Does S2GLC 2017 map detect forests five years after regeneration?

Radosław Jagiełło, Szymon Pikulik


Land cover and use maps are great sources of generalised information. Focusing on forestry, they could be employed to assess forested areas and their changes in time. Together with advances in technology we are able to capture images with a high spatial resolution, reaching 10 m for images from satellites of the Sentinel-2 mission. Our goal was to evaluate the applicability of maps resulting from the S2GLC project (Seninel-2 Global Land Cover) in assessing forest cover of areas five years after regeneration. Sample plots (n=33) were surveyed in a conventional manner by the Forest Service to assess forest cover. Then land cover maps were referred to data from the Polish Forest Data Bank and forest cover was assessed using two different programs: ImageJ (manually) and QGIS plug-in RasterStats (automatically). Assessment conducted on site indicated 94% total forest cover on all plots taken together. Both programs based on the data from the maps showed a lower forest cover amounting to 71 and 73%, respectively. In turn, RastrStats classified many more pixels than had been expected and a potential source of error was here discussed. Forest juvenile phases may be partially misinterpreted and classified on land cover maps also as marshes, peatbogs, herbaceous vegetation or cultivated areas. Hence, when areas after reforestation are defined as forest, land cover map used here may to some extent underestimate the actual area covered by forests. 


forest regeneration, ImageJ, land cover, land use, optical satellites, RasterStats

Full Text:



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 57:1–20. doi: 10.1080/15481603.2019.1650447

Bork, E.W., Su, J.G, (2007). Integrating LIDAR data and multispectral imagery for enhanced classification of rangeland vegetation: A meta analysis. Remote Sensing of Environment 111: 11-24. doi: 10.1016/j.rse.2007.03.011

Dean, A., Voss, D., Draguljić, D. (2017). Checking Model Assumptions. In: Design and Analysis of Experiments, 2nd edn. Springer International Publishing, Cham, pp. 103–137

Defries, R.S., Townshend, J.R.G. (1994). NDVI-derived land cover classifications at a global scale. International Journal of Remote Sensing 15:3567–3586. doi: 10.1080/01431169408954345

Di Gregorio, A., Lansen, L.J.M. (2000). Land Cover Classification System (LCCS): Classification Concepts and User Manual. Food and Agriculture Organisation of United Nations: (accessed on 4 March 2021).

Drusch, M., Del Bello, U., Carlier, S., et al. (2012). Sentinel-2: ESA’s Optical High-Resolution Mission for GMES Operational Services. Remote Sensing of Environment 120: 25–36. doi: 10.1016/j.rse.2011.11.026

Forestry (2020). Statistical Yearbook of Forestry 2020. Statistics Poland, Warsaw.

Gascon, F., Bouzinac, C., Thépaut, O., et al. (2017). Copernicus Sentinel-2A Calibration and Products Validation Status. Remote Sensing 9(6): 584. doi: 10.3390/rs9060584

GFRA (2018). Global Forest Resources Assessment 2020. Guidelines and specifications. Version 1.0. Forest resources assessment working paper 189. Food and Agriculture Organization of the United Nations: (accessed n 16 March 2021).

HRL (2021). Forest 2018 Product User Manual. European Union, Copernicus Land Monitoring Service 2021, European Environment Agency (EEA): (accessed on 4 March 2021).

Jagodziński, A.M., Dyderski, M.K., Gęsikiewicz, K., et al. (2018). How do tree stand parameters affect young Scots pine biomass? – Allometric equations and biomass conversion and expansion factors. Forest Ecology and Management 409: 74–83. doi: 10.1016/j.foreco.2017.11.001

Malinowski, R., Lewiński, S., Rybicki, M., et al. (2020). Automated Production of a Land Cover/Use Map of Europe Based on Sentinel‐2 Imagery. Remote Sensing 12: 1–27. doi: 10.3390/rs12213523

Næsset, E. (2005). Assessing sensor effects and effects of leaf-off and leaf-on canopy conditions on biophysical stand properties derived from small-footprint airborne laser data. Remote Sensing of Environment 98: 356-370. doi: 10.1016/j.rse.2005.07.012

Pitt, D. G., Wagner, R. G., Hall, R. J., King, D. J., Leckie, D. G., Runesson, U. (1997). Use of remote sensing for forest vegetation management: A problem analysis. Forestry Chronicle 73(4), 459–477.QGIS Development Team (2021). QGIS Geographic Information System. Open Source Geospatial Foundation Project.

Sader, S.A., Jin, S., Metzler, J.W., Hoppus, M. (2006). Exploratory analysis of forest harvest and regeneration pattern among multiple landowners. The Forestry Chronicle 82 (2): 203-210. doi: 10.5558/tfc82203-2

Sader, S.A., Legaard, K.R. (2008). Inclusion of forest harvest legacies, forest type, and regeneration spatial patterns in updated forest maps: A comparison of mapping results. Forest Ecology and Management 225(11): 3846-3856. doi: 10.1016/j.foreco.2008.03.047

Schneider, C.A., Rasband, W.S., Eliceiri, K.W. (2012). NIH Image to ImageJ: 25 years of image analysis. Nature Methods 9: 671–675. doi: 10.1038/nmeth.2089

Silviculture Principles (2012). Zasady hodowli lasu. Centrum Informacyjne Lasów Państwowych, Warszawa. (in Polish)

Socha, J., Pierzchalski, M., Bałazy, R., Ciesielski, M. (2017). Modelling top height growth and site index using repeated laser scanning data. Forest Ecology and Management 406: 307–317. doi: 10.1016/j.foreco.2017.09.039

SSA (2020). Speaker of the Sejm Announcement from 22 July 2020 concerning announcement of consolidated text of Forest Law Act of 28 September 1991: (accessed on 16 March 2021).

Townshend, J.R., Masek, J.G., Huang, C., et al. (2012). Global characterization and monitoring of forest cover using Landsat data: opportunities and challenges. International Journal of Digital Earth 5: 373–397. doi: 10.1080/17538947.2012.713190

Walker, W.S., Stickler, C.M., Kellendorfer, J.M., Kirsch, K.M., Nepstad, D.C. (2010). Large-Area Classification and Mapping of Forest and Land Cover in the Brazilian Amazon: A Comparative Analysis of ALOS/PALSAR and Landsat Data Sources. IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing 3(4): 594-604.

Wulder, M.A., Hermosilla, T., Stinson, G., Gougeon, F.A., White, J.C., Hill, D.A., Smiley, B.P. (2020). Satellite-based time series land cover and change information to map forest area consistent with national and international reporting requirements. Forestry 93: 331-343. doi: 10.1093/forestry/cpaa006

Forestry Letters  eISSN 2450-4920

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we'll assume that you are happy to receive all cookies from this website. If you would like to change your preferences you may do so by following the instructions here