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Mapping Soil Degradation using Remote Sensing Data and Ancillary Data - South-East Moravia, Czech Republic

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027049%3A_____%2F18%3AN0000067" target="_blank" >RIV/00027049:_____/18:N0000067 - isvavai.cz</a>

  • Alternative codes found

    RIV/60460709:41210/19:79454 RIV/00216208:11310/19:10378889

  • Result on the web

    <a href="https://www.tandfonline.com/doi/full/10.1080/22797254.2018.1482524" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/22797254.2018.1482524</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1080/22797254.2018.1482524" target="_blank" >10.1080/22797254.2018.1482524</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Mapping Soil Degradation using Remote Sensing Data and Ancillary Data - South-East Moravia, Czech Republic

  • Original language description

    Data on the real extent of soil that is degraded by erosion represent important information for the purposes of conservation policy. However, this type of data is rarely available for large areas. A remote-sensing-based method for identifying of eroded areas at the regional scale has been tested using a combination of time series of free access Sentinel-2 image data, airborne orthoimages and ground-truth data. The unsupervised classification ISODATA of the Sentinel-2A images has been performed. The minimum distance method has been applied for the assignment of unsupervised classes to four erosion classes using the ground-truth data. The automatic classification of eroded soils achieved an overall accuracy of 55.2 % for three distinguished classes. An accumulated class has been eliminated as no unsupervised classes were assigned to this erosion class. A simplified classification of two classes (strongly eroded and other soils) reached an accuracy of 80.9%. The overall accuracy of the simplified classification increased to 86.9% after the visual refinement using orthoimages. This study shows the potential of the tested approach to produce valuable data on actual soil degradation by erosion. The limitations of the method are related to the soil cover variability, masking effect of clouds, vegetation or litter and the spectral separability of individual classes.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    40104 - Soil science

Result continuities

  • 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)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    European Journal of Remote Sensing

  • ISSN

    2279-7254

  • e-ISSN

    2279-7254

  • Volume of the periodical

    sup1

  • Issue of the periodical within the volume

    52

  • Country of publishing house

    IT - ITALY

  • Number of pages

    16

  • Pages from-to

    108-122

  • UT code for WoS article

    000475928900009

  • EID of the result in the Scopus database

    2-s2.0-85049792270