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Spectral Enhancement of Imagery for Small Inland Water Bodies Monitoring: Utilization of UAV-Based Data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F19%3A39914997" target="_blank" >RIV/00216275:25410/19:39914997 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.jisem-journal.com/article/spectral-enhancement-of-imagery-for-small-inland-water-bodies-monitoring-utilization-of-uav-based-6346" target="_blank" >https://www.jisem-journal.com/article/spectral-enhancement-of-imagery-for-small-inland-water-bodies-monitoring-utilization-of-uav-based-6346</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.29333/jisem/6346" target="_blank" >10.29333/jisem/6346</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Spectral Enhancement of Imagery for Small Inland Water Bodies Monitoring: Utilization of UAV-Based Data

  • Original language description

    The article describes a way for identification of land cover types and consequently land cover changes around a small water body, which is based on spectral enhancement of RGB UAV-based data. A middle-class unmanned aerial vehicle (UAV) – DJI Phantom 3 Pro, was used for data collection. UAV represents a cheap and on-demand available solution for remote data sensing. Its utilization is limited by weather conditions and particular legal regulations must be followed. The article is focused on a monitoring of a small water body and its surrounding by spectral enhancement. Spectral indices, which are calculated only from the visible bands, are used to identify particular land cover types: Color Index of Vegetation Extraction (CIVE), Excess Green (ExG), Excess Red (ExR), Green Leaf Index (GLI), Normalized Green-Red Difference Index (NGRDI), Red-Green-Blue Vegetation Index (RGBVI), Visible Atmospherically Resistant Index (VARI), and ExG – ExR difference. Low pass filtering was used for post-processing and results were simply visualised in a form of classified raster (by natural breaks – Jenks). Even this simple spectral enhancement of imagery supports its visual interpretation. Visible spectral indices highlight particular land cover types, namely green vegetation and water surface but other types of land cover can be distinguished as well.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>ost</sub> - Miscellaneous article in a specialist periodical

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Information Systems Engineering &amp; Management

  • ISSN

    2468-4376

  • e-ISSN

  • Volume of the periodical

    4

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    9

  • Pages from-to

    1-9

  • UT code for WoS article

  • EID of the result in the Scopus database