Analisis spasial temporal zona rawan kekeringan lahan pertanian berbasis remote sensing
Agus Suprihatin Utomo(1*), M. Pramono Hadi(2), Emilya Nurjani(3)
(1) Ilmu Lingkungan Minat Geo-Informasi untuk Manajemen Bencana, Sekolah Pascasarjana, Universitas Gadjah Mada
(2) Fakultas Geografi, Universitas Gadjah Mada
(3) Fakultas Geografi, Universitas Gadjah Mada
(*) Corresponding Author
Abstract
A mapping model of drought-prone zones for agricultural land based on Geographic Information Systems is needed to determine the distribution of drought vulnerability levels that occured in Bantul Regency, DI Yogyakarta. This study aims to determine the estimated area of agricultural land drought based on the interpretation of aerial images. This study compares the performance of the drought potential index of agricultural land using the Normalized Difference Drought Index (NDDI) algorithm based on remote sensing technology/ Landsat 8 satellite imagery to identify the estimated zones indicated for agricultural land drought that occurred in Bantul Regency, based on trends in spatio-temporal data with recording intervals from the 2015 until 2020 data representative during the dry season. Comparisons were made by looking at the performance between indices extracted from Landsat 8 imagery data based on the value of the green vegetation parameter/ Normalized Difference Vegetation Index (NDVI) and the soil and vegetation moisture parameters/ Normalized Difference Water Index (NDWI). The method used in this research is descriptive correlative method: quantitative and qualitative deductive using geostatistical indicators based on big data analysis to measure and compare various data variables spatio-temporal. The distribution of agricultural land drought through the NDDI index transformation method on a normal, mild, moderate, to severe scale occurs in almost all areas of Bantul Regency. This happened, due to the influence of natural activities of the global climate phenomenon ENSO, the impact of the transition of the El Nino phenomenon to La Nina (wet drought) which was more dominant in 2016. The average area affected by drought in Bantul Regency on a normal scale affected was ± 6.500,49 ha, affected by mild drought was ± 17.192,16 ha, affected by moderate-scale drought was ± 8.636,155 ha, and affected by drought of heavy scale agricultural land was ± 2.407,485 ha.
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Adnyana, N. P., Putra, I. D. N. N., dan Purnawan, I. K. A. (2020). Implementation Drought Area Identifier Application Of East Bali Based On Remote Sensing. JURNAL ILMIAH MERPATI, Vol. 8 (No. 1), hal. 46–53. https://ojs.unud.ac.id/index.php/merpati/article/download/54389/34582
Astisiasari (2015) Comparative Assessment of NDVI Versus NDDI to Indicate Agricultural Drought : A Case Study Carried Out In District Of Gunungkidul, Province Of Yogyakarta Special Region. Universitas Gadjah Mada. Tersedia di: https://essay.utwente.nl/83970/.
BIG (2017) InaGeoportal - Badan Informasi Geospasial (BIG). Dapat diakses di: https://tanahair.indonesia.go.id/portal-web (Diakses pada: November 2020 dan Maret 2021).
Danoedoro, P. (2012) Pengantar Penginderaan Jauh Digital. 1st edn. Yogyakarta: Penerbit Andi. Tersedia di: https://www.researchgate.net/publication/302871328_PENGANTAR_PENGINDERAAN_JAUH_DIGITAL.
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), hal. 1–6. doi: 10.1029/2006GL029127.
Gu, Y., Hunt, E., Wardlow, B., Basara, J. B., Brown, J. F., dan Verdin, J. P. (2008) ‘Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data’, Geophysical Research Letters, 35(L22401), hal. 1–5. doi: 10.1029/2008GL035772.
Kurnia, K. D., D.K., S. dan Noraini, A. (2019) ‘Analisis Potensi Kekeringan Lahan Sawah dengan Menggunakan Metode Normalized Differency Drought Index (NDDI) dan Thermal Vegetation Index (TVI) (Studi Kasus : Kabupaten Bantul)’, hal. 1–8. Tersedia di: https://core.ac.uk/display/227424863.
Kurniawan, A. dan Isnaini, S. M. (2015) Keistimewaan Lingkungan Daerah Istimewa Yogyakarta. Yogyakarta: UGM Press.
LAPAN (2014) Katalog Data Resolusi Menengah (Katalog Landsat) Pustekdata LAPAN RI. Dapat diakses di: http://landsat-catalog.lapan.go.id/ (Diakses pada tanggal: 19 November 2020).
Putsanra, D. V. (2017) ‘Sejumlah Wilayah di Bantul DIY Dilanda Banjir Akibat Luapan Sungai’, tirto.id. Tersedia di: https://tirto.id/sejumlah-wilayah-di-bantul-diy-dilanda-banjir-akibat-luapan-sungai-djH5.
Rahardjo, W., Sukandarrumidi dan Rosidi, H. M. (1977) ‘Peta Geologi Lembar Yogyakarta Skala 1:100.000’.
Renza, D., Martinez, E., Arquero, A. dan Sanchez, J. (2010) ‘Drought Estimation Maps by Means of Multidate Landsat Fused Images’, Remote Sensing for Science, Education, and Natural and Cultural Heritage, hal. 775–782. Tersedia di: http://www.earsel.org/symposia/2010-symposium-Paris/Proceedings/EARSeL-Symposium-2010_17-03.pdf.
Rismayatika, F., Saraswati, R., Shidiq, I. P. A., dan Taqyyudin. (2020). Identification of Dry Areas on Agricultural Land using Normalized Difference Drought Index in Magetan Regency. IOP Conf. Series: Earth and Environmental Science - IOP Publishing, August, hal. 1–7. https://doi.org/10.1088/1755-1315/540/1/012029
DOI: https://doi.org/10.22146/teknosains.67932
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