Agricultural drought identification based on Soil Moisture Index (SMI) during 2019 Indian Ocean Dipole (IOD) in Bekasi Regency

Teddy Arfaansyah; Iqbal Putut Ash Shidiq; Muhammad Dimyati

doi:10.1117/12.2623397

22 December 2021 Agricultural drought identification based on Soil Moisture Index (SMI) during 2019 Indian Ocean Dipole (IOD) in Bekasi Regency

Teddy Arfaansyah, Iqbal Putut Ash Shidiq, Muhammad Dimyati

Author Affiliations +

Proceedings Volume 12082, Seventh Geoinformation Science Symposium 2021; 1208209 (2021) https://doi.org/10.1117/12.2623397
Event: Seventh Geoinformation Science Symposium (GSS 2021), 2021, Yogyakarta, Indonesia

Abstract

The 2019 Indian Ocean Dipole (IOD) event has impacted Indonesia in many ways. The extreme weather events due to the changes in rainfall patterns and increased average temperature were causing severe agricultural drought in some areas, including Bekasi Regency. Monitoring agricultural drought is challenging due to the nature and extent of the damage caused by the event. This study aims to identify some of the agricultural drought events in Bekasi based on soil moisture features (SMI). The approximate agricultural drought model was generated from Normalized Difference Drought Index (NDDI), while soil moisture information was derived from the Soil Moisture Index (SMI). Landsat 8 OLI-TIRS was utilized for generating both indexes. The analysis was carried out in the dry months of 2019, including July, August, September, and October, where the lowest rainfalls were found. The study founds that more than 50% of the area was damaged by severe drought every month. Most of the severe drought occurred in September, damaging 50,919.32 hectares (91%) of rice fields. Statistical-based Pearson’s correlation shows a significant relationship between NDDI and SMI, with R coefficient ranges from -0.37 to -0.74, especially from July to October. Conclusively, both indexes were successfully applied to picture agricultural drought phenomena in Bekasi Regency.

Citation Download Citation

Teddy Arfaansyah, Iqbal Putut Ash Shidiq, and Muhammad Dimyati "Agricultural drought identification based on Soil Moisture Index (SMI) during 2019 Indian Ocean Dipole (IOD) in Bekasi Regency", Proc. SPIE 12082, Seventh Geoinformation Science Symposium 2021, 1208209 (22 December 2021); https://doi.org/10.1117/12.2623397

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KEYWORDS

Soil science

Agriculture

Vegetation

Earth observing sensors

Remote sensing

Landsat

Data processing

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