Based on laboratory, field and airborne-acquired hyperspectral data, this paper aims to analyse the dominant minerals and rocks found in the Polish Karkonosze Mountains. Laboratory spectral characteristics were measured with the ASD FieldSpec 3 spectrometer and images were obtained from VITO’s Airborne Prism EXperiment (APEX) scanner. The terrain is covered mainly by lichens or vascular plants creating significant difficulties for rock identification. However, hyperspectral airborne imagery allowed for subpixel classifications of different types of granites, hornfels and mica schist within the research area. The hyperspectral data enabled geological mapping of bare ground that had been masked out using three advanced algorithms: Spectral Angle Mapper, Linear Spectral Unmixing and Matched Filtering. Though all three methods produced positive results, the Matched Filtering method proved to be the most effective. The result of this study was a set of maps and post classification statistical data of rock distribution in the area, one for each method of classification.
On January 1, 2005 the use of asbestos-containing products was banned in the European Union. According to the Act of 19 June 1997 banning the use of these products, their usage in Poland should be abated by the end of 2032. The whole process is being monitored by the Electronic Spatial Information System for the Monitoring of Asbestos Products Removal. The system design was based on a geodatabase. The research area of the study is the whole territory of Poland at the national, provincial and local level of detail. The monitoring process embraces spatial analysis through the preparation and interpretation of a range of maps. The results obtained from the deployed methods proved that the system has been useful for decision making purposes during the monitoring process. The proposed solutions were appreciated by the EU.
The goal of the paper is a presentation of field remote sensing methods for the analysis of the trampled plants of a highly protected mountain meadow ecosystem (M&B UNESCO Reserve and one of the most important Polish National Parks). The research area covers a core part of the Western Tatras - the Gąsienicowa Valley and Kasprowy Wierch summit, which are among the most visited destinations of the Polish Tatras. The research method is based on field hyperspectral measurements, using the ASD FieldSpec 3 spectrometer, on the dominant plant species of alpine swards. Sampling sites were located on trampled areas (next to trails) and reference plots, with the same species, but located more than 10 m from the trail (where the probability of trampling was very low, but the same composition of analysed plants). In each case, homogenous plots with a domination of one plant species were investigated. Based on the hyperspectral measurements, spectral characteristics as well as vegetation indices were analysed with the ANOVA statistical test. This indicated a varied resistance to trampling of the studied plant species. The analysis of vegetation indices enabled the selection of those groups which are the most useful for research into mountain vegetation condition: the broadband greenness group; the narrowband greenness group, measuring chlorophyll content and cell structure; and the canopy water content group. The results of the analyses show that vegetation of the High Tatras is characterised by optimal ranges of remote sensing indices. Only plants located nearest to the trails were in a worse condition (chlorophyll and water content was lower for the reference targets). These differences are statistically significant, but the measured values indicate a good condition of vegetation along trampled trails, within the range of optimum plant characteristics.
The unique set of physical and chemical properties of asbestos has led to its many industrial applications, such as roof coverings, textiles, rope, cord and yarn, paper, friction and composition materials, household product, acid-resistant filters, packing, insulation, and certain types of lagging, amongst others. In Poland asbestos-containing products were manufactured from raw materials imported mainly from the former Soviet Union, with production launched at the beginning of 20th century. According to Annex 4 to the Act of 19 June 1997 on the prohibition of the use of asbestos-containing products, there were 28 asbestos manufacturing plants in Poland located in 11 provinces throughout the country. The current survey was undertaken to enable asbestos manufacturing plants to be arranged, described and divided in order to contribute to further surveys.
Asbestos and asbestos containing products are harmful to human health, and therefore its use has been legally forbidden in the EU. Since there is no adequate data on the amount of asbestos-cement roofing in Poland, the objective of this study was to map asbestos-cement roofing with the use of hyperspectral APEX data (288 bands at the spatial resolution of 2.7 m) in the Karpacz area (southwest Poland). A field survey constituted the basis for training and verification polygons in the classification process. A SAM classification method was performed with the following classification results: 62% producer’s accuracy, 73% user’s accuracy and an overall accuracy of 95%. The asbestos-cement roofing for buildings may be discriminated with a high classification accuracy with the use of hyperspectral imagery. The vast majority of the classified buildings were characterised by their small area (i.e. residential type buildings), which reduced the overall accuracy of the classification.
The purpose of this article is to evaluate the possibilities of touristic development of the La Lopé National Park and to indicate the most important barriers and limitations of the area exploitation. For this purpose a SWOT method was applied. This assignment presents the situation as of the end of 2014. The majority of the up-to-date data was collected during the mission, the purpose of which was to observe the region, and which was organized by Université Omar Bongo in Libreville and Warsaw University. The La Lopé National Park has a significant touristic potential which is very poorly used. The diagnose of the reasons for that can be an indicator for attempts to rationally use the resources of the region and present an appropriate development strategy.
The paper deals with the evaluation of mountain meadow vegetation condition using in-situ measurements of the fraction of Accumulated Photosynthetically Active Radiation (fAPAR) and Leaf Area Index (LAI). The study analyses the relationship between these parameters and spectral properties of meadow vegetation and selected invasive species with the goal of finding out vegetation indices for the detection of fAPAR and LAI. The developed vegetation indices were applied on hyperspectral data from an APEX (Airborne Prism Experiment) sensor in the area of interest in the Krkonoše National Park. The results of index development on the level of the field data were quite good. The maximal sensitivity expressed by the coefficient of determination for LAI was R2 = 0.56 and R2 = 0.79 for fAPAR. However, the sensitivity of all the indices developed at the image level was quite low. The output values of in-situ measurements confirmed the condition of invasive species as better than that of the valuable original meadow vegetation, which is a serious problem for national park management.
Information about vegetation condition is needed for the effective management of natural resources and the estimation of the effectiveness of nature conservation. The aim of the study was to analyse the condition of non-forest mountain communities: synanthropic communities and natural grasslands. UNESCO’s M&B Karkonosze Transboundary Biosphere Reserve was selected as the research area. The analysis was based on 40 field test polygons and APEX hyperspectral images. The field measurements allowed the collection of biophysical parameters - Leaf Area Index (LAI), fraction of Absorbed Photosynthetically Active Radiation (fAPAR) and chlorophyll content - which were correlated with vegetation indices calculated using the APEX images. Correlations were observed between the vegetation indices (general condition, plant structure) and total area of leaves (LAI), as well as fraction of Absorbed Photosynthetically Active Radiation (fAPAR). The outcomes show that the non-forest communities in the Karkonosze are in good condition, with the synanthropic communities characterised by better condition compared to the natural communities.
This research aims to discover the potential of hyperspectral remote sensing data for mapping mountain vegetation ecosystems. First, the importance of mountain ecosystems to the global system should be stressed due to mountainous ecosystems forming a very sensitive indicator of global climate change. Furthermore, a variety of biotic and abiotic factors influence the spatial distribution of vegetation in the mountains, producing a diverse mosaic leading to high biodiversity. The research area covers the Szrenica Mount region on the border between Poland and the Czech Republic - the most important part of the Western Karkonosze and one of the main areas in the Karkonosze National Park (M&B Reserve of the UNESCO). The APEX hyperspectral data that was classified in this study was acquired on 10th September 2012 by the German Aerospace Center (DLR) in the framework of the EUFAR HyMountEcos project. This airborne scanner is a 288-channel imaging spectrometer operating in the wavelength range 0.4-2.5 μm. For reference patterns of forest and non-forest vegetation, maps (provided by the Polish Karkonosze National Park) were chosen. Terrain recognition was based on field walks with a Trimble GeoXT GPS receiver. It allowed test and validation dominant polygons of 15 classes of vegetation communities to be selected, which were used in the Support Vector Machines (SVM) classification. The SVM classifier is a type of machine used for pattern recognition. The result is a post classification map with statistics (total, user, producer accuracies, kappa coefficient and error matrix). Assessment of the statistics shows that almost all the classes were properly recognised, excluding the fern community. The overall classification accuracy is 79.13% and the kappa coefficient is 0.77. This shows that hyperspectral images and remote sensing methods can be support tools for the identification of the dominant plant communities of mountain areas.
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