Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)

The Utilization of Sentinel-1 Soil Moisture Satellite Imagery for Crop’s Water Requirement Analysis in the Dryland Agriculture

Authors
M. Wiji Nur Huda1, Hanggar Ganara Mawandha1, *, M. Ramadhan AG1, Ngadisih Ngadisih1
1Department of Agricultural Engineering and Biosystem, Gadjah Mada University, Yogyakarta, 55281, Indonesia
*Corresponding author. Email: hanggar.g.m@ugm.ac.id
Corresponding Author
Hanggar Ganara Mawandha
Available Online 28 December 2022.
DOI
10.2991/978-94-6463-086-2_66How to use a DOI?
Keywords
Soil moisture; Crop water; Sentinel-1; Backscattering; Dubois Model; Synthetic Aperture Radar
Abstract

Soil moisture is an essential factor in supporting the crop’s growth. The total soil moisture affects plant fertility, which impacts its productivity. The information about soil moisture can be used for crop scheduling to optimize the potential of the harvest and reduce crop failure risk. The utilization of remote sensing data to measure soil moisture can be implemented for routine agricultural practices. This information is important, especially for dryland agriculture such as in the Semanu, Gunung Kidul Regency. Value of soil moisture can be obtained from Sentinel-1 satellite image through the backscattering (σ°) method, which involves Apply Orbit File, Thermal Noise Removal, Border Noise Removal, Calibration, Speckle Filtering, Range Doppler Terrain Correction, and Conversion to dB. The dB (σ°) was then processed using the Dubois Model and Topp Model until the importance of soil moisture volumetric value was obtained, known in cm3/cm3. In this research, measuring the soil moisture value was also conducted by taking the soil sample tests under gravimetry methods for validation and sensor soil meter for comparison. Using Sentinel-1 to find soil moisture value is an alternative that can be done without conducting ground measurements. It is supported by a high resolution of 10x10 m and a standard error value of ±0,045. Furthermore, Sentinel-1 uses SAR (Synthetic Aperture Radar) possible to penetrate the cloud and land surface covers, even covered by lush vegetation. The backscattering data is, therefore, likely to be continuously generated. Based on the calculation of crops’ water requirements by inputting the soil moisture values obtained from the calibrated Sentinel-1 data, the crop scheduling for dryland agriculture in the Semanu region was adjusted. Sentinel-1, which has interval data available every 12 days, is ideal for routine agriculture practices in real time. Therefore, the opportunity for agriculture development through Sentinel-1 is auspicious.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)
Series
Advances in Biological Sciences Research
Publication Date
28 December 2022
ISBN
978-94-6463-086-2
ISSN
2468-5747
DOI
10.2991/978-94-6463-086-2_66How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - M. Wiji Nur Huda
AU  - Hanggar Ganara Mawandha
AU  - M. Ramadhan AG
AU  - Ngadisih Ngadisih
PY  - 2022
DA  - 2022/12/28
TI  - The Utilization of Sentinel-1 Soil Moisture Satellite Imagery for Crop’s Water Requirement Analysis in the Dryland Agriculture
BT  - Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)
PB  - Atlantis Press
SP  - 484
EP  - 491
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6463-086-2_66
DO  - 10.2991/978-94-6463-086-2_66
ID  - Huda2022
ER  -