Analisis Produktivitas Padi berdasarkan Indeks Kekeringan (NDWI dan NDDI) Lahan Sawah menggunakan Data Citra Sentinel-2A di Kecamatan Ambulu

Bowo Eko Cahyono, Rahmadin Rahagian, Agung Thahjo Nugroho

Abstract

Rice is almost a staple food source for the world's population. The State of Indonesia contributes the largest amount of rice productivity, especially in the province of East Java. Ambulu District is part of the province of East Java, which has experienced a decline in rice productivity. The decline in rice productivity is thought to be the result of agricultural land drought. The purpose of this study was to determine the correlation value of the drought index (NDWI and NDDI) with rice productivity. This research was conducted using remote sensing methods using the Sentinel-2A satellite from 2016 to 2020 during the rainy season. Sentinel-2A satellite data is in the form of images, which are then cropped and digitized on agricultural land. Furthermore, the data was processed using Arcgis Software to obtain NDWI (Normalized Defense Water Index) and NDDI (Normalized Defense Drought Index) values as land dryness parameters, which were classified into 5 classes. The correlation results of the NDWI value on rice productivity have a directly proportional relationship with an effect of 61.96% and 38.04% influenced by other factors. The results of the correlation of NDDI values on rice productivity have an inverse relationship with an effect of 68.68% and 31.32% influenced by other factors

Keywords

Remote sensing; Sentinel; NDWI; NDDI; rice productivity

Full Text:

PDF

References

  1. Ishaq, M., Rumiati, A. T., & Permatasari, E. O. 2017. Analisis faktor-faktor yang mempengaruhi produksi padi di Provinsi Jawa Timur menggunakan regresi semiparametrik spline. Jurnal Sains Dan Seni ITS. 6(1), 7, doi: 10.12962/j23373520.v6i1.22451.
  2. Adawiyah, C. R., Sumardjo, N., & Mulyani, E. S. 2018. Faktor-faktor yang memengaruhi peran komunikasi kelompok tani dalam adopsi inovasi teknologi upaya khusus (padi, jagung, dan kedelai) di Jawa Timur. Jurnal Agro Ekonomi, 35(2), 151. doi:10.21082/jae.v35n2.2017.151-170.
  3. Wahed, M. 2018. Pengaruh luas lahan, produksi dan harga gabah terhadap kesekjahteraan petani padi di daerah sentral produksi padi Kabupaten Jember. Journal of Economics Development Issues, 1(1), 33–40, doi: 10.33005/jedi.v1i1.9.
  4. Badan Pusat Statistik Kabupaten Jember. 2021. Kabupaten Jember Dalam Angka 2021. BPS Kabupaten Jember. BPS Kab, Jember, ISSN: 0215.5524.
  5. Gu, Y., Brown, J. F., Verdin, J. P., & Wardlow, B. 2007. A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States. Geophysical Research Letters, 34(6), 1–6, doi: 10.1029/2006GL029127.
  6. Estiningtyas, W., & Syakir, M. 2018. Pengaruh perubahan iklim terhadap produksi padi di lahan tadah hujan. Jurnal Meteorologi Dan Geofisika, 18(2), 83–93, doi: 10.31172/jmg.v18i2.406.
  7. Yuliandoko, H., & Wardhany, V. A. 2019. Implementasi monitoring kelembapan dan suhu tanah berbasis Wireless Mesh sebagai penunjang peningkatan produksi padi. Jurnal Teknologi Informasi Dan Terapan, 4(1), 33–38, doi: 10.25047/jtit.v4i1.18.
  8. Tubur, H. W., Chozin, M. A., Santosa, A., & Junaedi, A. 2013. Respon agronomi varietas padi terhadap periode kekeringan pada sistem sawah. Jurnal Agronomi Indonesia (Indonesian Journal of Agronomy), 40(3), 167–173, doi: 10.24831/jai.v40i3.6796.
  9. Wahyudie, Tri. 2020. Pengolaan Komoditas Hortikultura Ungulan Berbasis Lingkungan. FP. Aswaja. NTB, Indonesia, ISBN: 978-623-6636-31-2.
  10. Abbas, T., Rizwan, M., Ali, S., Adrees, M., Mahmood, A., Zia-ur-rehman, M., Ibrahim, M., Arshad, M., & Farooq, M. 2018. Ecotoxicology and Environmental Safety Biochar application increased the growth and yield and reduced cadmium in drought stressed wheat grown in an aged contaminated soil. Ecotoxicology and Environmental Safety, 148(August 2017), 825–833, doi: 10.1016/j.ecoenv.2017.11.063.
  11. Chen, W., Yao, X., Cai, K., & Chen, J. 2011. Silicon alleviates drought stress of rice plants by improving plant water status, photosynthesis and mineral nutrient absorption. Biological Trace Element Research, 142(1), 67–76, doi: 10.1007/s12011-010-8742-x.
  12. Taufik, A. 2019. Perspektif tentang perkembangan sistem pembelajaran jarak jauh di Kabupaten Kutai Kartanegara Kalimantan Timur. Jurnal Pendidikan&Konseptual, 3(2), 88–98, doi: 10.28926/riset_konseptual.v2i4.111.
  13. Zhang, C., & Kovacs, J. M. 2012. The application of small unmanned aerial systems for precision agriculture: A review. Precision Agriculture, 13(6), 693–712, doi: 10.1007/s11119-012-9274-5.
  14. Putri, E. S., Widiasari, A., Karim, R. A., Somantri, L., & Ridwana, R. (2021). Pemanfaatan citra Sentinel-2 untuk analisis kerapatan vegetasi di wilayah Gunung Manglayang. Jurnal Pendidikan Geografi Undiksha, 9(2), 133–143, doi: 10.23887/jjpg.v9i2.35357.
  15. Kasanah, N., Bashit, N., & Hadi, F. (2021). Analisis lahan sawah tergenang banjir menggunakan metode change detection dan Pppm (phenology and pixel based paddy rice mapping) (studi kasus: Kabupaten Demak). Jurnal Geodesi Undip, 10, 259–268.
  16. Rahman, F., Sukmono, A., & Yuwono, B. D. 2017. Analisis kekeringan pada lahan pertanian menggunakan metode NDDI dan perka BNPB nomer 02 tahun 2012 (studi kasus: Kabupaten Kendal tahun 2015). Jurnal Geodesi UNDIP, 6(4), 274-284.
  17. Ahmadalipour, A., Moradkhani, H., Yan, H., & Zarekarizi, M. 2017. Remote sensing of drought: vegetation, soil moisture, and data assimilation. 121–149, doi:10.1007/978-3-319-43744-6_7.
  18. Bahadur, K. 2018. NDVI, NDBI & NDWI calculation using landsat 7,8. Online: https://www.linkedin.com/pulse/ndvi-ndbi-ndwi-calculation-using-landsat-7-8-tek-bahadur-kshetri/%0Ahttps://www.linkedin.com/pulse/ndvi-ndbi-ndwi-calculation-using-landsat-7-8-tek-bahadur-kshetri.
  19. Karismawati, A., Sukmono, A., & Sasmito, B. (2019). Analisis perbandingan identifikasi kekeringan lahan sawah metode drought index dan vegetation index pada citra Landsat 8 (studi kasus: Kabupaten Kendal, Jawa Tengah). Jurnal Geodesi Undip, 8(4), 21–30.
  20. Shantiawan, P., & Suwardike, P. 2020. Adaptasi padi sawah (Oryza sativa L) terhadap peningkatan kelebihan air sebagai dampak pemanasan global. Agro Bali: Agricultural Journal, 2(2), 130–144, doi: 10.37637/ab.v2i2.415.
  21. Julianto, F. D., & Ediyanto, M. T. 2021. Analisis sebaran potensi kekeringan dengan cloud computing platform di Kabupaten Grobogan. Jurnal Ilmiah Teknik Geomatika IMAGI, 1, 23–30.
  22. Triana, A. N., Purnomo, R. H., & Khalid, F. 2021. Kajian kebutuhan air dan koefisien tanaman padi (Oryza sativa L) di lahan rawa lebak. Jurnal Keteknikan Pertanian, 9(1), 9–16.
  23. Supriyanto. 2019. Kebutuhan Air Pada Tanaman Padi. Online: http://cybex. pertanian.go.id/mobile/artikel/80004/KEBUTUHAN-AIR-PADA-TANAMAN-PADI/
  24. Zhang, J., Zhang, S., Cheng, M., Jiang, H., Zhang, X., Peng, C., Lu, X., Zhang, M., & Jin, J. (2018). Effect of Drought on Agronomic Traits of Rice and Wheat: A Meta-Analysis. International journal of environmental research and public health, 15(5), 839. https://doi.org/10.3390/ijerph15050839
  25. Govindan, V. (2005). Effect of water stress on yield of rice crop. International journal of Ecology & Development, 3, 77-89.

DOI: https://doi.org/10.13057/ijap.v13i1.70682

Refbacks

  • There are currently no refbacks.