DC pole | Wartość | Język |
dc.contributor.author | Bzdęga, Katarzyna | - |
dc.contributor.author | Zarychta, Adrian | - |
dc.contributor.author | Urbisz, Alina | - |
dc.contributor.author | Szporak-Wasilewska, Sylwia | - |
dc.contributor.author | Ludynia, Michał | - |
dc.contributor.author | Fojcik, Barbara | - |
dc.contributor.author | Tokarska-Guzik, Barbara | - |
dc.date.accessioned | 2020-12-18T11:57:00Z | - |
dc.date.available | 2020-12-18T11:57:00Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | "Ecological Indicators" (2021), vol. 121, art. no. 107204, s. 1-21. | pl_PL |
dc.identifier.issn | 1470-160X | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12128/17888 | - |
dc.description.abstract | The general trend of ongoing plant invasion and the increasing number of species that may become invasive in
the future, force seeking solutions that can improve the efficiency and economy of their management. Thus, we
applied a novel approach combining the use of geostatistical interpolators such as ordinary kriging (OK) and cokriging
(CK) with environmental and hyperspectral data to evaluate the potential threat associated with the
distribution of invasive plant species and to predict their probabilities of occurrence above the selected threshold
of 10%. The specific spatial patterns of the probability of occurrence of Heracleum sosnowskyi and Fallopia spp.
were modelled in two study areas in southern Poland. The significant achievement of this study was the
application of geostatistical tools producing results characterized by a degree of precision quantified by crossvalidation
errors, and prediction errors after field verification. OK and CK returned root mean squared error
(RMSE) values in a range from 0.21 to 0.51 and 0.21 to 0.47, respectively. For OK and CK, the prediction errors
resulting from field verification in the following year were between 0.03–0.39, and 0.03–0.29, respectively.
Additionally, the study provided the first prediction maps (2D) and Digital Prediction Models (DPMs) (3D) visualizations
of the probability of occurrence of both invasive plants. Although the proposed approach is illustrated
with real case studies related to Heracleum sosnowskyi and Fallopia spp., it could be extended to other
species. This demonstrates the potential of an effective alternative strategy for evaluating the risk posed by
invasive plants, that will be able to provide fast, low cost and effective prediction and monitoring of their spread.
For institutions dealing with invasive plants, this may be beneficial and help to reduce the negative consequences
of their improper management. | pl_PL |
dc.language.iso | en | pl_PL |
dc.rights | Uznanie autorstwa 3.0 Polska | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/pl/ | * |
dc.subject | Heracleum sosnowskyi | pl_PL |
dc.subject | Fallopia spp. | pl_PL |
dc.subject | Spatial distribution | pl_PL |
dc.subject | Spectral vegetation index | pl_PL |
dc.subject | Remote sensing | pl_PL |
dc.subject | Kriging | pl_PL |
dc.title | Geostatistical models with the use of hyperspectral data and seasonal variation - a new approach for evaluating the risk posed by invasive plants | pl_PL |
dc.type | info:eu-repo/semantics/article | pl_PL |
dc.identifier.doi | 10.1016/j.ecolind.2020.107204 | - |
Pojawia się w kolekcji: | Artykuły (WNP)
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