Soil mapping using geo-information technologies

DOI

10.2991/ispc-19.2019.35How to use a DOI?

Keywords

soil cover, Earth remote sensing (ERS), soil mapping, GIS technologies, cost-effectiveness of soil survey

Abstract

This paper presents the review of the current state of agricultural land based on GIS technologies using materials of Earth remote sensing on the example of the forest-steppe zone of Western Siberia which is the most developed and populated territory of this region. We used multispectral images of the Landsat 8 spacecraft (SC) (USA) with a resolution of 30 m per pixel. These images allow monitoring of the Earth’s surface every 16th day with a flying-by width of 185 km in nadir. Computer processing of the series of multispectral satellite images (MSI) using the method of synthesizing (superposition of the long and short wavelengths of solar radiation spectrum) was carried out using the licensed software package ENVI 5.0. (produced by ESRI company). During creating electronic cartographic material of the studied area (based on satellite data), a digital basis for agricultural lands was made at first. Digitalization of outdated material was performed using QGis software package (desktop GIS for creating, editing, visualizing, analyzing and publishing geospatial information. It is QGIS Desktop that is often meant by QGIS). For the first time, a spatial-temporal change in the structure of agricultural land of this region over the past twenty-five years was revealed using multi-temporal images made by Landsat 8 SC. Areas were found that have moved from the category of arable land to the fallow one, and were susceptible to flooding. A partial soil survey was conducted in the study area (with sampling for chemical analysis) to establish soil type according to modern classification in order to update soil maps and to create an electronic cartogram showing soil suitability based on their agricultural type. Cost-effectiveness of the cluster method for soil and agrochemical survey of agricultural land was calculated.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Marat Shayakhmetov
AU  - Alla Zinich
AU  - Alexandra Gindemit
PY  - 2019/06
DA  - 2019/06
TI  - Soil mapping using geo-information technologies
BT  - Proceedings of the International Scientific and Practical Conference “Digital agriculture - development strategy” (ISPC 2019)
PB  - Atlantis Press
SP  - 156
EP  - 159
SN  - 1951-6851
UR  - https://doi.org/10.2991/ispc-19.2019.35
DO  - 10.2991/ispc-19.2019.35
ID  - Shayakhmetov2019/06
ER  -