A simple trilingual app for determining near-surface soil moisture

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dc.contributor.author Kalra, Kanishk
dc.contributor.author Gadi, Vinay Kumar
dc.contributor.author Alybaev, Dastan
dc.contributor.author Garg, Ankit
dc.contributor.author Sreedeep, S.
dc.contributor.author Sahoo, Lingaraj
dc.coverage.spatial Germany
dc.date.accessioned 2021-03-16T12:18:59Z
dc.date.available 2021-03-16T12:18:59Z
dc.date.issued 2021-02
dc.identifier.citation Kalra, Kanishk; Gadi, Vinay Kumar; Alybaev, Dastan; Garg, Ankit; Sreedeep, S. and Sahoo, Lingaraj, "A simple trilingual app for determining near-surface soil moisture", Indian Geotechnical Journal, DOI: 10.1007/s40098-020-00487-3, Feb. 2021. en_US
dc.identifier.issn 2277-3347
dc.identifier.uri http://dx.doi.org/10.1007/s40098-020-00487-3
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/6356
dc.description.abstract The locust has been devastating pest, which destructs the crops and pastures. Scientists discover the breeding habitats of locust based on soil surface water content (SWC) to devise preventive measures. Hence, accurate interpretation of SWC is vital to safeguard economic livelihood and ensure food security. Researchers usually adapt satellite data and manual/automatic colour-based image processing techniques to interpret SWC. However, satellites could not capture high-resolution images and ground information in densely vegetated areas. In addition, many of the ground surveying teams/farmers could not conduct colour analysis due to the lack of knowledge. Therefore, this manuscript introduces a newly developed web app to overcome the limitations of previously developed techniques. The steps involved in developing the new app were demonstrated to avoid the manual image analysis. Four series of experiments were conducted to quantify the moisture content using the newly developed app. The moisture content was also quantified using conventional manual image analysis technique to validate the newly developed app. The difference between the moisture contents obtained from the above-mentioned methods was found to be 1%-3%. This shows that the newly developed app has potential to identify the locust breeding habitats and guide the ground surveying teams to prevent locust swarm formation.
dc.description.statementofresponsibility by Kanishk Kalra, Vinay Kumar Gadi, Dastan Alybaev, Ankit Garg, S. Sreedeep and Lingaraj Sahoo
dc.language.iso en_US en_US
dc.publisher Springer Verlag en_US
dc.subject Locust en_US
dc.subject Breeding areas en_US
dc.subject Identification en_US
dc.subject Surface water content en_US
dc.subject APP en_US
dc.title A simple trilingual app for determining near-surface soil moisture en_US
dc.type Article en_US
dc.relation.journal Indian Geotechnical Journal


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