Integration of data of the remote sensing, gis, and gamma-spectrometric analysis to study soil material redistribution

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Integration of data of the remote sensing, gis, and gamma-spectrometric analysis to study soil material redistribution. / Trofimetz, L. N.; Kolesnikov, A. A.; Panidi, E. A.; Kikin, P. M.

в: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Том 43, № B4-2021, 30.06.2021, стр. 147-152.

Результаты исследований: Научные публикации в периодических изданиях › статья в журнале по материалам конференции › Рецензирование

Author

Trofimetz, L. N. ; Kolesnikov, A. A. ; Panidi, E. A. ; Kikin, P. M. / Integration of data of the remote sensing, gis, and gamma-spectrometric analysis to study soil material redistribution. в: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 2021 ; Том 43, № B4-2021. стр. 147-152.

BibTeX

@article{a72b2544c553466d84aff09fc5bc9743,

title = "Integration of data of the remote sensing, gis, and gamma-spectrometric analysis to study soil material redistribution",

abstract = "The paper discusses a problem of complex data application when accounting erosion network elements to study soil runoff and soil material redistribution on arable slopes. It is needed to estimate and account contribution of microrelief landforms to the sediment (washed out soil material) redistribution on arable areas to enhance accuracy of estimation of the soil runoff and accumulation. However, microrelief landforms are hardly detected on topographic maps and plans used traditionally in land management. For example, temporary streams formed in plowing furrows (in the case of along-slope plowing) can be detected only when survey and soil sampling data are attracted, or (partially) using remote sensing data.Due to such a context, we discover integrated analysis of map data (digital maps represented and processed in GIS environment), data of gamma-spectrometric analysis of the soil samples, and very high resolution satellite imagery, which is aimed onto detection of the role of stable and dynamically changing microrelief landforms in soil material redistribution.",

keywords = "GIS-based Mapping, Microrelief, Soil Runoff, Very High Resolution Imagery",

author = "Trofimetz, {L. N.} and Kolesnikov, {A. A.} and Panidi, {E. A.} and Kikin, {P. M.}",

note = "Publisher Copyright: {\textcopyright} Author(s) 2021. CC BY 4.0 License.All right reserved.; 24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow, Commission IV ; Conference date: 05-07-2021 Through 09-07-2021",

year = "2021",

month = jun,

day = "30",

doi = "10.5194/isprs-archives-XLIII-B4-2021-147-2021",

language = "English",

volume = "43",

pages = "147--152",

journal = "International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences",

issn = "1682-1750",

publisher = "International Society for Photogrammetry and Remote Sensing",

number = "B4-2021",

}

RIS

TY - JOUR

T1 - Integration of data of the remote sensing, gis, and gamma-spectrometric analysis to study soil material redistribution

AU - Trofimetz, L. N.

AU - Kolesnikov, A. A.

AU - Panidi, E. A.

AU - Kikin, P. M.

PY - 2021/6/30

Y1 - 2021/6/30

N2 - The paper discusses a problem of complex data application when accounting erosion network elements to study soil runoff and soil material redistribution on arable slopes. It is needed to estimate and account contribution of microrelief landforms to the sediment (washed out soil material) redistribution on arable areas to enhance accuracy of estimation of the soil runoff and accumulation. However, microrelief landforms are hardly detected on topographic maps and plans used traditionally in land management. For example, temporary streams formed in plowing furrows (in the case of along-slope plowing) can be detected only when survey and soil sampling data are attracted, or (partially) using remote sensing data.Due to such a context, we discover integrated analysis of map data (digital maps represented and processed in GIS environment), data of gamma-spectrometric analysis of the soil samples, and very high resolution satellite imagery, which is aimed onto detection of the role of stable and dynamically changing microrelief landforms in soil material redistribution.

AB - The paper discusses a problem of complex data application when accounting erosion network elements to study soil runoff and soil material redistribution on arable slopes. It is needed to estimate and account contribution of microrelief landforms to the sediment (washed out soil material) redistribution on arable areas to enhance accuracy of estimation of the soil runoff and accumulation. However, microrelief landforms are hardly detected on topographic maps and plans used traditionally in land management. For example, temporary streams formed in plowing furrows (in the case of along-slope plowing) can be detected only when survey and soil sampling data are attracted, or (partially) using remote sensing data.Due to such a context, we discover integrated analysis of map data (digital maps represented and processed in GIS environment), data of gamma-spectrometric analysis of the soil samples, and very high resolution satellite imagery, which is aimed onto detection of the role of stable and dynamically changing microrelief landforms in soil material redistribution.

KW - GIS-based Mapping

KW - Microrelief

KW - Soil Runoff

KW - Very High Resolution Imagery

UR - http://www.scopus.com/inward/record.url?scp=85117819749&partnerID=8YFLogxK

U2 - 10.5194/isprs-archives-XLIII-B4-2021-147-2021

DO - 10.5194/isprs-archives-XLIII-B4-2021-147-2021

M3 - Conference article

AN - SCOPUS:85117819749

VL - 43

SP - 147

EP - 152

JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

SN - 1682-1750

IS - B4-2021

T2 - 24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow, Commission IV

Y2 - 5 July 2021 through 9 July 2021

ER -

ID: 87854285