Geostatistical models with the use of hyperspectral data and seasonal variation – A new approach for evaluating the risk posed by invasive plants

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 a...

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Autores principales:	Katarzyna Bzdęga, Adrian Zarychta, Alina Urbisz, Sylwia Szporak-Wasilewska, Michał Ludynia, Barbara Fojcik, Barbara Tokarska-Guzik
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Heracleum sosnowskyi Fallopia spp. Spatial distribution Spectral vegetation index Remote sensing Kriging Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/43b344ae65424ba6b146d98b0a49397d
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spelling	oai:doaj.org-article:43b344ae65424ba6b146d98b0a49397d2021-12-01T04:38:46ZGeostatistical models with the use of hyperspectral data and seasonal variation – A new approach for evaluating the risk posed by invasive plants1470-160X10.1016/j.ecolind.2020.107204https://doaj.org/article/43b344ae65424ba6b146d98b0a49397d2021-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20311432https://doaj.org/toc/1470-160XThe 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 co-kriging (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 cross-validation 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.Katarzyna BzdęgaAdrian ZarychtaAlina UrbiszSylwia Szporak-WasilewskaMichał LudyniaBarbara FojcikBarbara Tokarska-GuzikElsevierarticleHeracleum sosnowskyiFallopia spp.Spatial distributionSpectral vegetation indexRemote sensingKrigingEcologyQH540-549.5ENEcological Indicators, Vol 121, Iss , Pp 107204- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Heracleum sosnowskyi Fallopia spp. Spatial distribution Spectral vegetation index Remote sensing Kriging Ecology QH540-549.5
spellingShingle	Heracleum sosnowskyi Fallopia spp. Spatial distribution Spectral vegetation index Remote sensing Kriging Ecology QH540-549.5 Katarzyna Bzdęga Adrian Zarychta Alina Urbisz Sylwia Szporak-Wasilewska Michał Ludynia Barbara Fojcik Barbara Tokarska-Guzik Geostatistical models with the use of hyperspectral data and seasonal variation – A new approach for evaluating the risk posed by invasive plants
description	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 co-kriging (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 cross-validation 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.
format	article
author	Katarzyna Bzdęga Adrian Zarychta Alina Urbisz Sylwia Szporak-Wasilewska Michał Ludynia Barbara Fojcik Barbara Tokarska-Guzik
author_facet	Katarzyna Bzdęga Adrian Zarychta Alina Urbisz Sylwia Szporak-Wasilewska Michał Ludynia Barbara Fojcik Barbara Tokarska-Guzik
author_sort	Katarzyna Bzdęga
title	Geostatistical models with the use of hyperspectral data and seasonal variation – A new approach for evaluating the risk posed by invasive plants
title_short	Geostatistical models with the use of hyperspectral data and seasonal variation – A new approach for evaluating the risk posed by invasive plants
title_full	Geostatistical models with the use of hyperspectral data and seasonal variation – A new approach for evaluating the risk posed by invasive plants
title_fullStr	Geostatistical models with the use of hyperspectral data and seasonal variation – A new approach for evaluating the risk posed by invasive plants
title_full_unstemmed	Geostatistical models with the use of hyperspectral data and seasonal variation – A new approach for evaluating the risk posed by invasive plants
title_sort	geostatistical models with the use of hyperspectral data and seasonal variation – a new approach for evaluating the risk posed by invasive plants
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/43b344ae65424ba6b146d98b0a49397d
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Geostatistical models with the use of hyperspectral data and seasonal variation – A new approach for evaluating the risk posed by invasive plants

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