A review of major factors influencing the accuracy of mapping green-attack stage of bark beetle infestations using satellite imagery: Prospects to avoid data redundancy

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F21%3A89676" target="_blank" >RIV/60460709:41320/21:89676 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/abs/pii/S2352938521001749" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S2352938521001749</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.rsase.2021.100638" target="_blank" >10.1016/j.rsase.2021.100638</a>

Result language
angličtina
Original language name
A review of major factors influencing the accuracy of mapping green-attack stage of bark beetle infestations using satellite imagery: Prospects to avoid data redundancy
Original language description
Detecting green-attacked trees on satellite imagery with high accuracy provides very important broad-scale tools required to control the spreads of infestations to healthy trees. The scale or resolution plays a critical role in such equations but very often lacks adequate attentions in remote sensing investigations of environmental issues, including mapping green-attacked trees. We reviewed and synthesized current understanding about mapping green-attacked trees, vegetation remote sensing, and spatial statistics to characterize the uncertainty associated with major factors influencing the accuracy of detecting green-attacked trees. These factors include the spatial, spectral, and temporal resolutions of satellite imagery, and a type of model used. Satellite imagery with spatial resolutions less than 4 m (approximately 2/3 size of the crown diameter of a host tree on average) on bidaily to weekly acquisitions are required to improve the accuracy of mapping infested trees on a continuous basis. Changes
Czech name
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Czech description
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Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
20705 - Remote sensing

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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