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EN
Due to the observed impacts of climate change on the natural environment, the demand for energy from renewable sources is growing, especially in the last decades. One of the possibilities in this respect is the use of forest biomass, especially that one which comes from logging residues. This type of wood raw material is obtained primarily in mature forests and during late thinnings. Estimation of the expected volume of logging residues from a particular cutting site is currently carried out in the State Forests, National Forest Holding with an accuracy oscillating at an acceptable level of ±40%. The purpose of this study was to estimate the share of logging residues in the total volume of the harvested biomass and to determine the difference and error between the estimated volume to be sold and actually harvested. The research was carried out at the 164 logging sites located in 10 forest districts of north−eastern part of Poland. The average volume of logging residues was 37.7 ±14.4 m³/ha, and the average error of their estimation was –6.1%.
EN
The study presents the results on the dynamics and structure of the litter fall in the beech stand in two years (1995 - seed year and 1996 - barren year) overgrowing the northern slopes of the "Góra Chełmowa" located in Ojców National Park in two fertility variants. The total litter fall mass during the seed year was on average 4067.3 kg/1 ha and was different by 1260.15 kg from the results obtained during the following year. The greatest part of the litter fall are leaves, which make about 67.6% of the litter fall mass during the seed year and as much as 95.9% in the following year. The fertile habitat had a stimulating effect on the litter fall biomass production such as leaves, seeds, and seed cupules.
EN
The role of image classification based on multi-source, multi-temporal and multi-resolution remote sensed data is on the rise in the environmental studies due to the availability of new satellite sensors, easier access to aerial orthoimages and the automation of image analysis algorithms. The remote sensing technology provides accurate information on the spatial and temporal distribution of land use and land cover (LULC) classes. The presented study focuses on LULC change dynamics (especially secondary forest succession) that occurred between 1974 and 2010 in the Błędów Desert (an area of approx. 1210 ha; a unique refuge habitat – NATURA 2000; South Poland). The methods included: photointerpretation and on-screen digitalization of KH-9 CORONA (1974), aerial orthoimages (2009) and satellite images (LANDSAT 7 ETM+, 1999 and BlackBridge – RapidEye, 2010) and GIS spatial analyses. The results of the study have confirmed the high dynamic of the overgrowth process of the Błędów Desert by secondary forest and shrub vegetation. The bare soils covered 19.3% of the desert area in 1974, the initial vegetation and bush correspondingly 23.1% and 30.5%. In the years 2009/2010 the mentioned classes contained: the bare soils approx. 1.1%, the initial vegetation – 8.7% and bush – 15.8%. The performed classifications and GIS analyses confirmed a continuous increase in the area covered by forests, from 11.6% (KH-9) up to 24.2%, about 25 years later (LANDSAT 7) and in the following 11 years, has shown an increase up to 35.7% (RapidEye 2010).
EN
Land Use and Land Cover (LULC) maps play an important role in an environmental modelling, and for many years efforts have been made to improve and streamline the expensive mapping process. The aim of the study was to create LULC maps of three selected water catchment areas in South Poland using a Geographic Object-Based Image Analysis (GEOBIA) in order to highlight the advantages of this innovative, semi-automatic method of image analysis. The classification workflow included: multi-stage and multi-scale analyses based on a data fusion approach. Input data consisted mainly of BlackBridge (RapidEye) high resolution satellite imagery, although for distinguishing particular LULC classes, additional satellite images (LANDSAT TM5) and GIS-vector data were used. Accuracy assessment of GEOBIA classification results varied from 0.83 to 0.87 (Kappa), depending on the specific catchment area. The main recognized advantages of GEOBIA in the case study were: performing of multi-stage and multi-scale image classification using different features for specific LULC classes and the ability to using knowledge-based classification in conjunction with the data fusion approach in an efficient and reliable manner.
EN
Presented research investigates the possibility of applying the newest, free available satellite images Sentinel−2 for the automation of land use/cover (LULC) mapping in reclaimed areas, mainly in the aspect of monitoring forested areas. The study was performed for the former sulphur mines: ‘Machów’ (871.7 ha of the dump area after the opencast strip mine) and ‘Jeziórko’ (216.5 ha of the afforested area after the borehole exploitation). These areas are characterized by a diverse terrain structure and vegetation cover as the result of reclamation. The applied directions of reclamation were agro−forestry for the Sulphur Mine ‘Machów’ and forestry for the Sulphur Mine ‘Jeziórko’. We verified whether processing of Sentinel−2 data allows for reliable LULC classification – mainly identification forested areas in relation to the LULC mapping prepared by manual vectorization of orthophotomaps. Obtained classification results for Sentinel−2 data were also compared to the results of Landsat 8 images processing. The results of Sentinel−2 images classification showed correct graphical representation of the LULC classes, especially forested areas, in the relation to the results of applied on−screen vectorization of aerial orthophotomaps – better than results of the Landsat 8 images processing. The area of the mail class ‘Forests’ as a result of classification Sentinel−2 and Landsat 8 images compared to the results of manual on−screen vectorization of the orthophomaps shows differences: 5.4% – Sentinel−2, 12.8% – Landsat 8 for Sulphur Mine ‘Machów’ and 1.8% – Sentinel−2, 8.8% – Landsat 8 for Sulphur Mine ‘Jeziórko’. Research indicates the possibility of automation of LULC classification using Sentinel−2 images. It could be very useful for LULC changes monitoring in reclaimed areas, mainly in the aspect of forested areas mapping as a result of way of reclamation.
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