TY - GEN
T1 - Agricultural drought identification based on Soil Moisture Index (SMI) during 2019 Indian Ocean Dipole (IOD) in Bekasi Regency
AU - Arfaansyah, Teddy
AU - Shidiq, Iqbal Putut Ash
AU - Dimyati, Muhammad
N1 - Funding Information:
We thank the Department of Geography, University of Indonesia for its support and encouragement for this research. as one of the requirements for taking a bachelor's degree and the need for scientific publications
Publisher Copyright:
© 2021 SPIE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Agricultural drought
KW - Bekasi Regency
KW - Landsat 8
KW - NDDI
KW - SMI
UR - http://www.scopus.com/inward/record.url?scp=85124684207&partnerID=8YFLogxK
U2 - 10.1117/12.2623397
DO - 10.1117/12.2623397
M3 - Conference contribution
AN - SCOPUS:85124684207
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Seventh Geoinformation Science Symposium 2021
A2 - Wibowo, Sandy Budi
A2 - Wicaksono, Pramaditya
PB - SPIE
T2 - 7th Geoinformation Science Symposium 2021
Y2 - 25 October 2021 through 28 October 2021
ER -