonment and re-cultivation in northern Kazakhstan using annual Landsat time series. Remote Sensing of Environment, 213: 49-60, https://doi.org/10.1016/j.rse.2018.05.005.
- Directive–2018/2001–EN - EUR-Lex. (n.d.). https://eur-lex.europa.eu/eli/dir/2018/2001/oj (accessed 20 September 2024.
- Eco-schemes–European Commission. (2024, February 13). https://agriculture.ec.europa.eu/common-agricultural-policy/income-support/eco-schemes_en.
- Elbersen B.S., Beaufoy G., Jones G., Noij I., Breman B.C., Hazeu G.W., 2014. Aspects of data on diverse relationships between agriculture and the environment.
- Estel S., Kuemmerle T., Alcántara C., Levers C., Prishchepov A., Hostert P., 2015. Mapping farmland abandonment and recultivation across Europe using MODIS NDVI time series. Remote Sensing of Environment, 163: 312-325, https://doi.org/10.1016/j.rse.2015.03.028.
- Falińska K., 1997. Ekologia roślin. Wydawnictwo Naukowe PWN.
- Foody G.M., 2002. Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80(1): 185-201, https://doi.org/10.1016/S0034-4257(01)00295-4.
- Geoportal.gov.pl. (n.d.). https://mapy.geoportal.gov.pl/imap/Imgp_2.html?gpmap=gp0 (accessed 20 September 2024).
- Gitelson A.A., Merzlyak M.N., 1998. Remote sensing of chlorophyll concentration in higher plant leaves. Advances in Space Research, 22(5), Article 5, https://doi.org/10.1016/S0273-1177(97)01133-2.
- Goga T., Feranec J., Bucha T., Rusnák M., Sačkov I., Barka I., Kopecká M., Papčo J., Oťaheľ J., Szatmári D., Pazúr R., Sedliak M., Pajtík J., Vladovič J., 2019. A Review of the Application of Remote Sensing Data for Abandoned Agricultural Land Identification with Focus on Central and Eastern Europe. Remote Sensing, 11(23), Article 23, https://doi.org/10.3390/rs11232759.
- Grabska-Szwagrzyk E., Tiede D., Sudmanns M., Kozak J., 2024. Map of forest tree species for Poland based on Sentinel-2 data. Earth System Science Data, 16(6): 2877-2891, https://doi.org/10.5194/essd-16-2877-2024.
- Grădinaru S.R., Kienast F., Psomas A., 2019. Using multi-seasonal Landsat imagery for rapid identification of abandoned land in areas affected by urban sprawl. Ecological Indicators, 96Ł 79+86. https://doi.org/10.1016/j.ecolind.2017.06.022
- Gutman G., Radeloff V. C. (Eds.)., 2017. Land-Cover and Land-Use Changes in Eastern Europe after the Collapse of the Soviet Union in 1991. Springer.
- Hansen P.M., Schjoerring J.K., 2003. Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression. Remote Sensing of Environment, 86(4): 542–553, https://doi.org/10.1016/S0034-4257(03)00131-7.
- Hawryło P., Bednarz B., Wężyk P., Szostak M., 2018. Estimating defoliation of Scots pine stands using machine learning methods and vegetation indices of Sentinel-2. European Journal of Remote Sensing, 51(1), Article 1, https://doi.org/10.1080/22797254.2017.1417745.
- Hejmanowska B., Wężyk P. (Eds.), 2020. Dane satelitarne dla administracji publicznej. e-ISBN: 978-83-945436-3-1, https://polsa.gov.pl/wp-content/themes/polsa/files/Podrecznik.pdf
- Herrmann I., Pimstein A., Karnieli A., Cohen Y., Alchanatis V., Bonfil D.J., 2011. LAI assessment of wheat and potato crops by VENμS and Sentinel-2 bands. Remote Sensing of Environment, 115(8): 2141-2151, https://doi.org/10.1016/j.rse.2011.04.018.
- Hijmans R.J., 2020. terra: Spatial Data Analysis. R apckage version 1.7-78. https://doi.org/10.32614/CRAN.package.terra.
- Huete A., Didan K., Miura T., Rodriguez E.P., Gao X., Ferreira L.G., 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83(1–2), Article 1–2, https://doi.org/10.1016/S0034-4257(02)00096-2.
- Huete A.R., 1988. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), Article 3, https://doi.org/10.1016/0034-4257(88)90106-X.
- IDB - Index DataBase. (n.d.). https://www.indexdatabase.de/ (accessed 21 August 2024).
- Jabs-Sobocińska Z., Affek A.N., Ewiak I., Nita M.D., 2021. Mapping Mature Post-Agricultural Forests in the Polish Eastern Carpathians with Archival Remote Sensing Data. Remote Sensing, 13(10), Article 10, https://doi.org/10.3390/rs13102018.
- Janus J., Bożek P., 2019. Land abandonment in Poland after the collapse of socialism: Over a quarter of a century of increasing tree cover on agricultural land. Ecological Engineering, 138: 106-117, https://doi.org/10.1016/j.ecoleng.2019.06.017.
- Kolecka N., 2018. Height of Successional Vegetation Indicates Moment of Agricultural Land Abandonment. Remote Sensing, 10(10), Article 10, https://doi.org/10.3390/rs10101568.
- Kolecka N., 2021. Greening trends and their relationship with agricultural land abandonment across Poland. Remote Sensing of Environment, 257, 112340, https://doi.org/10.1016/j.rse.2021.112340.
- Kolecka N., Kozak J., 2019. Wall-to-Wall Parcel-Level Mapping of Agricultural Land Abandonment in the Polish Carpathians. Land, 8(9), Article 9, https://doi.org/10.3390/land8090129.
- Kolecka N., Kozak J., Kaim D., Dobosz M., Ostafin K., Ostapowicz K., Wężyk P., Price B., 2017. Understanding farmland abandonment in the Polish Carpathians. Applied Geography, 88: 62–72, https://doi.org/10.1016/j.apgeog.2017.09.002.
- Kozak M., Pudełko R., 2021. Impact assessment of the long-term fallowed land on agricultural soils and the possibility of their return to agriculture. Agriculture, 11(2), Article 2, https://doi.org/10.3390/agriculture11020148.
- Kruskal W.H., 1952. A Nonparametric test for the Several Sample Problem. The Annals of Mathematical Statistics, 23(4): 525-540, https://doi.org/10.1214/aoms/1177729332.
- Kruskal W.H., Wallis W.A., 1952. Use of Ranks in One-Criterion Variance Analysis. Journal of the American Statistical Association, 47(260): 583-621, https://doi.org/10.1080/01621459.1952.10483441.
- Krysiak S., 2011. Fallow lands in the landscapes of central Poland–Spatial, typological and ecological aspects (6–1). XXXI(6–1), Article 6–1.
- Lasanta T., Nadal-Romero E., Arnáez J., 2015. Managing abandoned farmland to control the impact of re-vegetation on the environment. The state of the art in Europe. Environmental Science & Policy, 52: 99-109, https://doi.org/10.1016/j.envsci.2015.05.012
- Macintyre P., van Niekerk A., Mucina L., 2020. Efficacy of multi-season Sentinel-2 imagery for compositional vegetation classification. International Journal of Applied Earth Observation and Geoinformation, 85, 101980, https://doi.org/10.1016/j.jag.2019.101980.
- Matyka M., Radzikowski P., 2020. Productivity and Biometric Characteristics of 11 Varieties of Willow Cultivated on Marginal Soil. Agriculture, 10(12), Article 12. https://doi.org/10.3390/agriculture10120616.
- Morell-Monzó S., Estornell J., Sebastiá-Frasquet M.-T., 2020. Comparison of Sentinel-2 and High-Resolution Imagery for Mapping Land Abandonment in Fragmented Areas. Remote Sensing, 12(12), Article 12, https://doi.org/10.3390/rs12122062.
- Pudełko R., Kozak M., Jędrejek A., Gałczyńska M., Pomianek B., 2018. Regionalisation of unutilised agricultural area in Poland. Polish Journal of Soil Science, 51(1), Article 1, https://doi.org/10.17951/pjss.2018.51.1.119.
- Queiroz C., Beilin R., Folke C., Lindborg R., 2014. Farmland abandonment: Threat or opportunity for biodiversity conservation? A global review. Frontiers in Ecology and the Environment, 12(5): 288-296, https://doi.org/10.1890/120348.
- Ranghetti L., Boschetti M., Nutini F., Busetto L., 2020. “sen2r”: An R toolbox for automatically downloading and preprocessing Sentinel-2 satellite data. Computers & Geosciences, 139, 104473, https://doi.org/10.1016/j.cageo.2020.104473.
- Rouse J.W., Haas R.H., Schell J.A., Deering D.W., 1974. Monitoring vegetation systems in the Great Plains with ERTS. Paper A 20, https://ntrs.nasa.gov/citations/19740022614.
- Sentinel-2. (n.d.). https://sentiwiki.copernicus.eu/web/sentinel-2 (accessed 20 September 2024).
- Shahbandeh M., Kaim D., Kozak J., 2022. The Substantial Increase of Forest Cover in Central Poland Following Extensive Land Abandonment: Szydłowiec County Case Study. Remote Sensing, 14(16), Article 16, https://doi.org/10.3390/rs14163852.
- Sosnowska A.J., 2019. Changes of vegetation effects in soil properties in the post-agriculture landscapes (south-eastern Poland). Miscellanea Geographica, 23(1), Article 1, https://doi.org/10.2478/mgrsd-2018-0032.
- Stolarski M.J., Dudziec P., Olba-Zięty E., Stachowicz P., Krzyżaniak M., 2022. Forest Dendromass as Energy Feed-stock: Diversity of Properties and Composition Depending on Systematic Genus and Organ. Energies, 15(4), Article 4, https://doi.org/10.3390/en15041442.
- Stolarski M.J., Rosenqvist H., Krzyżaniak M., Szczukowski S., Tworkowski J., Gołaszewski J., Olba-Zięty E., 2015. Economic comparison of growing different willow cultivars. Biomass and Bioenergy, 81: 210-215, https://doi.org/10.1016/j.biombioe.2015.07.002.
- Stolarski M.J., Stachowicz P., Sieniawski W., Krzyżaniak M., Olba-Zięty E., 2021. Quality and Delivery Costs of Wood Chips by Railway vs. Road Transport. Energies, 14(21), Article 21, https://doi.org/10.3390/en14216877.
- Stolarski M.J., Szczukowski S., Krzyżaniak M., Tworkowski J., 2020. Energy Value of Yield and Biomass Quality in a 7-Year Rotation of Willow Cultivated on Marginal Soil. Energies, 13(9), Article 9, https://doi.org/10.3390/en13092144.
- Stolarski M., Niksa D., Krzyżaniak M., Tworkowski J., Szczukowski S., 2019. Willow productivity from small- and large-scale experimental plantations in Poland from 2000 to 2017. Renewable and Sustainable Energy Reviews, 101: 461-475, https://doi.org/10.1016/j.rser.2018.11.034.
- Stuczynski T., Siebielec G., Korzeniowska-Puculek R., Koza P., Pudelko R., Lopatka A., Kowalik M., 2009. Geographical location and key sensitivity issues of post-industrial regions in Europe. Environmental Monitoring and Assessment, 151(1): 77–91, https://doi.org/10.1007/s10661-008-0251-4.
- Study of conditions and directions of spatial development. (n.d.). Pulawy commune. https://gminapulawy.pl/studium-uwarunkowan-i-kierunkow-zagospodarowania-przestrzennego/ (accessed 20 September 2024).
- Suziedelyte Visockiene J., Tumeliene E., Maliene V., 2019. Analysis and identification of abandoned agricultural land using remote sensing methodology. Land Use Policy, 82: 709-715, https://doi.org/10.1016/j.landusepol.2019.01.013.
- Szatmári D., Kopecka M., Feranec J., Goga T., 2018. Abandoned agricultural land mapping using Sentinel-2A data.
- Szirmai O., Saláta D., Benedek L.K., Czóbel S., 2022. Investigation of the Secondary Succession of Abandoned Areas from Different Cultivation in the Pannonian Biogeographic Region. Agronomy, 12(4), Article 4, https://doi.org/10.3390/agronomy12040773.
- Szostak M., Hawryło P., Piela D., 2018. Using of Sentinel-2 images for automation of the forest succession detection. European Journal of Remote Sensing, 51(1), Article 1, https://doi.org/10.1080/22797254.2017.1412272.
- Szostak M., Wężyk P., Hawryło P., Puchała M., 2016. Monitoring the Secondary Forest Succession and Land Cover/Use Changes of the Błędów Desert (Poland) Using Geospatial Analyses. Quaestiones Geographicae, 35(3): 1-13, https://doi.org/10.1515/quageo-2016-0022.
- The Agricultural Census 2020. (n.d.). https://bdl.stat.gov.pl/bdl/dane/podgrup/temat (accessed 26 September 2024).
- Thompson C.N., Guo W., Sharma B., Ritchie G.L., 2019. Using Normalized Difference Red Edge Index to Assess Maturity in Cotton. Crop Science, 59(5): 2167–2177, https://doi.org/10.2135/cropsci2019.04.0227.
- Toure S.I., Stow D.A., Shih H., Weeks J., Lopez-Carr D., 2018. Land cover and land use change analysis using multi-spatial resolution data and object-based image analysis. Remote Sensing of Environment, 210: 259-268, https://doi.org/10.1016/j.rse.2018.03.023.
- Trystuła A., Konieczna J., 2008. Land parcel management system in Poland and a case study of EU member states. Geodetski Vestnik, 62(04): 630–640, https://doi.org/10.15292/geodetski-vestnik.2018.04.630-640.
- Tumelienė E., Visockienė J.S., Malienė V., 2021. The Influence of Seasonality on the Multi-Spectral Image Segmentation for Identification of Abandoned Land. Sustainability, 13(12), Article 12, https://doi.org/10.3390/su13126941.
- Von Cossel M., Lewandowski I., Elbersen B., Staritsky I., Van Eupen M., Iqbal Y., Mantel S., Scordia D., Testa G., Cosentino S.L., Maliarenko O., Eleftheriadis I., Zanetti F., Monti A., Lazdina D., Neimane S., Lamy I., Ciadamidaro L., Sanz M., Alexopoulou E., 2019. Marginal Agricultural Land Low-Input Systems for Biomass Production. Energies, 12(16), Article 16, https://doi.org/10.3390/en12163123.
- Wakulińska M., Marcinkowska-Ochtyra A., 2020. Multi-Temporal Sentinel-2 Data in Classification of Mountain Vegetation. Remote Sensing, 12(17), Article 17, https://doi.org/10.3390/rs12172696.
- Yin H., Prishchepov A.V., Kuemmerle T., Bleyhl B., Buchner J., Radeloff V.C., 2018. Mapping agricultural land abandonment from spatial and temporal segmentation of Landsat time series. Remote Sensing of Environment, 210: 12–24, https://doi.org/10.1016/j.rse.2018.02.050.
- Yusoff N.M., Muharam F.M., Takeuchi W., Darmawan S., Abd Razak M.H., 2017. Phenology and classification of abandoned agricultural land based on ALOS-1 and 2 PALSAR multi-temporal measurements. International Journal of Digital Earth, 10(2): 155–174, https://doi.org/10.1080/17538947.2016.1216615.
- Zhu X., Xiao G., Zhang D., Guo L., 2021. Mapping abandoned farmland in China using time series MODIS NDVI. Science of The Total Environment, 755, 142651, https://doi.org/10.1016/j.scitotenv.2020.142651.