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Information on the spatial distribution and variability of forests is important in monitoring of forest resources, biodiversity assessment, threat prevention, estimation of carbon content and forest management. The Pan−European High Resolution Layers (HRLs) produced as part of the European Earth Monitoring Programme – Copernicus provide detailed information on the land cover characteristics in Europe. The HRLs are produced using satellite imagery based on an interactive rule−based classification. There are the following HRL themes: imperviousness, forest, water and wetness and grasslands. The HRLs are available for the reference year 2012 and 2015, at the spatial resolution of 20 m. The forest related HRL consists of tree cover density, dominant tree type and forest type products. In this study, we performed a) the qualitative and quantitative analysis of the accuracy of the dominant leaf type (DLT) layer for the 2015 year at the national scale, and b) detailed analysis of the data quality at the forest stand level over the selected forest districts. The DLT layer was compared with the national orthophotos. The detailed analysis was carried out using Sentinel−2 images and forest inventory data obtained from the Forest Data Bank over the selected forest districts. The accuracy analysis of the national DLT layer revealed the high omission error equal to 18.8%, and lower commission error of 5.4%. The omission error is mostly related to the omitted orchards and young forest plantations, which are included in the DLT layer. The commission error of the broadleaved forest is related mostly to the small patches of coniferous forest that was misclassified as broadleaved. In general, commission errors were identified more frequently in broadleaved forest than in the coniferous forest. In many locations the patches of coniferous forest were misclassified as broadleaved forest. In general, the area of the broadleaved forest is overestimated., Sylwan 164 (2): 151-160

Extreme weather events such as hurricanes, floods or fires become more and more common phenomena in Europe. In August 2017, strong wind accompanied by heavy thunderstorms caused severe damage over the large area in central and western Poland. According to rapid damage assessment prepared by the State Forests authorities a few days after the windthrow, ca 79.7 thousand hectares of forest was damaged and 9.8 million of cubic meters of wood was lost. Assessment of such a large−scale forest damage is difficult without using the remote sensed data. In this study, we examined the potential of the European satellite Sentinel−2 data for assessment of the forest damage caused by the windthrow. The assessment was performed using a difference between a normalized difference moisture index (NDMI) calculated based on the pre− and post−damage Sentinel−2 images. NDMI was calculated based on NIR (824 nm) and SWIR (1610 nm) bands. The result of this study showed the total damage area in forest is equal to 35.8 thousand hectares, of which 27.7 thousand hectares was damaged within the State Forests and 8.1 thousand hectares outside the State Forests administration. These figures are much lower than the estimates by the State Forests, regarding the forest damage within the State Forests and higher comparing to estimations in the non−state forest. In fact, these figures are comparable with the heavily damage areas assigned to clearance by the State Forests. The accurate comparison of the results was not possible due to the lack of up−to−date information on forest damage. Sentinel−2 data revealed to be perfect data for large scale damage assessment and postdamage forest monitoring mainly due to the wide swath up to 290 km. The limitation of the optical sensors is the cloudiness. Unfortunately, in the case of this analysis, the first cloud free image was acquired 6 weeks after the windthrow. It reduces the potential of the single−source data for rapid assessment of damages., Sylwan 162 (8): 619-627

Geoinformation Issues, 2018, Vol. 10, No 1(10), pages 53-64, The techniques of converting stereo-pair aerial photographs or satellite images are used to prepare the digital surface models (DSM), digital elevation models (DEM) or to obtain the height of the objects. Recently, the Copernicus Land Monitoring service released a product presenting the building heights for the major – capital cities in Europe. The Building Height 2012 layer was derived based on the stereo images acquired by the IRS-5 satellite close to the defined reference year 2012. The main aim of the study was to examine the accuracy of the Copernicus Building Height 2012 layer in comparison with the building height derived from airborne laser scanning system. The study was carried out over the city of Warsaw (the capital of Poland). In general, data from both datasets are compatible, however the overestimation of the height was observed. The comparison carried out in two ways produced similar results. On average, the overestimation of the satellite-based building height for the study area reached 1.08 m.

Geoinformation Issues, 2017, Vol. 9, No 1(9), pages 27-38, The knowledge on forest resources is important for sustainable forest management at local and national level. The aim of this paper is to examine the efficacy of the Support Vector Machine (SVM) approach for tree cover mapping based on Sentinel-2 images and to explore the potential of the Sentinel-2 data for the assessment of tree cover. Sentinel-2 is a constellation of two European satellites providing innovative wide-swath (up to 290 km), high-resolution and multispectral data (13 spectral bands at 10, 20 and 60 m spatial resolution).The study area is located in the Forest Promotion Complex, which is a part of the Knyszyn Forest Landscape Park in Poland. The SVM classification was performed on the single images (spring and summer season) and on multi-date Sentinel-2 images (images from two dates classified simultaneously). In addition, the use of high-resolution bands and a combination of the 10 m and 20 m spatial resolution data was examined. The overall accuracy for all performed classification was very high and reached the level of 96.7%–99.6%, which con-firms that SVM classification can be successfully applied for tree cover mapping. The analysis showed that the Sentinel-2 images acquired in the middle of the vegetation season, when the leaves are fully developed are more suitable for tree cover mapping than the images acquired in spring.

Several studies discussed a disagreement concerning forest extent in Poland between land cadaster and status on the ground. The aim of the paper was to assess the actual forest extent in Poland based on an existing spatial datasets such as: Digital Forest Map (covering explicitly the State Forests), Topographic Database, Database of Parcel Identification System, High Resolution Layer (Copernicus Land Monitoring product based on classification of satellite data) and National Forest Data Bank. The geospatial data analyses were preceded by an accuracy assessment of the available datasets, which allowed to assign weights to each of the dataset. The result of this project was the actual forest extent map, which refers to the national definition of forest as defined in the Forest Act of 28 September 1991 (forest by definition is a homogeneous area of 0.1 hectares). This includes all forms of ownership forests and areas that are forested, but officially recorded as non−forest. Moreover, the map of the forest extent under the Kyoto Protocol, including areas that meet the criteria of actual forest extent map and additionally forest areas designed or used for housing, recreation, infrastructure, and other industrial and agricultural areas (e.g.: permanent crops – orchards) were determined. The results confirmed that the actual forest extent is higher by almost 800 thousand hectares then the official statistics provided by the Central Statistical Office of Poland. According to the official statistics forest in Poland covers 29.4% of the country, however this study revealed that 32% of the country, considering the national forest definition, and 33.5%, considering the forest definition under the Kyoto Protocol, is occupied by forest. It showed the need for the land cadaster update. Precise information on spatial distribution of forest extent is crucial for the national purposes i.e. reporting, implementation of the National Afforestation Program and also for the international commitments under the climate convention to determine the accurate forest carbon content and carbon dioxide sequestration., Sylwan 160 (8): 627-634