Satellite data spectral analysis under critical hydrogeological-amelioratory conditions of Golodnostepsky irrigation lands

Zhuldyzbek Onglassynov, Lyudmila Shagarova, Mira Muratova

E3S Web of Conferences, 2023

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DOI 10.1051/e3sconf/202340702005
Data confidence 70 medium
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Abstract

The article presents the analysis of widespread spectral indexes of the results of the Earth remote sensing data thematic processing to reveal the most representative one for applying under conditions of critical increase of groundwater level and salinity as well as salinized soil. Long-term monitoring data and multispectral images of the LandSat-8 satellite were collected for the Golodnostepsky irrigation land. Sites with the most disturbing ameliorative conditions were identified using GIS. 74 sites comply with this criterion where cotton, rice, and cucurbits crops are cultivated. Seasonal multispectral data of the region covering emphasised sites and spectral indexes were processed and calculated: NDVI, SAVI, MSAVI-2, GEMI, ARVI, IPVI, MTVI, TDVI, NDWI, MNDWI, NDSI. The following results turned out to be the most informative vegetation indexes: NDVI (yearly changes variation range 0.40) and SAVI (yearly changes variation range 0.44). At the same time the least informative vegetation indexes became IPVI (yearly changes variation range 0.19) and GEMI (yearly changes variation range 0.11). It was shown that vegetation indexes data are highly correlated with the amount of precipitation, an average air temperature and crop yield. Among water indexes, NDWI (yearly changes variation range 0.32) turned out to be more preferable than MNDWI (yearly changes variation range 0.15). The information value of the index of salinity NDSI for the sample turned out to be low (yearly changes variation range 0.17), which can be explained by agricultural and ameliorative activity at the site under research (ploughing, sprouting, vegetation, saline washing, etc.)