Distribution of Drought on Agricultural Land in Palabuhanratu District Sukabumi Regency

Ayu Handayani(1), Hafid Setiadi(2),


(1) Department of Geography, Faculty of Mathematics and Natural Sciences, University of Indonesia, Indonesia
(2) Department of Geography, Faculty of Mathematics and Natural Sciences, University of Indonesia, Indonesia

Abstract

Drought is one of the natural disasters that causes substantial losses to food crop production, water supply in several important sectors such as industry, settlements, and agriculture. Climate change often causes drought on agricultural land and can indirectly threaten livelihoods and food security. This study aims to analyze the distribution of drought on agricultural land and examine the relationship between physical conditions. Drought monitoring study using remote sensing methods on Landsat 8 OLI imagery with the Normalized Difference Drought Index (NDDI) algorithm is the result of combining two parameters, namely the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). The results of the study show the distribution of agricultural land drought in Palabuhanratu District, Sukabumi Regency during 2018-2021 with five classes (normal, mild, moderate, severe, and very severe), and a very severe drought category of 80.78 ha in 2021, followed by 2018 an area of 32.09 ha. The most potential drought areas are in Palabuhanratu District, namely Jayanti Village and Citepus Village.

Keywords

Drought, Agricultural Land, Landsat 8, Pelabuhanratu District

Full Text:

PDF

References

Aini, R. N., Ratna, S., & Adi, W. (2019). Pola Sebaran Kekeringan Lahan Pertanian Kabupaten Serang Dengan Menggunakan Algoritma NDDI. Prosiding Simposium Infrastruktur Informasi Geospasial, kode makalah: SIIG-008

Badan Pusat Statistik. (2020). Kecamatan Palabuhanratu Dalam Angka 2020. Diambil dari: https://sukabumikab.bps.go.id/

BNPB. (2018). Potensi Bencana di Indonesia. Diambil dari: https://www.bnpb.go.id/home/potensi.

Julianto, F. D. (2021). Analisis Sebaran Potensi Kekeringan Dengan Cloud Computing Platform di Kabupaten Grobogan. Jurnal Ilmiah Geomatika (IMAGI), 1(1).

Fathony, A., Somantri, L., & Sugito, N. T. (2022). Analisis Potensi Kekeringan Pertanian di Kabupaten Bandung. Jurnal Geografi: Media Informasi Pengembangan dan Profesi Kegeografian, 19(1), 29-37.

Gu, Y., Brown, J. F.,Verdin, J.P. dan 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(L06407) 1–6.

Luqman, A. D., Wiyono, R. U. A., & Hidayah, E. Akurasi Pemetaan Kekeringan Lahan Pertanian Menggunakan Metode Normalized Difference Drought Index (NDDI) di Kecamatan Wuluhan dan Rambipuji Jember.

McFeeters. Stuart K. (2013). Using the Normalized Difference Water Index (NDWI) within a Geographic Information System to Detect Swimming Pools for Mosquito Abatement: A Practical Approach. Remote Sensing, 5, 3544–3561.

Perdana, A. M. P., Pratama, A. Y., Fauzi, A. I., Welly, T. K., & Nurtyawan, R. (2022). Analisis Spasio-temporal Kekeringan Pada Lahan Sawah di Lampung Selatan Berbasis Pengolahan Normalized Difference Drought Index Pada Citra Satelit Landsat 8. Jurnal Geosains dan Remote Sensing, 3(1), 1-9.

Rahman, F., Sukmono, A., & Yuwono, B. D. (2017). Analisis kekeringan pada lahan pertanian menggunakan metode nddi dan perka bnpb nomor 02 tahun 2012 (Studi kasus: Kabupaten kendal tahun 2015). Jurnal Geodesi UNDIP, 6(4), 274-284.

Widyastuti, R. (2020). Pola Sebaran Kekeringan di Kecamatan Simpenan Menggunakan Metode SPI (Standardized Precipitation Index). Jurnal Geosaintek, 6(1), 19-24.

Renza, D., Martinez, E., Arquero, A., & Sanchez, J. (2010, May). Drought estimation maps by means of multidate Landsat fused images. In Proceedings of the 30th EARSeL Symposium (pp. 775-782).

Sholihah, R. I., Trisasongko, B. H., Shiddiq, D., La Ode, S. I., Kusdaryanto, S., & Panuju, D. R. (2016). Identification of agricultural drought extent based on vegetation health indices of landsat data: case of Subang and Karawang, Indonesia. Procedia Environmental Sciences, 33, 14-20.

Sukmono, A., Rahman, F., & Yuwono, B. D. (2018). Pemanfaatan Teknologi Penginderaan Jauh untuk Deteksi Kekeringan Pertanian Menggunakan Metode Normalized Difference Drought Index di Kabupaten Kendal. Jurnal Geografi: Media Informasi Pengembangan dan Profesi Kegeografian, 14(2), 57-65.

Agus Suprihatin Utomo, A. S. U., M Pramono Hadi, M., & Emilya Nurjani, E. N. (2022). Analisis spasial temporal zona rawan kekeringan lahan pertanian berbasis remote sensing. Jurnal Ilmiah Sains dan Teknologi, 11(2), 112-127.

Refbacks

  • There are currently no refbacks.