TY - JOUR
T1 - Remote sensing-based vegetation indices for monitoring rice crop phenology and productivity in cikakak sub-district, sukabumi regency
AU - Hisyam, A. K.
AU - Supriatna, S.
AU - Shidiq, I. P.A.
N1 - Publisher Copyright:
© 2022 Institute of Physics Publishing. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Paddy is the main food crop consumed by most of the Indonesian daily. It is supported by the fact that rice consumption reached up to 1.55 tons in 2018, and Sukabumi Regency is among the five largest rice producer in Indonesia. The goal of this study is to determine the rice crop phenology and estimate rice productivity in one year of the planting season. The rice crop phenology was analyzed by comparing vegetation indices such as NDVI, ARVI, and MSAVI in different temporal situations. Vegetation indices derived from Sentinel-2 imageries via Google Earth Engine. A rice crop productivity model developed from the statistical relationship between in-situ-based productivity data and vegetation indices applied to estimate productivity per each paddy field at a sub-district level. Also, the estimation will be associated with elevation data. The results of this study are the pattern of the rice crop phenology and the number of harvesting time in one year-planting season. The rice productivity in the Cikakak sub-district estimates at the range between 6.50 to 8.87 tonnes per hectare. Estimation models utilizing NDVI and MSAVI are showing similar results, which averagely at 8.89 and 8.87 tonnes per hectare, respectively. Rice fields with high productivity are mostly located at 250 to 500 meters above sea level.
AB - Paddy is the main food crop consumed by most of the Indonesian daily. It is supported by the fact that rice consumption reached up to 1.55 tons in 2018, and Sukabumi Regency is among the five largest rice producer in Indonesia. The goal of this study is to determine the rice crop phenology and estimate rice productivity in one year of the planting season. The rice crop phenology was analyzed by comparing vegetation indices such as NDVI, ARVI, and MSAVI in different temporal situations. Vegetation indices derived from Sentinel-2 imageries via Google Earth Engine. A rice crop productivity model developed from the statistical relationship between in-situ-based productivity data and vegetation indices applied to estimate productivity per each paddy field at a sub-district level. Also, the estimation will be associated with elevation data. The results of this study are the pattern of the rice crop phenology and the number of harvesting time in one year-planting season. The rice productivity in the Cikakak sub-district estimates at the range between 6.50 to 8.87 tonnes per hectare. Estimation models utilizing NDVI and MSAVI are showing similar results, which averagely at 8.89 and 8.87 tonnes per hectare, respectively. Rice fields with high productivity are mostly located at 250 to 500 meters above sea level.
UR - http://www.scopus.com/inward/record.url?scp=85142475885&partnerID=8YFLogxK
U2 - 10.1088/1755-1315/1089/1/012025
DO - 10.1088/1755-1315/1089/1/012025
M3 - Conference article
AN - SCOPUS:85142475885
SN - 1755-1307
VL - 1089
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 1
M1 - 012025
T2 - 4th International Geography Seminar 2020, IGEOS 2020
Y2 - 29 September 2020 through 30 September 2020
ER -