Characterizing the spatial variability of soil salinity in lake urmia basin by applying geo-statistical methods

Taha Gorji, Aylin Yildirim, Nikou Hamzehpour, Elif Sertel, Aysegul Tanik

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

Özet

Land degradation by salinity is one of the main environmental hazards threatening soil sustainability especially in arid and semi-arid regions of the world characterized by low precipitation and high evaporation. Geo-statistical approaches and remote sensing (RS) techniques have provided fast, accurate and economic prediction and mapping of soil salinity within the last two decades. Obtaining multi-temporal data via satellite images in different spatial domains with various scales is one of the key developments of monitoring spatial variability of soil salinity. In addition, geo-statistical methods have the capability of producing prediction surfaces from limited sample data. This study aims to map spatial distribution of soil salinity in the selected pilot area which is located in the western part of Urmia Lake Basin, Iran, by applying geo-statistical methods. A kriging based map and three different co-kriging based maps were produced using electrical conductivity (EC) measurements as primary variable and three different soil salinity index values as secondary variable. Three soil salinity indices were created by using Sentinel-2A image that were acquired in the same date of field measurements to generate 3 various soil salinity prediction maps. Salinity maps obtained from geo-statistical methods were compared and validated to understand the performance of these approaches for soil salinity prediction. The results of this study demonstrated that co-kriging can provide promising estimation of spatial variability of soil salinity especially when there is relevant and abundant set of secondary data derived from satellite images.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2019 8th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2019
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9781728121161
DOI'lar
Yayın durumuYayınlandı - Tem 2019
Etkinlik8th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2019 - Istanbul, Turkey
Süre: 16 Tem 201919 Tem 2019

Yayın serisi

Adı2019 8th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2019

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???event.eventtypes.event.conference???8th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2019
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot16/07/1919/07/19

Bibliyografik not

Publisher Copyright:
© 2019 IEEE.

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