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Korekcja geometryczna a wyniki klasyfikacji zdjec wielospektralnych

100%
Osinska-Skotak K., Fijalkowska A.
Acta Scientiarum Polonorum. Geodesia et Descriptio Terrarum
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2005
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tom 04
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nr 1
55-66
2
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Oszacowanie różnorodności gatunkowej drzewostanów z wykorzystaniem ich reflektancji

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Kotlarz J., Kubiak K., Kacprzak M., Czapski P.
Sylwan
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2016
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tom 160
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nr 12
Evaluation of the forest landscape diversity was investigated based on the multispectral aerial images using iterative Principal Component Analysis (PCA) methodology. In 2014, we carried out several photogrammetric flights over the experimental plots establish in the Krotoszyn Plateau (central Poland) documenting the vegetation cycle of forest stands dominated by oaks. Aerial photos of the spatial resolution about 25 cm of forest area in Karczma Borowa Forest District in the range of visible light (460−650 nm) and near infrared (700−930 nm) were collected by multispectral Quercus 6 platform placed on the aircraft. The aim of the study was to evaluate the diversity of forest vegetation cover using remote sensing data based on spectral signatures of plants without complete classification of fractional vegetation cover and species identification in the field. Recursive PCA on data collection from the multispectral images helped to determine with the semi−automatic mode the number of land cover classes, including the classes of vegetation. Based on the radiometric data, the separation of inorganic matter from vegetation and diversity indicators of forest stands on the image area were evaluated. With the PCA method, along the most volatile vectors, the first division into land cover classes of vegetation was conducted. As a result of the first iteration of PCA, three classes of vegetation: deciduous trees, conifers and forest undergrowth was determined. In the second iteration, classes of forest vegetation were separated and interpreted as the area dominated by a single species of tree or shrub. The second iteration divided the deciduous plant image area in plots dominated by English oak stands with an admixture of birch and red oak. Based on the number of pixels in classes representing individual plant species, Shannon−Wiener (H) and Simpson (D) diversity indices were determined. By described methodology, it was found that the differences between the H and D indices for the imagery area after the first and second PCA iteration were small. The relevance of performing successive iterations of PCA analysis, and thus the full identification of species, in the context of diversity calculation should be the subject of further study.
3

Wykorzystanie pomiarow zdalnych do oceny wiosennego porazenia roslin przez choroby

80%
Nierobca A., Pudelko R., Kozyra J., Smagacz J., Mizak K.
Progress in Plant Protection
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2007
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tom 47
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nr 4
189-192
4
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Określenie rozdzielczości przestrzennej wielospektralnych zdjęć satelitarnych optymalnej do detekcji martwych drzew na obszarach leśnych

80%
Pluto-Kossakowska J., Osinska-Skotak K., Sterenczak K.
Sylwan
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2017
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tom 161
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nr 05
The mainstream of remotely sensed methodology for identifying the tree stand condition is based on spectral responses registered by a multispectral sensor as a digital image. The changes in spectral properties are caused by dying leaves, needles or whole trees. In further steps, the relationship between the spectral values (radiometry) registered in a multispectral satellite image and the health condition of trees should be determined. The most frequent situation includes the one whem dying stand (sensu single tree) occupies the area of <5 m². Therefore the remotely sensed data for determining sanitary conditions of trees must be of a very high spatial resolution (e.g. WorldView2 or 3, GeoEye−1, Pleiades) on one hand and at the same time favourable for the vegetation studies, i.e. utilizing suitable spectral bands and be of low acquisition cost (e.g. RapidEye, LANDSAT−7, ETM +, LANDSAT−8 OLI). Thus a compromise between spatial and spectral resolution should be found to answer the question at what resolution it is possible to clearly separate the damaged tree. The scope of the research included testing of selected methods of satellite image processing and analysis in terms of defining the optimal spatial resolution, which was performed on simulated images obtained for the area of the Beskidy Mountains (S Poland). Pixel size on simulated images was downgraded to the size corresponding to the currently functioning satellite systems. Consequently the obtained material for comparison was free from influence of external factors such as the differences in: time and weather conditions, the geometry of satellite image acquisition, light at the surface of the treetops and phenological vegetation. For each image we used vegetation indices (NDVI and GDVI) and supervised classification. These tests and the obtained results allowed to draw conclusions about the optimal satellite image resolution that can be used to detect damaged or dead stands.
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