Cite Article

Rice Growth Stages Mapping with Normalized Difference Vegetation Index (NDVI) Algorithm Using Sentinel-2 Time Series Satellite Imagery

Choose citation format

BibTeX

@article{IJASEIT12335,
   author = {Bangun Muljo Sukojo and Rizki Hari Kurniawan},
   title = {Rice Growth Stages Mapping with Normalized Difference Vegetation Index (NDVI) Algorithm Using Sentinel-2 Time Series Satellite Imagery},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {11},
   number = {4},
   year = {2021},
   pages = {1594--1598},
   keywords = {NDVI; rice growth stages; sentinel-2; time series.},
   abstract = {Rice as one of the staple food commodities consumed by most of Indonesia's population. In terms of the rice consumption level, the trend always follows national population growth every year. In 2016, Bojonegoro Regency reached 1,050,000 tons of rice; hence, it obtained a surplus of 750,000 tons of rice from the production target. Considering this potency, it is necessary to monitor the stability of agricultural production regularly. This study monitored the rice growth stages by utilizing remote sensing data of Sentinel-2 optical satellite imagery. Analyzing the growth stages of rice plants can be done through the vegetation index algorithm. The algorithm used in this study is the Normalized Difference Vegetation Index (NDVI) in time series. From the analysis of NDVI time-series graphs, the correlation between NDVI values of Sentinel-2 images and the rice growth stages is 0.896 with a coefficient of determination of 0.803 or 80.34%. The seedling phase has an NDVI value <0.224. The vegetative phase has a range of values of NDVI 0.224 - 0.894. The generative phase has NDVI value range of 0.894 - 0.270. The fallow phase has a range of NDVI values <0.270. The results of the Sentinel-2 image classification obtained classification accuracy-test values for images on January 9, 2019 with a Kappa coefficient of 0.7824 and overall accuracy of 83.87%.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12335},
   doi = {10.18517/ijaseit.11.4.12335}
}

EndNote

%A Sukojo, Bangun Muljo
%A Kurniawan, Rizki Hari
%D 2021
%T Rice Growth Stages Mapping with Normalized Difference Vegetation Index (NDVI) Algorithm Using Sentinel-2 Time Series Satellite Imagery
%B 2021
%9 NDVI; rice growth stages; sentinel-2; time series.
%! Rice Growth Stages Mapping with Normalized Difference Vegetation Index (NDVI) Algorithm Using Sentinel-2 Time Series Satellite Imagery
%K NDVI; rice growth stages; sentinel-2; time series.
%X Rice as one of the staple food commodities consumed by most of Indonesia's population. In terms of the rice consumption level, the trend always follows national population growth every year. In 2016, Bojonegoro Regency reached 1,050,000 tons of rice; hence, it obtained a surplus of 750,000 tons of rice from the production target. Considering this potency, it is necessary to monitor the stability of agricultural production regularly. This study monitored the rice growth stages by utilizing remote sensing data of Sentinel-2 optical satellite imagery. Analyzing the growth stages of rice plants can be done through the vegetation index algorithm. The algorithm used in this study is the Normalized Difference Vegetation Index (NDVI) in time series. From the analysis of NDVI time-series graphs, the correlation between NDVI values of Sentinel-2 images and the rice growth stages is 0.896 with a coefficient of determination of 0.803 or 80.34%. The seedling phase has an NDVI value <0.224. The vegetative phase has a range of values of NDVI 0.224 - 0.894. The generative phase has NDVI value range of 0.894 - 0.270. The fallow phase has a range of NDVI values <0.270. The results of the Sentinel-2 image classification obtained classification accuracy-test values for images on January 9, 2019 with a Kappa coefficient of 0.7824 and overall accuracy of 83.87%.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12335
%R doi:10.18517/ijaseit.11.4.12335
%J International Journal on Advanced Science, Engineering and Information Technology
%V 11
%N 4
%@ 2088-5334

IEEE

Bangun Muljo Sukojo and Rizki Hari Kurniawan,"Rice Growth Stages Mapping with Normalized Difference Vegetation Index (NDVI) Algorithm Using Sentinel-2 Time Series Satellite Imagery," International Journal on Advanced Science, Engineering and Information Technology, vol. 11, no. 4, pp. 1594-1598, 2021. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.11.4.12335.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Sukojo, Bangun Muljo
AU  - Kurniawan, Rizki Hari
PY  - 2021
TI  - Rice Growth Stages Mapping with Normalized Difference Vegetation Index (NDVI) Algorithm Using Sentinel-2 Time Series Satellite Imagery
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 11 (2021) No. 4
Y2  - 2021
SP  - 1594
EP  - 1598
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - NDVI; rice growth stages; sentinel-2; time series.
N2  - Rice as one of the staple food commodities consumed by most of Indonesia's population. In terms of the rice consumption level, the trend always follows national population growth every year. In 2016, Bojonegoro Regency reached 1,050,000 tons of rice; hence, it obtained a surplus of 750,000 tons of rice from the production target. Considering this potency, it is necessary to monitor the stability of agricultural production regularly. This study monitored the rice growth stages by utilizing remote sensing data of Sentinel-2 optical satellite imagery. Analyzing the growth stages of rice plants can be done through the vegetation index algorithm. The algorithm used in this study is the Normalized Difference Vegetation Index (NDVI) in time series. From the analysis of NDVI time-series graphs, the correlation between NDVI values of Sentinel-2 images and the rice growth stages is 0.896 with a coefficient of determination of 0.803 or 80.34%. The seedling phase has an NDVI value <0.224. The vegetative phase has a range of values of NDVI 0.224 - 0.894. The generative phase has NDVI value range of 0.894 - 0.270. The fallow phase has a range of NDVI values <0.270. The results of the Sentinel-2 image classification obtained classification accuracy-test values for images on January 9, 2019 with a Kappa coefficient of 0.7824 and overall accuracy of 83.87%.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12335
DO  - 10.18517/ijaseit.11.4.12335

RefWorks

RT Journal Article
ID 12335
A1 Sukojo, Bangun Muljo
A1 Kurniawan, Rizki Hari
T1 Rice Growth Stages Mapping with Normalized Difference Vegetation Index (NDVI) Algorithm Using Sentinel-2 Time Series Satellite Imagery
JF International Journal on Advanced Science, Engineering and Information Technology
VO 11
IS 4
YR 2021
SP 1594
OP 1598
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 NDVI; rice growth stages; sentinel-2; time series.
AB Rice as one of the staple food commodities consumed by most of Indonesia's population. In terms of the rice consumption level, the trend always follows national population growth every year. In 2016, Bojonegoro Regency reached 1,050,000 tons of rice; hence, it obtained a surplus of 750,000 tons of rice from the production target. Considering this potency, it is necessary to monitor the stability of agricultural production regularly. This study monitored the rice growth stages by utilizing remote sensing data of Sentinel-2 optical satellite imagery. Analyzing the growth stages of rice plants can be done through the vegetation index algorithm. The algorithm used in this study is the Normalized Difference Vegetation Index (NDVI) in time series. From the analysis of NDVI time-series graphs, the correlation between NDVI values of Sentinel-2 images and the rice growth stages is 0.896 with a coefficient of determination of 0.803 or 80.34%. The seedling phase has an NDVI value <0.224. The vegetative phase has a range of values of NDVI 0.224 - 0.894. The generative phase has NDVI value range of 0.894 - 0.270. The fallow phase has a range of NDVI values <0.270. The results of the Sentinel-2 image classification obtained classification accuracy-test values for images on January 9, 2019 with a Kappa coefficient of 0.7824 and overall accuracy of 83.87%.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12335
DO  - 10.18517/ijaseit.11.4.12335